Clinical Review

Abstract

Diagnostic errors in hospitalized patients are a leading cause of preventable morbidity and mortality. Significant challenges in defining and measuring diagnostic errors and underlying process failure points have led to considerable variability in reported rates of diagnostic errors and adverse outcomes. In this article, we explore the diagnostic process and its discrete components, emphasizing the centrality of the patient in decision-making as well as the continuous nature of the process. We review the incidence of diagnostic errors in hospitalized patients and different methodological approaches that have been used to arrive at these estimates. We discuss different but interdependent provider- and system-related process-failure points that lead to diagnostic errors. We examine specific challenges related to measurement of diagnostic errors and describe traditional and novel approaches that are being used to obtain the most precise estimates. Finally, we examine various patient-, provider-, and organizational-level interventions that have been proposed to improve diagnostic safety in hospitalized patients.

Keywords: diagnostic error, hospital medicine, patient safety.

Diagnosis is defined as a “pre-existing set of categories agreed upon by the medical profession to designate a specific condition.”¹ The diagnostic process involves obtaining a clinical history, performing a physical examination, conducting diagnostic testing, and consulting with other clinical providers to gather data that are relevant to understanding the underlying disease processes. This exercise involves generating hypotheses and updating prior probabilities as more information and evidence become available. Throughout this process of information gathering, integration, and interpretation, there is an ongoing assessment of whether sufficient and necessary knowledge has been obtained to make an accurate diagnosis and provide appropriate treatment.²

Diagnostic error is defined as a missed opportunity to make a timely diagnosis as part of this iterative process, including the failure of communicating the diagnosis to the patient in a timely manner.³ It can be categorized as a missed, delayed, or incorrect diagnosis based on available evidence at the time. Establishing the correct diagnosis has important implications. A timely and precise diagnosis ensures the patient the highest probability of having a positive health outcome that reflects an appropriate understanding of underlying disease processes and is consistent with their overall goals of care.³ When diagnostic errors occur, they can cause patient harm. Adverse events due to medical errors, including diagnostic errors, are estimated to be the third leading cause of death in the United States.⁴ Most people will experience at least 1 diagnostic error in their lifetime. In the 2015 National Academy of Medicine report Improving Diagnosis in Healthcare, diagnostic errors were identified as a major hazard as well as an opportunity to improve patient outcomes.²

Diagnostic errors during hospitalizations are especially concerning, as they are more likely to be implicated in a wider spectrum of harm, including permanent disability and death. This has become even more relevant for hospital medicine physicians and other clinical providers as they encounter increasing cognitive and administrative workloads, rising dissatisfaction and burnout, and unique obstacles such as night-time scheduling.⁵

Incidence of Diagnostic Errors in Hospitalized Patients

Several methodological approaches have been used to estimate the incidence of diagnostic errors in hospitalized patients. These include retrospective reviews of a sample of all hospital admissions, evaluations of selected adverse outcomes including autopsy studies, patient and provider surveys, and malpractice claims. Laboratory testing audits and secondary reviews in other diagnostic subspecialities (eg, radiology, pathology, and microbiology) are also essential to improving diagnostic performance in these specialized fields, which in turn affects overall hospital diagnostic error rates.^6-8 These diverse approaches provide unique insights regarding our ability to assess the degree to which potential harms, ranging from temporary impairment to permanent disability, to death, are attributable to different failure points in the diagnostic process.

Large retrospective chart reviews of random hospital admissions remain the most accurate way to determine the overall incidence of diagnostic errors in hospitalized patients.⁹ The Harvard Medical Practice Study, published in 1991, laid the groundwork for measuring the incidence of adverse events in hospitalized patients and assessing their relation to medical error, negligence, and disability. Reviewing 30,121 randomly selected records from 51 randomly selected acute care hospitals in New York State, the study found that adverse events occurred in 3.7% of hospitalizations, diagnostic errors accounted for 13.8% of these events, and these errors were likely attributable to negligence in 74.7% of cases. The study not only outlined individual-level process failures, but also focused attention on some of the systemic causes, setting the agenda for quality improvement research in hospital-based care for years to come.^10-12 A recent systematic review and meta-analysis of 22 hospital admission studies found a pooled rate of 0.7% (95% CI, 0.5%-1.1%) for harmful diagnostic errors.⁹ It found significant variations in the rates of adverse events, diagnostic errors, and range of diagnoses that were missed. This was primarily because of variabilities in pre-test probabilities in detecting diagnostic errors in these specific cohorts, as well as due to heterogeneity in study definitions and methodologies, especially regarding how they defined and measured “diagnostic error.” The analysis, however, did not account for diagnostic errors that were not related to patient harm (missed opportunities); therefore, it likely significantly underestimated the true incidence of diagnostic errors in these study populations. Table 1 summarizes some of key studies that have examined the incidence of harmful diagnostic errors in hospitalized patients.^9-21

The chief limitation of reviewing random hospital admissions is that, since overall rates of diagnostic errors are still relatively low, a large number of case reviews are required to identify a sufficient sample of adverse outcomes to gain a meaningful understanding of the underlying process failure points and develop tools for remediation. Patient and provider surveys or data from malpractice claims can be high-yield starting points for research on process errors.^22,23 Reviews of enriched cohorts of adverse outcomes, such as rapid-response events, intensive care unit (ICU) transfers, deaths, and hospital readmissions, can be an efficient way to identify process failures that lead to greatest harm. Depending on the research approach and the types of underlying patient populations sampled, rates of diagnostic errors in these high-risk groups have been estimated to be approximately 5% to 20%, or even higher.^6,24-31 For example, a retrospective study of 391 cases of unplanned 7-day readmissions found that 5.6% of cases contained at least 1 diagnostic error during the index admission.³² In a study conducted at 6 Belgian acute-care hospitals, 56% of patients requiring an unplanned transfer to a higher level of care were determined to have had an adverse event, and of these adverse events, 12.4% of cases were associated with errors in diagnosis.²⁹ A systematic review of 16 hospital-based studies estimated that 3.1% of all inpatient deaths were likely preventable, which corresponded to 22,165 deaths annually in the United States.³⁰ Another such review of 31 autopsy studies reported that 28% of autopsied ICU patients had at least 1 misdiagnosis; of these diagnostic errors, 8% were classified as potentially lethal, and 15% were considered major but not lethal.³¹ Significant drawbacks of such enriched cohort studies, however, are their poor generalizability and inability to detect failure points that do not lead to patient harm (near-miss events).³³

Causes of Diagnostic Errors in Hospitalized Patients

All aspects of the diagnostic process are susceptible to errors. These errors stem from a variety of faulty processes, including failure of the patient to engage with the health care system (eg, due to lack of insurance or transportation, or delay in seeking care); failure in information gathering (eg, missed history or exam findings, ordering wrong tests, laboratory errors); failure in information interpretation (eg, exam finding or test result misinterpretation); inaccurate hypothesis generation (eg, due to suboptimal prioritization or weighing of supporting evidence); and failure in communication (eg, with other team members or with the patient).^2,34 Reasons for diagnostic process failures vary widely across different health care settings. While clinician assessment errors (eg, failure to consider or alternatively overweigh competing diagnoses) and errors in testing and the monitoring phase (eg, failure to order or follow up diagnostic tests) can lead to a majority of diagnostic errors in some patient populations, in other settings, social (eg, poor health literacy, punitive cultural practices) and economic factors (eg, lack of access to appropriate diagnostic tests or to specialty expertise) play a more prominent role.^34,35

The Figure describes the relationship between components of the diagnostic process and subsequent outcomes, including diagnostic process failures, diagnostic errors, and absence or presence of patient harm.^2,36,37 It reemphasizes the centrality of the patient in decision-making and the continuous nature of the process. The Figure also illustrates that only a minority of process failures result in diagnostic errors, and a smaller proportion of diagnostic errors actually lead to patient harm. Conversely, it also shows that diagnostic errors can happen without any obvious process-failure points, and, similarly, patient harm can take place in the absence of any evident diagnostic errors.^36-38 Finally, it highlights the need to incorporate feedback from process failures, diagnostic errors, and favorable and unfavorable patient outcomes in order to inform future quality improvement efforts and research.

A significant proportion of diagnostic errors are due to system-related vulnerabilities, such as limitations in availability, adoption or quality of work force training, health informatics resources, and diagnostic capabilities. Lack of institutional culture that promotes safety and transparency also predisposes to diagnostic errors.^39,40 The other major domain of process failures is related to cognitive errors in clinician decision-making. Anchoring, confirmation bias, availability bias, and base-rate neglect are some of the common cognitive biases that, along with personality traits (aversion to risk or ambiguity, overconfidence) and affective biases (influence of emotion on decision-making), often determine the degree of utilization of resources and the possibility of suboptimal diagnostic performance.^41,42 Further, implicit biases related to age, race, gender, and sexual orientation contribute to disparities in access to health care and outcomes.⁴³ In a large number of cases of preventable adverse outcomes, however, there are multiple interdependent individual and system-related failure points that lead to diagnostic error and patient harm.^6,32

Challenges in Defining and Measuring Diagnostic Errors

In order to develop effective, evidence-based interventions to reduce diagnostic errors in hospitalized patients, it is essential to be able to first operationally define, and then accurately measure, diagnostic errors and the process failures that contribute to these errors in a standardized way that is reproducible across different settings.^6,44 There are a number of obstacles in this endeavor.

A fundamental problem is that establishing a diagnosis is not a single act but a process. Patterns of symptoms and clinical presentations often differ for the same disease. Information required to make a diagnosis is usually gathered in stages, where the clinician obtains additional data, while considering many possibilities, of which 1 may be ultimately correct. Diagnoses evolve over time and in different care settings. “The most likely diagnosis” is not always the same as “the final correct diagnosis.” Moreover, the diagnostic process is influenced by patients’ individual clinical courses and preferences over time. This makes determination of missed, delayed, or incorrect diagnoses challenging.^45,46

For hospitalized patients, generally the goal is to first rule out more serious and acute conditions (eg, pulmonary embolism or stroke), even if their probability is rather low. Conversely, a diagnosis that appears less consequential if delayed (eg, chronic anemia of unclear etiology) might not be pursued on an urgent basis, and is often left to outpatient providers to examine, but still may manifest in downstream harm (eg, delayed diagnosis of gastrointestinal malignancy or recurrent admissions for heart failure due to missed iron-deficiency anemia). Therefore, coming up with disease diagnosis likelihoods in hindsight may turn out to be highly subjective and not always accurate. This can be particularly difficult when clinician and other team deliberations are not recorded in their entirety.⁴⁷

Another hurdle in the practice of diagnostic medicine is to preserve the balance between underdiagnosing versus pursuing overly aggressive diagnostic approaches. Conducting laboratory, imaging, or other diagnostic studies without a clear shared understanding of how they would affect clinical decision-making (eg, use of prostate-specific antigen to detect prostate cancer) not only leads to increased costs but can also delay appropriate care. Worse, subsequent unnecessary diagnostic tests and treatments can sometimes lead to serious harm.^48,49

Finally, retrospective reviews by clinicians are subject to multiple potential limitations that include failure to create well-defined research questions, poorly developed inclusion and exclusion criteria, and issues related to inter- and intra-rater reliability.⁵⁰ These methodological deficiencies can occur despite following "best practice" guidelines during the study planning, execution, and analysis phases. They further add to the challenge of defining and measuring diagnostic errors.⁴⁷

Strategies to Improve Measurement of Diagnostic Errors

Development of new methodologies to reliably measure diagnostic errors is an area of active research. The advancement of uniform and universally agreed-upon frameworks to define and identify process failure points and diagnostic errors would help reduce measurement error and support development and testing of interventions that could be generalizable across different health care settings. To more accurately define and measure diagnostic errors, several novel approaches have been proposed (Table 2).

The Safer Dx framework is an all-round tool developed to advance the discipline of measuring diagnostic errors. For an episode of care under review, the instrument scores various items to determine the likelihood of a diagnostic error. These items evaluate multiple dimensions affecting diagnostic performance and measurements across 3 broad domains: structure (provider and organizational characteristics—from everyone involved with patient care, to computing infrastructure, to policies and regulations), process (elements of the patient-provider encounter, diagnostic test performance and follow-up, and subspecialty- and referral-specific factors), and outcome (establishing accurate and timely diagnosis as opposed to missed, delayed, or incorrect diagnosis). This instrument has been revised and can be further modified by a variety of stakeholders, including clinicians, health care organizations, and policymakers, to identify potential diagnostic errors in a standardized way for patient safety and quality improvement research.^51,52

Use of standardized tools, such as the Diagnosis Error Evaluation and Research (DEER) taxonomy, can help to identify and classify specific failure points across different diagnostic process dimensions.³⁷ These failure points can be classified into: issues related to patient presentation or access to health care; failure to obtain or misinterpretation of history or physical exam findings; errors in use of diagnostics tests due to technical or clinician-related factors; failures in appropriate weighing of evidence and hypothesis generation; errors associated with referral or consultation process; and failure to monitor the patient or obtain timely follow-up.³⁴ The DEER taxonomy can also be modified based on specific research questions and study populations. Further, it can be recategorized to correspond to Safer Dx framework diagnostic process dimensions to provide insights into reasons for specific process failures and to develop new interventions to mitigate errors and patient harm.⁶

Since a majority of diagnostic errors do not lead to actual harm, use of “triggers” or clues (eg, procedure-related complications, patient falls, transfers to a higher level of care, readmissions within 30 days) can be a more efficient method to identify diagnostic errors and adverse events that do cause harm. The Global Trigger Tool, developed by the Institute for Healthcare Improvement, uses this strategy. This tool has been shown to identify a significantly higher number of serious adverse events than comparable methods.⁵³ This facilitates selection and development of strategies at the institutional level that are most likely to improve patient outcomes.²⁴

Encouraging and facilitating voluntary or prompted reporting from patients and clinicians can also play an important role in capturing diagnostic errors. Patients and clinicians are not only the key stakeholders but are also uniquely placed within the diagnostic process to detect and report potential errors.^25,54 Patient-safety-event reporting systems, such as RL6, play a vital role in reporting near-misses and adverse events. These systems provide a mechanism for team members at all levels within the hospital to contribute toward reporting patient adverse events, including those arising from diagnostic errors.⁵⁵ The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first standardized, nationally reported patient survey designed to measure patients’ perceptions of their hospital experience. The US Centers for Medicare and Medicaid Services (CMS) publishes HCAHPS results on its website 4 times a year, which serves as an important incentive for hospitals to improve patient safety and quality of health care delivery.⁵⁶

Another novel approach links multiple symptoms to a range of target diseases using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework. Using “big data” technologies, this technique can help discover otherwise hidden symptom-disease links and improve overall diagnostic performance. This approach is proposed for both case-control (look-back) and cohort (look-forward) studies assessing diagnostic errors and misdiagnosis-related harms. For example, starting with a known diagnosis with high potential for harm (eg, stroke), the “look-back” approach can be used to identify high-risk symptoms (eg, dizziness, vertigo). In the “look-forward” approach, a single symptom or exposure risk factor known to be frequently misdiagnosed (eg, dizziness) can be analyzed to identify potential adverse disease outcomes (eg, stroke, migraine).⁵⁷

Many large ongoing studies looking at diagnostic errors among hospitalized patients, such as Utility of Predictive Systems to identify Inpatient Diagnostic Errors (UPSIDE),⁵⁸Patient Safety Learning Lab (PSLL),⁵⁹ and Achieving Diagnostic Excellence through Prevention and Teamwork (ADEPT),⁶⁰ are using structured chart review methodologies incorporating many of the above strategies in combination. Cases triggered by certain events (eg, ICU transfer, death, rapid response event, new or worsening acute kidney injury) are reviewed using validated tools, including Safer Dx framework and DEER taxonomy, to provide the most precise estimates of the burden of diagnostic errors in hospitalized patients. These estimates may be much higher than previously predicted using traditional chart review approaches.^6,24 For example, a recently published study of 2809 random admissions in 11 Massachusetts hospitals identified 978 adverse events but only 10 diagnostic errors (diagnostic error rate, 0.4%).¹⁹ This was likely because the trigger method used in the study did not specifically examine the diagnostic process as critically as done by the Safer Dx framework and DEER taxonomy tools, thereby underestimating the total number of diagnostic errors. Further, these ongoing studies (eg, UPSIDE, ADEPT) aim to employ new and upcoming advanced machine-learning methods to create models that can improve overall diagnostic performance. This would pave the way to test and build novel, efficient, and scalable interventions to reduce diagnostic errors and improve patient outcomes.

Strategies to Improve Diagnostic Safety in Hospitalized Patients

Disease-specific biomedical research, as well as advances in laboratory, imaging, and other technologies, play a critical role in improving diagnostic accuracy. However, these technical approaches do not address many of the broader clinician- and system-level failure points and opportunities for improvement. Various patient-, provider-, and organizational-level interventions that could make diagnostic processes more resilient and reduce the risk of error and patient harm have been proposed.⁶¹

Among these strategies are approaches to empower patients and their families. Fostering therapeutic relationships between patients and members of the care team is essential to reducing diagnostic errors.⁶² Facilitating timely access to health records, ensuring transparency in decision making, and tailoring communication strategies to patients’ cultural and educational backgrounds can reduce harm.⁶³ Similarly, at the system level, enhancing communication among different providers by use of tools such as structured handoffs can prevent communication breakdowns and facilitate positive outcomes.⁶⁴

Interventions targeted at individual health care providers, such as educational programs to improve content-specific knowledge, can enhance diagnostic performance. Regular feedback, strategies to enhance equity, and fostering an environment where all providers are actively encouraged to think critically and participate in the diagnostic process (training programs to use “diagnostic time-outs” and making it a “team sport”) can improve clinical reasoning.^65,66 Use of standardized patients can help identify individual-level cognitive failure points and facilitate creation of new interventions to improve clinical decision-making processes.⁶⁷

Novel health information technologies can further augment these efforts. These include effective documentation by maintaining dynamic and accurate patient histories, problem lists, and medication lists^68-70; use of electronic health record–based algorithms to identify potential diagnostic delays for serious conditions^71,72; use of telemedicine technologies to improve accessibility and coordination⁷³;application of mobile health and wearable technologies to facilitate data-gathering and care delivery^74,75; and use of computerized decision-support tools, including applications to interpret electrocardiograms, imaging studies, and other diagnostic tests.⁷⁶

Use of precision medicine, powered by new artificial intelligence (AI) tools, is becoming more widespread. Algorithms powered by AI can augment and sometimes even outperform clinician decision-making in areas such as oncology, radiology, and primary care.⁷⁷ Creation of large biobanks like the All of Us research program can be used to study thousands of environmental and genetic risk factors and health conditions simultaneously, and help identify specific treatments that work best for people of different backgrounds.⁷⁸ Active research in these areas holds great promise in terms of how and when we diagnose diseases and make appropriate preventative and treatment decisions. Significant scientific, ethical, and regulatory challenges will need to be overcome before these technologies can address some of the most complex problems in health care.⁷⁹

Finally, diagnostic performance is affected by the external environment, including the functioning of the medical liability system. Diagnostic errors that lead to patient harm are a leading cause of malpractice claims.⁸⁰ Developing a legal environment, in collaboration with patient advocacy groups and health care organizations, that promotes and facilitates timely disclosure of diagnostic errors could decrease the incentive to hide errors, advance care processes, and improve outcomes.^81,82

Conclusion

The burden of diagnostic errors in hospitalized patients is unacceptably high and remains an underemphasized cause of preventable morbidity and mortality. Diagnostic errors often result from a breakdown in multiple interdependent processes that involve patient-, provider-, and system-level factors. Significant challenges remain in defining and identifying diagnostic errors as well as underlying process-failure points. The most effective interventions to reduce diagnostic errors will require greater patient participation in the diagnostic process and a mix of evidence-based interventions that promote individual-provider excellence as well as system-level changes. Further research and collaboration among various stakeholders should help improve diagnostic safety for hospitalized patients.

Corresponding author: Abhishek Goyal, MD, MPH; [email protected]

Disclosures: Dr. Dalal disclosed receiving income ≥ $250 from MayaMD.

Abstract

Diagnostic errors in hospitalized patients are a leading cause of preventable morbidity and mortality. Significant challenges in defining and measuring diagnostic errors and underlying process failure points have led to considerable variability in reported rates of diagnostic errors and adverse outcomes. In this article, we explore the diagnostic process and its discrete components, emphasizing the centrality of the patient in decision-making as well as the continuous nature of the process. We review the incidence of diagnostic errors in hospitalized patients and different methodological approaches that have been used to arrive at these estimates. We discuss different but interdependent provider- and system-related process-failure points that lead to diagnostic errors. We examine specific challenges related to measurement of diagnostic errors and describe traditional and novel approaches that are being used to obtain the most precise estimates. Finally, we examine various patient-, provider-, and organizational-level interventions that have been proposed to improve diagnostic safety in hospitalized patients.

Keywords: diagnostic error, hospital medicine, patient safety.

Diagnosis is defined as a “pre-existing set of categories agreed upon by the medical profession to designate a specific condition.”¹ The diagnostic process involves obtaining a clinical history, performing a physical examination, conducting diagnostic testing, and consulting with other clinical providers to gather data that are relevant to understanding the underlying disease processes. This exercise involves generating hypotheses and updating prior probabilities as more information and evidence become available. Throughout this process of information gathering, integration, and interpretation, there is an ongoing assessment of whether sufficient and necessary knowledge has been obtained to make an accurate diagnosis and provide appropriate treatment.²

Diagnostic error is defined as a missed opportunity to make a timely diagnosis as part of this iterative process, including the failure of communicating the diagnosis to the patient in a timely manner.³ It can be categorized as a missed, delayed, or incorrect diagnosis based on available evidence at the time. Establishing the correct diagnosis has important implications. A timely and precise diagnosis ensures the patient the highest probability of having a positive health outcome that reflects an appropriate understanding of underlying disease processes and is consistent with their overall goals of care.³ When diagnostic errors occur, they can cause patient harm. Adverse events due to medical errors, including diagnostic errors, are estimated to be the third leading cause of death in the United States.⁴ Most people will experience at least 1 diagnostic error in their lifetime. In the 2015 National Academy of Medicine report Improving Diagnosis in Healthcare, diagnostic errors were identified as a major hazard as well as an opportunity to improve patient outcomes.²

Diagnostic errors during hospitalizations are especially concerning, as they are more likely to be implicated in a wider spectrum of harm, including permanent disability and death. This has become even more relevant for hospital medicine physicians and other clinical providers as they encounter increasing cognitive and administrative workloads, rising dissatisfaction and burnout, and unique obstacles such as night-time scheduling.⁵

Incidence of Diagnostic Errors in Hospitalized Patients

Several methodological approaches have been used to estimate the incidence of diagnostic errors in hospitalized patients. These include retrospective reviews of a sample of all hospital admissions, evaluations of selected adverse outcomes including autopsy studies, patient and provider surveys, and malpractice claims. Laboratory testing audits and secondary reviews in other diagnostic subspecialities (eg, radiology, pathology, and microbiology) are also essential to improving diagnostic performance in these specialized fields, which in turn affects overall hospital diagnostic error rates.^6-8 These diverse approaches provide unique insights regarding our ability to assess the degree to which potential harms, ranging from temporary impairment to permanent disability, to death, are attributable to different failure points in the diagnostic process.

Large retrospective chart reviews of random hospital admissions remain the most accurate way to determine the overall incidence of diagnostic errors in hospitalized patients.⁹ The Harvard Medical Practice Study, published in 1991, laid the groundwork for measuring the incidence of adverse events in hospitalized patients and assessing their relation to medical error, negligence, and disability. Reviewing 30,121 randomly selected records from 51 randomly selected acute care hospitals in New York State, the study found that adverse events occurred in 3.7% of hospitalizations, diagnostic errors accounted for 13.8% of these events, and these errors were likely attributable to negligence in 74.7% of cases. The study not only outlined individual-level process failures, but also focused attention on some of the systemic causes, setting the agenda for quality improvement research in hospital-based care for years to come.^10-12 A recent systematic review and meta-analysis of 22 hospital admission studies found a pooled rate of 0.7% (95% CI, 0.5%-1.1%) for harmful diagnostic errors.⁹ It found significant variations in the rates of adverse events, diagnostic errors, and range of diagnoses that were missed. This was primarily because of variabilities in pre-test probabilities in detecting diagnostic errors in these specific cohorts, as well as due to heterogeneity in study definitions and methodologies, especially regarding how they defined and measured “diagnostic error.” The analysis, however, did not account for diagnostic errors that were not related to patient harm (missed opportunities); therefore, it likely significantly underestimated the true incidence of diagnostic errors in these study populations. Table 1 summarizes some of key studies that have examined the incidence of harmful diagnostic errors in hospitalized patients.^9-21

The chief limitation of reviewing random hospital admissions is that, since overall rates of diagnostic errors are still relatively low, a large number of case reviews are required to identify a sufficient sample of adverse outcomes to gain a meaningful understanding of the underlying process failure points and develop tools for remediation. Patient and provider surveys or data from malpractice claims can be high-yield starting points for research on process errors.^22,23 Reviews of enriched cohorts of adverse outcomes, such as rapid-response events, intensive care unit (ICU) transfers, deaths, and hospital readmissions, can be an efficient way to identify process failures that lead to greatest harm. Depending on the research approach and the types of underlying patient populations sampled, rates of diagnostic errors in these high-risk groups have been estimated to be approximately 5% to 20%, or even higher.^6,24-31 For example, a retrospective study of 391 cases of unplanned 7-day readmissions found that 5.6% of cases contained at least 1 diagnostic error during the index admission.³² In a study conducted at 6 Belgian acute-care hospitals, 56% of patients requiring an unplanned transfer to a higher level of care were determined to have had an adverse event, and of these adverse events, 12.4% of cases were associated with errors in diagnosis.²⁹ A systematic review of 16 hospital-based studies estimated that 3.1% of all inpatient deaths were likely preventable, which corresponded to 22,165 deaths annually in the United States.³⁰ Another such review of 31 autopsy studies reported that 28% of autopsied ICU patients had at least 1 misdiagnosis; of these diagnostic errors, 8% were classified as potentially lethal, and 15% were considered major but not lethal.³¹ Significant drawbacks of such enriched cohort studies, however, are their poor generalizability and inability to detect failure points that do not lead to patient harm (near-miss events).³³

Causes of Diagnostic Errors in Hospitalized Patients

All aspects of the diagnostic process are susceptible to errors. These errors stem from a variety of faulty processes, including failure of the patient to engage with the health care system (eg, due to lack of insurance or transportation, or delay in seeking care); failure in information gathering (eg, missed history or exam findings, ordering wrong tests, laboratory errors); failure in information interpretation (eg, exam finding or test result misinterpretation); inaccurate hypothesis generation (eg, due to suboptimal prioritization or weighing of supporting evidence); and failure in communication (eg, with other team members or with the patient).^2,34 Reasons for diagnostic process failures vary widely across different health care settings. While clinician assessment errors (eg, failure to consider or alternatively overweigh competing diagnoses) and errors in testing and the monitoring phase (eg, failure to order or follow up diagnostic tests) can lead to a majority of diagnostic errors in some patient populations, in other settings, social (eg, poor health literacy, punitive cultural practices) and economic factors (eg, lack of access to appropriate diagnostic tests or to specialty expertise) play a more prominent role.^34,35

The Figure describes the relationship between components of the diagnostic process and subsequent outcomes, including diagnostic process failures, diagnostic errors, and absence or presence of patient harm.^2,36,37 It reemphasizes the centrality of the patient in decision-making and the continuous nature of the process. The Figure also illustrates that only a minority of process failures result in diagnostic errors, and a smaller proportion of diagnostic errors actually lead to patient harm. Conversely, it also shows that diagnostic errors can happen without any obvious process-failure points, and, similarly, patient harm can take place in the absence of any evident diagnostic errors.^36-38 Finally, it highlights the need to incorporate feedback from process failures, diagnostic errors, and favorable and unfavorable patient outcomes in order to inform future quality improvement efforts and research.

A significant proportion of diagnostic errors are due to system-related vulnerabilities, such as limitations in availability, adoption or quality of work force training, health informatics resources, and diagnostic capabilities. Lack of institutional culture that promotes safety and transparency also predisposes to diagnostic errors.^39,40 The other major domain of process failures is related to cognitive errors in clinician decision-making. Anchoring, confirmation bias, availability bias, and base-rate neglect are some of the common cognitive biases that, along with personality traits (aversion to risk or ambiguity, overconfidence) and affective biases (influence of emotion on decision-making), often determine the degree of utilization of resources and the possibility of suboptimal diagnostic performance.^41,42 Further, implicit biases related to age, race, gender, and sexual orientation contribute to disparities in access to health care and outcomes.⁴³ In a large number of cases of preventable adverse outcomes, however, there are multiple interdependent individual and system-related failure points that lead to diagnostic error and patient harm.^6,32

Challenges in Defining and Measuring Diagnostic Errors

In order to develop effective, evidence-based interventions to reduce diagnostic errors in hospitalized patients, it is essential to be able to first operationally define, and then accurately measure, diagnostic errors and the process failures that contribute to these errors in a standardized way that is reproducible across different settings.^6,44 There are a number of obstacles in this endeavor.

A fundamental problem is that establishing a diagnosis is not a single act but a process. Patterns of symptoms and clinical presentations often differ for the same disease. Information required to make a diagnosis is usually gathered in stages, where the clinician obtains additional data, while considering many possibilities, of which 1 may be ultimately correct. Diagnoses evolve over time and in different care settings. “The most likely diagnosis” is not always the same as “the final correct diagnosis.” Moreover, the diagnostic process is influenced by patients’ individual clinical courses and preferences over time. This makes determination of missed, delayed, or incorrect diagnoses challenging.^45,46

For hospitalized patients, generally the goal is to first rule out more serious and acute conditions (eg, pulmonary embolism or stroke), even if their probability is rather low. Conversely, a diagnosis that appears less consequential if delayed (eg, chronic anemia of unclear etiology) might not be pursued on an urgent basis, and is often left to outpatient providers to examine, but still may manifest in downstream harm (eg, delayed diagnosis of gastrointestinal malignancy or recurrent admissions for heart failure due to missed iron-deficiency anemia). Therefore, coming up with disease diagnosis likelihoods in hindsight may turn out to be highly subjective and not always accurate. This can be particularly difficult when clinician and other team deliberations are not recorded in their entirety.⁴⁷

Another hurdle in the practice of diagnostic medicine is to preserve the balance between underdiagnosing versus pursuing overly aggressive diagnostic approaches. Conducting laboratory, imaging, or other diagnostic studies without a clear shared understanding of how they would affect clinical decision-making (eg, use of prostate-specific antigen to detect prostate cancer) not only leads to increased costs but can also delay appropriate care. Worse, subsequent unnecessary diagnostic tests and treatments can sometimes lead to serious harm.^48,49

Finally, retrospective reviews by clinicians are subject to multiple potential limitations that include failure to create well-defined research questions, poorly developed inclusion and exclusion criteria, and issues related to inter- and intra-rater reliability.⁵⁰ These methodological deficiencies can occur despite following "best practice" guidelines during the study planning, execution, and analysis phases. They further add to the challenge of defining and measuring diagnostic errors.⁴⁷

Strategies to Improve Measurement of Diagnostic Errors

Development of new methodologies to reliably measure diagnostic errors is an area of active research. The advancement of uniform and universally agreed-upon frameworks to define and identify process failure points and diagnostic errors would help reduce measurement error and support development and testing of interventions that could be generalizable across different health care settings. To more accurately define and measure diagnostic errors, several novel approaches have been proposed (Table 2).

The Safer Dx framework is an all-round tool developed to advance the discipline of measuring diagnostic errors. For an episode of care under review, the instrument scores various items to determine the likelihood of a diagnostic error. These items evaluate multiple dimensions affecting diagnostic performance and measurements across 3 broad domains: structure (provider and organizational characteristics—from everyone involved with patient care, to computing infrastructure, to policies and regulations), process (elements of the patient-provider encounter, diagnostic test performance and follow-up, and subspecialty- and referral-specific factors), and outcome (establishing accurate and timely diagnosis as opposed to missed, delayed, or incorrect diagnosis). This instrument has been revised and can be further modified by a variety of stakeholders, including clinicians, health care organizations, and policymakers, to identify potential diagnostic errors in a standardized way for patient safety and quality improvement research.^51,52

Use of standardized tools, such as the Diagnosis Error Evaluation and Research (DEER) taxonomy, can help to identify and classify specific failure points across different diagnostic process dimensions.³⁷ These failure points can be classified into: issues related to patient presentation or access to health care; failure to obtain or misinterpretation of history or physical exam findings; errors in use of diagnostics tests due to technical or clinician-related factors; failures in appropriate weighing of evidence and hypothesis generation; errors associated with referral or consultation process; and failure to monitor the patient or obtain timely follow-up.³⁴ The DEER taxonomy can also be modified based on specific research questions and study populations. Further, it can be recategorized to correspond to Safer Dx framework diagnostic process dimensions to provide insights into reasons for specific process failures and to develop new interventions to mitigate errors and patient harm.⁶

Since a majority of diagnostic errors do not lead to actual harm, use of “triggers” or clues (eg, procedure-related complications, patient falls, transfers to a higher level of care, readmissions within 30 days) can be a more efficient method to identify diagnostic errors and adverse events that do cause harm. The Global Trigger Tool, developed by the Institute for Healthcare Improvement, uses this strategy. This tool has been shown to identify a significantly higher number of serious adverse events than comparable methods.⁵³ This facilitates selection and development of strategies at the institutional level that are most likely to improve patient outcomes.²⁴

Encouraging and facilitating voluntary or prompted reporting from patients and clinicians can also play an important role in capturing diagnostic errors. Patients and clinicians are not only the key stakeholders but are also uniquely placed within the diagnostic process to detect and report potential errors.^25,54 Patient-safety-event reporting systems, such as RL6, play a vital role in reporting near-misses and adverse events. These systems provide a mechanism for team members at all levels within the hospital to contribute toward reporting patient adverse events, including those arising from diagnostic errors.⁵⁵ The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first standardized, nationally reported patient survey designed to measure patients’ perceptions of their hospital experience. The US Centers for Medicare and Medicaid Services (CMS) publishes HCAHPS results on its website 4 times a year, which serves as an important incentive for hospitals to improve patient safety and quality of health care delivery.⁵⁶

Another novel approach links multiple symptoms to a range of target diseases using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework. Using “big data” technologies, this technique can help discover otherwise hidden symptom-disease links and improve overall diagnostic performance. This approach is proposed for both case-control (look-back) and cohort (look-forward) studies assessing diagnostic errors and misdiagnosis-related harms. For example, starting with a known diagnosis with high potential for harm (eg, stroke), the “look-back” approach can be used to identify high-risk symptoms (eg, dizziness, vertigo). In the “look-forward” approach, a single symptom or exposure risk factor known to be frequently misdiagnosed (eg, dizziness) can be analyzed to identify potential adverse disease outcomes (eg, stroke, migraine).⁵⁷

Many large ongoing studies looking at diagnostic errors among hospitalized patients, such as Utility of Predictive Systems to identify Inpatient Diagnostic Errors (UPSIDE),⁵⁸Patient Safety Learning Lab (PSLL),⁵⁹ and Achieving Diagnostic Excellence through Prevention and Teamwork (ADEPT),⁶⁰ are using structured chart review methodologies incorporating many of the above strategies in combination. Cases triggered by certain events (eg, ICU transfer, death, rapid response event, new or worsening acute kidney injury) are reviewed using validated tools, including Safer Dx framework and DEER taxonomy, to provide the most precise estimates of the burden of diagnostic errors in hospitalized patients. These estimates may be much higher than previously predicted using traditional chart review approaches.^6,24 For example, a recently published study of 2809 random admissions in 11 Massachusetts hospitals identified 978 adverse events but only 10 diagnostic errors (diagnostic error rate, 0.4%).¹⁹ This was likely because the trigger method used in the study did not specifically examine the diagnostic process as critically as done by the Safer Dx framework and DEER taxonomy tools, thereby underestimating the total number of diagnostic errors. Further, these ongoing studies (eg, UPSIDE, ADEPT) aim to employ new and upcoming advanced machine-learning methods to create models that can improve overall diagnostic performance. This would pave the way to test and build novel, efficient, and scalable interventions to reduce diagnostic errors and improve patient outcomes.

Strategies to Improve Diagnostic Safety in Hospitalized Patients

Disease-specific biomedical research, as well as advances in laboratory, imaging, and other technologies, play a critical role in improving diagnostic accuracy. However, these technical approaches do not address many of the broader clinician- and system-level failure points and opportunities for improvement. Various patient-, provider-, and organizational-level interventions that could make diagnostic processes more resilient and reduce the risk of error and patient harm have been proposed.⁶¹

Among these strategies are approaches to empower patients and their families. Fostering therapeutic relationships between patients and members of the care team is essential to reducing diagnostic errors.⁶² Facilitating timely access to health records, ensuring transparency in decision making, and tailoring communication strategies to patients’ cultural and educational backgrounds can reduce harm.⁶³ Similarly, at the system level, enhancing communication among different providers by use of tools such as structured handoffs can prevent communication breakdowns and facilitate positive outcomes.⁶⁴

Interventions targeted at individual health care providers, such as educational programs to improve content-specific knowledge, can enhance diagnostic performance. Regular feedback, strategies to enhance equity, and fostering an environment where all providers are actively encouraged to think critically and participate in the diagnostic process (training programs to use “diagnostic time-outs” and making it a “team sport”) can improve clinical reasoning.^65,66 Use of standardized patients can help identify individual-level cognitive failure points and facilitate creation of new interventions to improve clinical decision-making processes.⁶⁷

Novel health information technologies can further augment these efforts. These include effective documentation by maintaining dynamic and accurate patient histories, problem lists, and medication lists^68-70; use of electronic health record–based algorithms to identify potential diagnostic delays for serious conditions^71,72; use of telemedicine technologies to improve accessibility and coordination⁷³;application of mobile health and wearable technologies to facilitate data-gathering and care delivery^74,75; and use of computerized decision-support tools, including applications to interpret electrocardiograms, imaging studies, and other diagnostic tests.⁷⁶

Use of precision medicine, powered by new artificial intelligence (AI) tools, is becoming more widespread. Algorithms powered by AI can augment and sometimes even outperform clinician decision-making in areas such as oncology, radiology, and primary care.⁷⁷ Creation of large biobanks like the All of Us research program can be used to study thousands of environmental and genetic risk factors and health conditions simultaneously, and help identify specific treatments that work best for people of different backgrounds.⁷⁸ Active research in these areas holds great promise in terms of how and when we diagnose diseases and make appropriate preventative and treatment decisions. Significant scientific, ethical, and regulatory challenges will need to be overcome before these technologies can address some of the most complex problems in health care.⁷⁹

Finally, diagnostic performance is affected by the external environment, including the functioning of the medical liability system. Diagnostic errors that lead to patient harm are a leading cause of malpractice claims.⁸⁰ Developing a legal environment, in collaboration with patient advocacy groups and health care organizations, that promotes and facilitates timely disclosure of diagnostic errors could decrease the incentive to hide errors, advance care processes, and improve outcomes.^81,82

Conclusion

The burden of diagnostic errors in hospitalized patients is unacceptably high and remains an underemphasized cause of preventable morbidity and mortality. Diagnostic errors often result from a breakdown in multiple interdependent processes that involve patient-, provider-, and system-level factors. Significant challenges remain in defining and identifying diagnostic errors as well as underlying process-failure points. The most effective interventions to reduce diagnostic errors will require greater patient participation in the diagnostic process and a mix of evidence-based interventions that promote individual-provider excellence as well as system-level changes. Further research and collaboration among various stakeholders should help improve diagnostic safety for hospitalized patients.

Corresponding author: Abhishek Goyal, MD, MPH; [email protected]

Disclosures: Dr. Dalal disclosed receiving income ≥ $250 from MayaMD.

Abstract

Diagnostic errors in hospitalized patients are a leading cause of preventable morbidity and mortality. Significant challenges in defining and measuring diagnostic errors and underlying process failure points have led to considerable variability in reported rates of diagnostic errors and adverse outcomes. In this article, we explore the diagnostic process and its discrete components, emphasizing the centrality of the patient in decision-making as well as the continuous nature of the process. We review the incidence of diagnostic errors in hospitalized patients and different methodological approaches that have been used to arrive at these estimates. We discuss different but interdependent provider- and system-related process-failure points that lead to diagnostic errors. We examine specific challenges related to measurement of diagnostic errors and describe traditional and novel approaches that are being used to obtain the most precise estimates. Finally, we examine various patient-, provider-, and organizational-level interventions that have been proposed to improve diagnostic safety in hospitalized patients.

Keywords: diagnostic error, hospital medicine, patient safety.

Diagnosis is defined as a “pre-existing set of categories agreed upon by the medical profession to designate a specific condition.”¹ The diagnostic process involves obtaining a clinical history, performing a physical examination, conducting diagnostic testing, and consulting with other clinical providers to gather data that are relevant to understanding the underlying disease processes. This exercise involves generating hypotheses and updating prior probabilities as more information and evidence become available. Throughout this process of information gathering, integration, and interpretation, there is an ongoing assessment of whether sufficient and necessary knowledge has been obtained to make an accurate diagnosis and provide appropriate treatment.²

Diagnostic error is defined as a missed opportunity to make a timely diagnosis as part of this iterative process, including the failure of communicating the diagnosis to the patient in a timely manner.³ It can be categorized as a missed, delayed, or incorrect diagnosis based on available evidence at the time. Establishing the correct diagnosis has important implications. A timely and precise diagnosis ensures the patient the highest probability of having a positive health outcome that reflects an appropriate understanding of underlying disease processes and is consistent with their overall goals of care.³ When diagnostic errors occur, they can cause patient harm. Adverse events due to medical errors, including diagnostic errors, are estimated to be the third leading cause of death in the United States.⁴ Most people will experience at least 1 diagnostic error in their lifetime. In the 2015 National Academy of Medicine report Improving Diagnosis in Healthcare, diagnostic errors were identified as a major hazard as well as an opportunity to improve patient outcomes.²

Diagnostic errors during hospitalizations are especially concerning, as they are more likely to be implicated in a wider spectrum of harm, including permanent disability and death. This has become even more relevant for hospital medicine physicians and other clinical providers as they encounter increasing cognitive and administrative workloads, rising dissatisfaction and burnout, and unique obstacles such as night-time scheduling.⁵

Incidence of Diagnostic Errors in Hospitalized Patients

Several methodological approaches have been used to estimate the incidence of diagnostic errors in hospitalized patients. These include retrospective reviews of a sample of all hospital admissions, evaluations of selected adverse outcomes including autopsy studies, patient and provider surveys, and malpractice claims. Laboratory testing audits and secondary reviews in other diagnostic subspecialities (eg, radiology, pathology, and microbiology) are also essential to improving diagnostic performance in these specialized fields, which in turn affects overall hospital diagnostic error rates.^6-8 These diverse approaches provide unique insights regarding our ability to assess the degree to which potential harms, ranging from temporary impairment to permanent disability, to death, are attributable to different failure points in the diagnostic process.

Large retrospective chart reviews of random hospital admissions remain the most accurate way to determine the overall incidence of diagnostic errors in hospitalized patients.⁹ The Harvard Medical Practice Study, published in 1991, laid the groundwork for measuring the incidence of adverse events in hospitalized patients and assessing their relation to medical error, negligence, and disability. Reviewing 30,121 randomly selected records from 51 randomly selected acute care hospitals in New York State, the study found that adverse events occurred in 3.7% of hospitalizations, diagnostic errors accounted for 13.8% of these events, and these errors were likely attributable to negligence in 74.7% of cases. The study not only outlined individual-level process failures, but also focused attention on some of the systemic causes, setting the agenda for quality improvement research in hospital-based care for years to come.^10-12 A recent systematic review and meta-analysis of 22 hospital admission studies found a pooled rate of 0.7% (95% CI, 0.5%-1.1%) for harmful diagnostic errors.⁹ It found significant variations in the rates of adverse events, diagnostic errors, and range of diagnoses that were missed. This was primarily because of variabilities in pre-test probabilities in detecting diagnostic errors in these specific cohorts, as well as due to heterogeneity in study definitions and methodologies, especially regarding how they defined and measured “diagnostic error.” The analysis, however, did not account for diagnostic errors that were not related to patient harm (missed opportunities); therefore, it likely significantly underestimated the true incidence of diagnostic errors in these study populations. Table 1 summarizes some of key studies that have examined the incidence of harmful diagnostic errors in hospitalized patients.^9-21

The chief limitation of reviewing random hospital admissions is that, since overall rates of diagnostic errors are still relatively low, a large number of case reviews are required to identify a sufficient sample of adverse outcomes to gain a meaningful understanding of the underlying process failure points and develop tools for remediation. Patient and provider surveys or data from malpractice claims can be high-yield starting points for research on process errors.^22,23 Reviews of enriched cohorts of adverse outcomes, such as rapid-response events, intensive care unit (ICU) transfers, deaths, and hospital readmissions, can be an efficient way to identify process failures that lead to greatest harm. Depending on the research approach and the types of underlying patient populations sampled, rates of diagnostic errors in these high-risk groups have been estimated to be approximately 5% to 20%, or even higher.^6,24-31 For example, a retrospective study of 391 cases of unplanned 7-day readmissions found that 5.6% of cases contained at least 1 diagnostic error during the index admission.³² In a study conducted at 6 Belgian acute-care hospitals, 56% of patients requiring an unplanned transfer to a higher level of care were determined to have had an adverse event, and of these adverse events, 12.4% of cases were associated with errors in diagnosis.²⁹ A systematic review of 16 hospital-based studies estimated that 3.1% of all inpatient deaths were likely preventable, which corresponded to 22,165 deaths annually in the United States.³⁰ Another such review of 31 autopsy studies reported that 28% of autopsied ICU patients had at least 1 misdiagnosis; of these diagnostic errors, 8% were classified as potentially lethal, and 15% were considered major but not lethal.³¹ Significant drawbacks of such enriched cohort studies, however, are their poor generalizability and inability to detect failure points that do not lead to patient harm (near-miss events).³³

Causes of Diagnostic Errors in Hospitalized Patients

All aspects of the diagnostic process are susceptible to errors. These errors stem from a variety of faulty processes, including failure of the patient to engage with the health care system (eg, due to lack of insurance or transportation, or delay in seeking care); failure in information gathering (eg, missed history or exam findings, ordering wrong tests, laboratory errors); failure in information interpretation (eg, exam finding or test result misinterpretation); inaccurate hypothesis generation (eg, due to suboptimal prioritization or weighing of supporting evidence); and failure in communication (eg, with other team members or with the patient).^2,34 Reasons for diagnostic process failures vary widely across different health care settings. While clinician assessment errors (eg, failure to consider or alternatively overweigh competing diagnoses) and errors in testing and the monitoring phase (eg, failure to order or follow up diagnostic tests) can lead to a majority of diagnostic errors in some patient populations, in other settings, social (eg, poor health literacy, punitive cultural practices) and economic factors (eg, lack of access to appropriate diagnostic tests or to specialty expertise) play a more prominent role.^34,35

The Figure describes the relationship between components of the diagnostic process and subsequent outcomes, including diagnostic process failures, diagnostic errors, and absence or presence of patient harm.^2,36,37 It reemphasizes the centrality of the patient in decision-making and the continuous nature of the process. The Figure also illustrates that only a minority of process failures result in diagnostic errors, and a smaller proportion of diagnostic errors actually lead to patient harm. Conversely, it also shows that diagnostic errors can happen without any obvious process-failure points, and, similarly, patient harm can take place in the absence of any evident diagnostic errors.^36-38 Finally, it highlights the need to incorporate feedback from process failures, diagnostic errors, and favorable and unfavorable patient outcomes in order to inform future quality improvement efforts and research.

A significant proportion of diagnostic errors are due to system-related vulnerabilities, such as limitations in availability, adoption or quality of work force training, health informatics resources, and diagnostic capabilities. Lack of institutional culture that promotes safety and transparency also predisposes to diagnostic errors.^39,40 The other major domain of process failures is related to cognitive errors in clinician decision-making. Anchoring, confirmation bias, availability bias, and base-rate neglect are some of the common cognitive biases that, along with personality traits (aversion to risk or ambiguity, overconfidence) and affective biases (influence of emotion on decision-making), often determine the degree of utilization of resources and the possibility of suboptimal diagnostic performance.^41,42 Further, implicit biases related to age, race, gender, and sexual orientation contribute to disparities in access to health care and outcomes.⁴³ In a large number of cases of preventable adverse outcomes, however, there are multiple interdependent individual and system-related failure points that lead to diagnostic error and patient harm.^6,32

Challenges in Defining and Measuring Diagnostic Errors

In order to develop effective, evidence-based interventions to reduce diagnostic errors in hospitalized patients, it is essential to be able to first operationally define, and then accurately measure, diagnostic errors and the process failures that contribute to these errors in a standardized way that is reproducible across different settings.^6,44 There are a number of obstacles in this endeavor.

A fundamental problem is that establishing a diagnosis is not a single act but a process. Patterns of symptoms and clinical presentations often differ for the same disease. Information required to make a diagnosis is usually gathered in stages, where the clinician obtains additional data, while considering many possibilities, of which 1 may be ultimately correct. Diagnoses evolve over time and in different care settings. “The most likely diagnosis” is not always the same as “the final correct diagnosis.” Moreover, the diagnostic process is influenced by patients’ individual clinical courses and preferences over time. This makes determination of missed, delayed, or incorrect diagnoses challenging.^45,46

For hospitalized patients, generally the goal is to first rule out more serious and acute conditions (eg, pulmonary embolism or stroke), even if their probability is rather low. Conversely, a diagnosis that appears less consequential if delayed (eg, chronic anemia of unclear etiology) might not be pursued on an urgent basis, and is often left to outpatient providers to examine, but still may manifest in downstream harm (eg, delayed diagnosis of gastrointestinal malignancy or recurrent admissions for heart failure due to missed iron-deficiency anemia). Therefore, coming up with disease diagnosis likelihoods in hindsight may turn out to be highly subjective and not always accurate. This can be particularly difficult when clinician and other team deliberations are not recorded in their entirety.⁴⁷

Another hurdle in the practice of diagnostic medicine is to preserve the balance between underdiagnosing versus pursuing overly aggressive diagnostic approaches. Conducting laboratory, imaging, or other diagnostic studies without a clear shared understanding of how they would affect clinical decision-making (eg, use of prostate-specific antigen to detect prostate cancer) not only leads to increased costs but can also delay appropriate care. Worse, subsequent unnecessary diagnostic tests and treatments can sometimes lead to serious harm.^48,49

Finally, retrospective reviews by clinicians are subject to multiple potential limitations that include failure to create well-defined research questions, poorly developed inclusion and exclusion criteria, and issues related to inter- and intra-rater reliability.⁵⁰ These methodological deficiencies can occur despite following "best practice" guidelines during the study planning, execution, and analysis phases. They further add to the challenge of defining and measuring diagnostic errors.⁴⁷

Strategies to Improve Measurement of Diagnostic Errors

Development of new methodologies to reliably measure diagnostic errors is an area of active research. The advancement of uniform and universally agreed-upon frameworks to define and identify process failure points and diagnostic errors would help reduce measurement error and support development and testing of interventions that could be generalizable across different health care settings. To more accurately define and measure diagnostic errors, several novel approaches have been proposed (Table 2).

The Safer Dx framework is an all-round tool developed to advance the discipline of measuring diagnostic errors. For an episode of care under review, the instrument scores various items to determine the likelihood of a diagnostic error. These items evaluate multiple dimensions affecting diagnostic performance and measurements across 3 broad domains: structure (provider and organizational characteristics—from everyone involved with patient care, to computing infrastructure, to policies and regulations), process (elements of the patient-provider encounter, diagnostic test performance and follow-up, and subspecialty- and referral-specific factors), and outcome (establishing accurate and timely diagnosis as opposed to missed, delayed, or incorrect diagnosis). This instrument has been revised and can be further modified by a variety of stakeholders, including clinicians, health care organizations, and policymakers, to identify potential diagnostic errors in a standardized way for patient safety and quality improvement research.^51,52

Use of standardized tools, such as the Diagnosis Error Evaluation and Research (DEER) taxonomy, can help to identify and classify specific failure points across different diagnostic process dimensions.³⁷ These failure points can be classified into: issues related to patient presentation or access to health care; failure to obtain or misinterpretation of history or physical exam findings; errors in use of diagnostics tests due to technical or clinician-related factors; failures in appropriate weighing of evidence and hypothesis generation; errors associated with referral or consultation process; and failure to monitor the patient or obtain timely follow-up.³⁴ The DEER taxonomy can also be modified based on specific research questions and study populations. Further, it can be recategorized to correspond to Safer Dx framework diagnostic process dimensions to provide insights into reasons for specific process failures and to develop new interventions to mitigate errors and patient harm.⁶

Since a majority of diagnostic errors do not lead to actual harm, use of “triggers” or clues (eg, procedure-related complications, patient falls, transfers to a higher level of care, readmissions within 30 days) can be a more efficient method to identify diagnostic errors and adverse events that do cause harm. The Global Trigger Tool, developed by the Institute for Healthcare Improvement, uses this strategy. This tool has been shown to identify a significantly higher number of serious adverse events than comparable methods.⁵³ This facilitates selection and development of strategies at the institutional level that are most likely to improve patient outcomes.²⁴

Encouraging and facilitating voluntary or prompted reporting from patients and clinicians can also play an important role in capturing diagnostic errors. Patients and clinicians are not only the key stakeholders but are also uniquely placed within the diagnostic process to detect and report potential errors.^25,54 Patient-safety-event reporting systems, such as RL6, play a vital role in reporting near-misses and adverse events. These systems provide a mechanism for team members at all levels within the hospital to contribute toward reporting patient adverse events, including those arising from diagnostic errors.⁵⁵ The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first standardized, nationally reported patient survey designed to measure patients’ perceptions of their hospital experience. The US Centers for Medicare and Medicaid Services (CMS) publishes HCAHPS results on its website 4 times a year, which serves as an important incentive for hospitals to improve patient safety and quality of health care delivery.⁵⁶

Another novel approach links multiple symptoms to a range of target diseases using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework. Using “big data” technologies, this technique can help discover otherwise hidden symptom-disease links and improve overall diagnostic performance. This approach is proposed for both case-control (look-back) and cohort (look-forward) studies assessing diagnostic errors and misdiagnosis-related harms. For example, starting with a known diagnosis with high potential for harm (eg, stroke), the “look-back” approach can be used to identify high-risk symptoms (eg, dizziness, vertigo). In the “look-forward” approach, a single symptom or exposure risk factor known to be frequently misdiagnosed (eg, dizziness) can be analyzed to identify potential adverse disease outcomes (eg, stroke, migraine).⁵⁷

Many large ongoing studies looking at diagnostic errors among hospitalized patients, such as Utility of Predictive Systems to identify Inpatient Diagnostic Errors (UPSIDE),⁵⁸Patient Safety Learning Lab (PSLL),⁵⁹ and Achieving Diagnostic Excellence through Prevention and Teamwork (ADEPT),⁶⁰ are using structured chart review methodologies incorporating many of the above strategies in combination. Cases triggered by certain events (eg, ICU transfer, death, rapid response event, new or worsening acute kidney injury) are reviewed using validated tools, including Safer Dx framework and DEER taxonomy, to provide the most precise estimates of the burden of diagnostic errors in hospitalized patients. These estimates may be much higher than previously predicted using traditional chart review approaches.^6,24 For example, a recently published study of 2809 random admissions in 11 Massachusetts hospitals identified 978 adverse events but only 10 diagnostic errors (diagnostic error rate, 0.4%).¹⁹ This was likely because the trigger method used in the study did not specifically examine the diagnostic process as critically as done by the Safer Dx framework and DEER taxonomy tools, thereby underestimating the total number of diagnostic errors. Further, these ongoing studies (eg, UPSIDE, ADEPT) aim to employ new and upcoming advanced machine-learning methods to create models that can improve overall diagnostic performance. This would pave the way to test and build novel, efficient, and scalable interventions to reduce diagnostic errors and improve patient outcomes.

Strategies to Improve Diagnostic Safety in Hospitalized Patients

Disease-specific biomedical research, as well as advances in laboratory, imaging, and other technologies, play a critical role in improving diagnostic accuracy. However, these technical approaches do not address many of the broader clinician- and system-level failure points and opportunities for improvement. Various patient-, provider-, and organizational-level interventions that could make diagnostic processes more resilient and reduce the risk of error and patient harm have been proposed.⁶¹

Among these strategies are approaches to empower patients and their families. Fostering therapeutic relationships between patients and members of the care team is essential to reducing diagnostic errors.⁶² Facilitating timely access to health records, ensuring transparency in decision making, and tailoring communication strategies to patients’ cultural and educational backgrounds can reduce harm.⁶³ Similarly, at the system level, enhancing communication among different providers by use of tools such as structured handoffs can prevent communication breakdowns and facilitate positive outcomes.⁶⁴

Interventions targeted at individual health care providers, such as educational programs to improve content-specific knowledge, can enhance diagnostic performance. Regular feedback, strategies to enhance equity, and fostering an environment where all providers are actively encouraged to think critically and participate in the diagnostic process (training programs to use “diagnostic time-outs” and making it a “team sport”) can improve clinical reasoning.^65,66 Use of standardized patients can help identify individual-level cognitive failure points and facilitate creation of new interventions to improve clinical decision-making processes.⁶⁷

Novel health information technologies can further augment these efforts. These include effective documentation by maintaining dynamic and accurate patient histories, problem lists, and medication lists^68-70; use of electronic health record–based algorithms to identify potential diagnostic delays for serious conditions^71,72; use of telemedicine technologies to improve accessibility and coordination⁷³;application of mobile health and wearable technologies to facilitate data-gathering and care delivery^74,75; and use of computerized decision-support tools, including applications to interpret electrocardiograms, imaging studies, and other diagnostic tests.⁷⁶

Use of precision medicine, powered by new artificial intelligence (AI) tools, is becoming more widespread. Algorithms powered by AI can augment and sometimes even outperform clinician decision-making in areas such as oncology, radiology, and primary care.⁷⁷ Creation of large biobanks like the All of Us research program can be used to study thousands of environmental and genetic risk factors and health conditions simultaneously, and help identify specific treatments that work best for people of different backgrounds.⁷⁸ Active research in these areas holds great promise in terms of how and when we diagnose diseases and make appropriate preventative and treatment decisions. Significant scientific, ethical, and regulatory challenges will need to be overcome before these technologies can address some of the most complex problems in health care.⁷⁹

Finally, diagnostic performance is affected by the external environment, including the functioning of the medical liability system. Diagnostic errors that lead to patient harm are a leading cause of malpractice claims.⁸⁰ Developing a legal environment, in collaboration with patient advocacy groups and health care organizations, that promotes and facilitates timely disclosure of diagnostic errors could decrease the incentive to hide errors, advance care processes, and improve outcomes.^81,82

Conclusion

The burden of diagnostic errors in hospitalized patients is unacceptably high and remains an underemphasized cause of preventable morbidity and mortality. Diagnostic errors often result from a breakdown in multiple interdependent processes that involve patient-, provider-, and system-level factors. Significant challenges remain in defining and identifying diagnostic errors as well as underlying process-failure points. The most effective interventions to reduce diagnostic errors will require greater patient participation in the diagnostic process and a mix of evidence-based interventions that promote individual-provider excellence as well as system-level changes. Further research and collaboration among various stakeholders should help improve diagnostic safety for hospitalized patients.

Corresponding author: Abhishek Goyal, MD, MPH; [email protected]

Disclosures: Dr. Dalal disclosed receiving income ≥ $250 from MayaMD.

Photo: Shutterstock

Six months after the Supreme Court decision that overturned the constitutional right to abortion, trainees across the United States are asking a critical question in the current resident recruitment season: How will the restrictions on abortion access affect my training as an obstetrician-gynecologist, and will they impact my ability to be the kind of provider I want to be in the future?

Among the myriad of downstream effects to patient care, the Dobbs decision will indisputably impact the scope of residency training for those that provide reproductive health services. Almost half of ObGyn residents train in states that have abortion restrictions in place.¹ New educational milestones for abortion training, which are a requirement by the Accreditation Council for Graduate Medical Education (ACGME), were proposed quickly after Dobbs, guiding programs to offer opportunities for training in nonrestricted areas or the “combination of didactic activities, including simulation” to meet the training requirement in abortion care.²

Like many providers, residents already are grappling with precarious and risky circumstances, balancing patient safety and patient-driven care amidst pre-existing and newly enforced abortion restrictions. Whether managing a patient with an undesired pregnancy, severe medical comorbidities, unexpected pregnancy complications such as preterm premature rupture of membranes, or bleeding, or substantial fetal anomalies, ObGyn residents cannot gain the experience of providing the full scope of reproductive health care without the ability to offer all possible management options. While some enacted abortion restrictions have exceptions for the health of or life-saving measures for the mother, there is no standard guidance for timing of interventions, leaving providers confused and in fear of legal retribution. At a time when trainees should be learning to provide patient-centered, evidence-based care, they are instead paralyzed by the legal or professional consequences they may face for offering their best medical judgements.

Furthermore, the lack of exposure to dilation and evacuation procedures for residents in restricted practice areas will undoubtably decrease their confidence in managing acute complications, which is one of the critical facets of residency training. In a surgical field where repetition is crucial for technical competence, highlighted by ACGME minimum case requirements, the decreased volume of abortion procedures is a disadvantage for trainees and a disservice for patients. While anti-choice promoters may argue that involvement in surgical management of early pregnancy loss should suffice for ObGyn training in family planning, this piecemeal approach will leave gaps in technical skills.

The fear of legal ramifications, moral injury, and inadequate surgical training may lead to the siphoning of talented trainees to areas in the country with fewer restrictions.³Dobbs already has demonstrated how limiting abortion access will deepen inequities in reproductive health care service delivery. Approximately 55% of ObGyn trainees and nearly two-thirds of maternal-fetal medicine graduates join the workforce in the state where they received their training.⁴ Medical students will seek opportunities for high-quality ObGyn training in areas that will help them to be well-prepared, competent physicians—and more often than not, stay in the area or region that they trained in. This will lead to provider shortages in areas where access to reproductive health care and subspecialist providers already is limited, further exacerbating existing health disparities.

During this recruitment season, trainees and residency programs alike will need to reckon with how the ramifications of Dobbs will alter both the immediate and long-term training in comprehensive reproductive health care for the ObGyn workforce. ObGyn trainees have taken a stand in response to the Dobbs decision, and nearly 750 current residents signed onto the statement below as a commitment to high-quality training and patient-centered care. Clinical experience in performing abortions is essential to the provision of comprehensive evidence-based reproductive health care, and access to these procedures is as important for physicians-in-training as it is for patients.

Actions to take to ensure high-quality abortion training in ObGyn residencies include the following:

• Connect with and stay involved with organizations such as the American College of Obstetricians and Gynecologists (ACOG), Physicians for Reproductive Health (PRH), and Medical Students for Choice (MSFC) for initiatives, toolkits, and resources for training at your institutions.
• Seek specific abortion training opportunities through the Leadership Training Academy (offered through PRH) or the Abortion Training Institute (offered through MSFC).
• Ensure that your residency program meets the ACGME criteria of providing opportunities for clinical experiences for abortion care and work with program leadership at a program, state, or regional level to enforce these competencies.
• Reach out to your local American Civil Liberties Union or other local reproductive legal rights organizations if you want to be involved with advocacy around abortion access and training but have concerns about legal protections.
• Have a voice at the table for empowering training opportunities by seeking leadership positions through ACOG, ACGME, Council on Resident Education in Obstetrics and Gynecology and the Association of Professors of Gynecology and Obstetrics, American Medical Association, Student National Medical Association, and subspecialty organizations.
• Vote in every election and promote voting registration and access to your patients, colleagues, and communities. ●

Continue to: The implications of the Dobbs v Jackson Women’s Health Organization decision on the health care and wellbeing of our patients...

Photo: Shutterstock

Six months after the Supreme Court decision that overturned the constitutional right to abortion, trainees across the United States are asking a critical question in the current resident recruitment season: How will the restrictions on abortion access affect my training as an obstetrician-gynecologist, and will they impact my ability to be the kind of provider I want to be in the future?

Among the myriad of downstream effects to patient care, the Dobbs decision will indisputably impact the scope of residency training for those that provide reproductive health services. Almost half of ObGyn residents train in states that have abortion restrictions in place.¹ New educational milestones for abortion training, which are a requirement by the Accreditation Council for Graduate Medical Education (ACGME), were proposed quickly after Dobbs, guiding programs to offer opportunities for training in nonrestricted areas or the “combination of didactic activities, including simulation” to meet the training requirement in abortion care.²

Like many providers, residents already are grappling with precarious and risky circumstances, balancing patient safety and patient-driven care amidst pre-existing and newly enforced abortion restrictions. Whether managing a patient with an undesired pregnancy, severe medical comorbidities, unexpected pregnancy complications such as preterm premature rupture of membranes, or bleeding, or substantial fetal anomalies, ObGyn residents cannot gain the experience of providing the full scope of reproductive health care without the ability to offer all possible management options. While some enacted abortion restrictions have exceptions for the health of or life-saving measures for the mother, there is no standard guidance for timing of interventions, leaving providers confused and in fear of legal retribution. At a time when trainees should be learning to provide patient-centered, evidence-based care, they are instead paralyzed by the legal or professional consequences they may face for offering their best medical judgements.

Furthermore, the lack of exposure to dilation and evacuation procedures for residents in restricted practice areas will undoubtably decrease their confidence in managing acute complications, which is one of the critical facets of residency training. In a surgical field where repetition is crucial for technical competence, highlighted by ACGME minimum case requirements, the decreased volume of abortion procedures is a disadvantage for trainees and a disservice for patients. While anti-choice promoters may argue that involvement in surgical management of early pregnancy loss should suffice for ObGyn training in family planning, this piecemeal approach will leave gaps in technical skills.

The fear of legal ramifications, moral injury, and inadequate surgical training may lead to the siphoning of talented trainees to areas in the country with fewer restrictions.³Dobbs already has demonstrated how limiting abortion access will deepen inequities in reproductive health care service delivery. Approximately 55% of ObGyn trainees and nearly two-thirds of maternal-fetal medicine graduates join the workforce in the state where they received their training.⁴ Medical students will seek opportunities for high-quality ObGyn training in areas that will help them to be well-prepared, competent physicians—and more often than not, stay in the area or region that they trained in. This will lead to provider shortages in areas where access to reproductive health care and subspecialist providers already is limited, further exacerbating existing health disparities.

During this recruitment season, trainees and residency programs alike will need to reckon with how the ramifications of Dobbs will alter both the immediate and long-term training in comprehensive reproductive health care for the ObGyn workforce. ObGyn trainees have taken a stand in response to the Dobbs decision, and nearly 750 current residents signed onto the statement below as a commitment to high-quality training and patient-centered care. Clinical experience in performing abortions is essential to the provision of comprehensive evidence-based reproductive health care, and access to these procedures is as important for physicians-in-training as it is for patients.

Actions to take to ensure high-quality abortion training in ObGyn residencies include the following:

• Connect with and stay involved with organizations such as the American College of Obstetricians and Gynecologists (ACOG), Physicians for Reproductive Health (PRH), and Medical Students for Choice (MSFC) for initiatives, toolkits, and resources for training at your institutions.
• Seek specific abortion training opportunities through the Leadership Training Academy (offered through PRH) or the Abortion Training Institute (offered through MSFC).
• Ensure that your residency program meets the ACGME criteria of providing opportunities for clinical experiences for abortion care and work with program leadership at a program, state, or regional level to enforce these competencies.
• Reach out to your local American Civil Liberties Union or other local reproductive legal rights organizations if you want to be involved with advocacy around abortion access and training but have concerns about legal protections.
• Have a voice at the table for empowering training opportunities by seeking leadership positions through ACOG, ACGME, Council on Resident Education in Obstetrics and Gynecology and the Association of Professors of Gynecology and Obstetrics, American Medical Association, Student National Medical Association, and subspecialty organizations.
• Vote in every election and promote voting registration and access to your patients, colleagues, and communities. ●

Continue to: The implications of the Dobbs v Jackson Women’s Health Organization decision on the health care and wellbeing of our patients...

Photo: Shutterstock

Six months after the Supreme Court decision that overturned the constitutional right to abortion, trainees across the United States are asking a critical question in the current resident recruitment season: How will the restrictions on abortion access affect my training as an obstetrician-gynecologist, and will they impact my ability to be the kind of provider I want to be in the future?

Among the myriad of downstream effects to patient care, the Dobbs decision will indisputably impact the scope of residency training for those that provide reproductive health services. Almost half of ObGyn residents train in states that have abortion restrictions in place.¹ New educational milestones for abortion training, which are a requirement by the Accreditation Council for Graduate Medical Education (ACGME), were proposed quickly after Dobbs, guiding programs to offer opportunities for training in nonrestricted areas or the “combination of didactic activities, including simulation” to meet the training requirement in abortion care.²

Like many providers, residents already are grappling with precarious and risky circumstances, balancing patient safety and patient-driven care amidst pre-existing and newly enforced abortion restrictions. Whether managing a patient with an undesired pregnancy, severe medical comorbidities, unexpected pregnancy complications such as preterm premature rupture of membranes, or bleeding, or substantial fetal anomalies, ObGyn residents cannot gain the experience of providing the full scope of reproductive health care without the ability to offer all possible management options. While some enacted abortion restrictions have exceptions for the health of or life-saving measures for the mother, there is no standard guidance for timing of interventions, leaving providers confused and in fear of legal retribution. At a time when trainees should be learning to provide patient-centered, evidence-based care, they are instead paralyzed by the legal or professional consequences they may face for offering their best medical judgements.

Furthermore, the lack of exposure to dilation and evacuation procedures for residents in restricted practice areas will undoubtably decrease their confidence in managing acute complications, which is one of the critical facets of residency training. In a surgical field where repetition is crucial for technical competence, highlighted by ACGME minimum case requirements, the decreased volume of abortion procedures is a disadvantage for trainees and a disservice for patients. While anti-choice promoters may argue that involvement in surgical management of early pregnancy loss should suffice for ObGyn training in family planning, this piecemeal approach will leave gaps in technical skills.

The fear of legal ramifications, moral injury, and inadequate surgical training may lead to the siphoning of talented trainees to areas in the country with fewer restrictions.³Dobbs already has demonstrated how limiting abortion access will deepen inequities in reproductive health care service delivery. Approximately 55% of ObGyn trainees and nearly two-thirds of maternal-fetal medicine graduates join the workforce in the state where they received their training.⁴ Medical students will seek opportunities for high-quality ObGyn training in areas that will help them to be well-prepared, competent physicians—and more often than not, stay in the area or region that they trained in. This will lead to provider shortages in areas where access to reproductive health care and subspecialist providers already is limited, further exacerbating existing health disparities.

During this recruitment season, trainees and residency programs alike will need to reckon with how the ramifications of Dobbs will alter both the immediate and long-term training in comprehensive reproductive health care for the ObGyn workforce. ObGyn trainees have taken a stand in response to the Dobbs decision, and nearly 750 current residents signed onto the statement below as a commitment to high-quality training and patient-centered care. Clinical experience in performing abortions is essential to the provision of comprehensive evidence-based reproductive health care, and access to these procedures is as important for physicians-in-training as it is for patients.

Actions to take to ensure high-quality abortion training in ObGyn residencies include the following:

• Connect with and stay involved with organizations such as the American College of Obstetricians and Gynecologists (ACOG), Physicians for Reproductive Health (PRH), and Medical Students for Choice (MSFC) for initiatives, toolkits, and resources for training at your institutions.
• Seek specific abortion training opportunities through the Leadership Training Academy (offered through PRH) or the Abortion Training Institute (offered through MSFC).
• Ensure that your residency program meets the ACGME criteria of providing opportunities for clinical experiences for abortion care and work with program leadership at a program, state, or regional level to enforce these competencies.
• Reach out to your local American Civil Liberties Union or other local reproductive legal rights organizations if you want to be involved with advocacy around abortion access and training but have concerns about legal protections.
• Have a voice at the table for empowering training opportunities by seeking leadership positions through ACOG, ACGME, Council on Resident Education in Obstetrics and Gynecology and the Association of Professors of Gynecology and Obstetrics, American Medical Association, Student National Medical Association, and subspecialty organizations.
• Vote in every election and promote voting registration and access to your patients, colleagues, and communities. ●

Continue to: The implications of the Dobbs v Jackson Women’s Health Organization decision on the health care and wellbeing of our patients...

In the musical Hamilton, there is a line from the song “The Election of 1800” in which, after a tumultuous time, Thomas Jefferson pleads for a sense of normalcy with, “Can we get back to politics?”

Trying to get back to “normal,” whatever that is, characterized the year 2022. Peeking out from under the constant shadow of the COVID-19 pandemic (not really gone, definitely not forgotten) were some blockbuster obstetrical headlines, including those on the CHAP (Chronic Hypertension and Pregnancy) trial and the impact of the Dobbs v Jackson Supreme Court decision. As these have been extensively covered in both OBG Management and other publications, in this Update we simply ask, “Can we get back to obstetrics?” as we focus on some straightforward patient care guidelines.

Thus, we offer updated information on the use of progesterone for preterm birth prevention, management of pregnancies that result from in vitro fertilization (IVF), and headache management in pregnant and postpartum patients.

Society guidance and FDA  advisement on the use of  progesterone for the prevention  of spontaneous preterm birth

American College of Obstetricians and Gynecologists’ Committee on Practice Bulletins–Obstetrics. Prediction and prevention of spontaneous preterm birth. ACOG practice bulletin no. 234. Obstet Gynecol. 2021;138:e65-e90.

EPPPIC Group. Evaluating Progestogens for Preventing Preterm birth International Collaborative (EPPPIC): meta-analysis of individual participant data from randomised controlled trials. Lancet. 2021;397:1183-1194.

This is not déjà vu! Progesterone and spontaneous preterm birth (sPTB) is a hot topic again. If you wonder what to tell your patients, you are not alone. Preterm birth (PTB) continues to pose a challenge in obstetrics, with a most recently reported overall rate of 10.49%¹ in the United States—a 4% increase from 2019. Preterm birth accounts for approximately 75% of perinatal mortality and more than half of neonatal morbidity.²

What has not changed

A recent practice bulletin from the American College of Obstetricians and Gynecologists (ACOG) notes that some risk factors and screening assessments for PTB remain unchanged, including²:

• A history of PTB increases the risk for subsequent PTB. Risk increases with the number of prior preterm deliveries.
• A short cervix (<25 mm between 16 and  24 weeks’ gestation) is a risk factor for sPTB.
• The cervix should be visualized during the anatomy ultrasound exam (18 0/7 to 22 6/7 weeks’ gestation) in all pregnant patients regardless of prior birth history. If the cervix length (CL) appears shortened on transabdominal imaging, transvaginal (TV) imaging should be performed.
• Patients with a current singleton pregnancy and history of sPTB should have serial TV cervical measurements between 16 0/7 and 24 0/7 weeks’ gestation.²

EPPPIC changes and key takeaway points

In a meta-analysis of data from 31 randomized controlled trials, the EPPPIC (Evaluating Progestogens for Preventing Preterm birth International Collaborative) investigators compared vaginal progesterone, intramuscular 17-hydroxyprogesterone caproate  (17-OHPC), or oral progesterone with control or with each other in women at risk for PTB.³ Outcomes included PTB and the associated adverse neonatal and maternal outcomes.

The EPPPIC study’s main findings were:

• Singleton pregnancies at high risk for PTB due to prior sPTB or short cervix who received 17-OHPC or vaginal progesterone were less likely to deliver before  34 weeks’ gestation compared with those who received no treatment.
• There is a benefit to both 17-OHPC and vaginal progesterone in reducing the risk of PTB, with no clear evidence to support one intervention’s effectiveness over the other.
• There is benefit to either 17-OHPC or vaginal progesterone for CL less than 25 mm. The shorter the CL, the greater the absolute risk reduction on PTB.
• In multifetal pregnancies, use of 17-OHPC, when compared with placebo, was shown to increase the risk of preterm premature rupture of membranes. Neither 17-OHPC nor vaginal progesterone was found to reduce the risk of sPTB in multifetal pregnancies.³

What continues to change

While the March 30, 2021, statement from the Society for Maternal-Fetal Medicine (SMFM), “Response to EPPPIC and consideration for the use of progestogens for the prevention of preterm birth” (https://www .smfm.org/publications/383-smfm-stat ement-response-to-epppic-and-consider ations-of-the-use-of-progestogens-for-the -prevention-of-preterm-birth), stands, ACOG has withdrawn its accompanying Practice Advisory on guidance for integrating the EPPPIC findings.

In August 2022, the US Food and Drug Administration (FDA) granted a hearing on the Center for Drug Evaluation and Research’s proposal to withdraw approval for Makena (hydroxyprogesterone caproate injection, 250 mg/mL, once weekly) on the basis that available evidence does not demonstrate that it is effective for its approved indication to reduce the risk of PTB in women with a singleton pregnancy with a history of singleton sPTB.⁴

The key takeaway points from the FDA hearing (October 17–19, 2022) were:

• A better designed randomized controlled confirmatory trial is needed in the most at-risk patients to determine if Makena is effective for its approved indication.
• Makena and its approved generic equivalents remain on the market until the FDA makes its final decision regarding approval.⁴

Continue to: Managing pregnancies that result from IVF...

Society for Maternal-Fetal Medicine (SMFM); Ghidini A, Gandhi M, McCoy J, et al; Publications Committee. Society for Maternal-Fetal Medicine consult series #60: management of pregnancies resulting from in vitro fertilization. Am J Obstet Gynecol. 2022;226:B2-B12.

Assisted reproductive technology contributes to 1.6% of all infant births, and although most pregnancies are uncomplicated, some specific risks alter management.^5–7 For example, IVF is associated with increased rates of prematurity and its complications, fetal growth restriction, low birth weight, congenital anomalies, genetic abnormalities, and placental abnormalities. In addition, there is doubling of the risk of morbidities to the pregnant IVF patient, including but not limited to hypertensive disorders and diabetes. These complications are thought to be related to both the process of IVF itself as well as to conditions that contribute to subfertility and infertility in the first place.

Genetic screening and diagnostic testing options

IVF pregnancies have a documented increase in chromosomal abnormalities compared with spontaneously conceived pregnancies due to the following factors:

• karyotypic abnormalities in couples with infertility
• microdeletions on the Y chromosome in patients with oligospermia or azoospermia
• de novo chromosomal abnormalities in IVF pregnancies that utilize intracytoplasmic sperm injection (ICSI)
• fragile X mutations in patients with reduced ovarian reserve
• imprinting disorders in patients with fertility issues.

A common misconception is that preimplantation genetic testing renders prenatal genetic screening or testing unnecessary. However, preimplantation testing can be anywhere from 43% to 84% concordant with prenatal diagnostic testing due to biologic and technical factors. Therefore, all pregnancies should be offered the same options of aneuploidy screening as well as diagnostic testing. Pretest counseling should include an increased risk in IVF pregnancies of false-positives for the first-trimester screen and “no-call” results for cell-free fetal DNA. Additionally, diagnostic testing is recommended specifically in cases where mosaic embryos are transferred when euploid embryos are not available.

Counseling on fetal reduction for multifetal pregnancies

The risks of multifetal pregnancies (particularly higher order multiples) are significant and well documented for both the patient and the fetuses. It is therefore recommended that the option of multifetal pregnancy reduction be discussed, including the risks and benefits of reduction versus pregnancy continuation, timing, procedural considerations, and genetic testing options.^5,8

Detailed anatomic survey and fetal echocardiogram are indicated

Fetal anomalies, including congenital cardiac defects, occur at a higher rate in IVF pregnancies compared with spontaneously conceived pregnancies (475/10,000 live births vs 317/10,000 live births). Placental anomalies (such as placenta previa, vasa previa, and velamentous cord insertion) are also more common in this population. A detailed anatomic survey is therefore recommended for all IVF pregnancies and it is suggested that a fetal echocardiogram is offered these patients as well.

Pregnancy management and delivery considerations

Despite an increased risk of preterm birth, preeclampsia, and fetal growth restriction in IVF pregnancies (odds ratios range, 1.4–2), serial cervical lengths, serial growth ultrasound exams, and low-dose aspirin are not recommended for the sole indication of IVF. Due to lack of data on the utility of serial exams, a single screening cervical length at the time of anatomic survey and a third-trimester growth assessment are recommended. For aspirin, IVF qualifies as a “moderate” risk factor for preeclampsia; it is therefore recommended if another moderate risk factor is present (for example, nulliparity, obesity, or family history of preeclampsia).⁹

There is a 2- to 3-fold increased risk of stillbirth in IVF pregnancies; therefore, antenatal surveillance in the third trimester is recommended (weekly starting at 36 weeks for the sole indication of IVF).¹⁰ As no specific studies have evaluated the timing of delivery in IVF pregnancies, delivery recommendations include the option of 39-week delivery with shared decision-making with the patient.

Continue to: Evaluating and treating headaches in pregnancy and postpartum...

Evaluating and treating headaches in pregnancy and postpartum

American College of Obstetricians and Gynecologists. Clinical practice guideline no. 3: headaches in pregnancy and postpartum. Obstet Gynecol. 2022;139:944-972.

For obstetricians, headaches are a common and often frustrating condition to treat, as many of the available diagnostic tools and medications are either not recommended or have no data on use in pregnancy and lactation. Additionally, a headache is not always just a headache but could be a sign of a time-sensitive serious complication. An updated guideline from the American College of Obstetricians and Gynecologists approaches the topic of headaches in a stepwise algorithm that promotes efficiency and efficacy in diagnosis  and treatment.¹¹

Types of headaches

The primary headache types—migraine, cluster, and tension—are distinguished from each other by patient characteristics, quality, duration, location, and related symptoms. Reassuringly, headache frequency decreases by 30% to 80% during pregnancy, which allows for the option to decrease, change, or stop current medications, ideally prior to pregnancy. Prevention via use of calcium channel blockers, antihistamines, or β-blockers is recommended, as requiring acute treatments more than 2 days per week increases the risk of medication overuse headaches.

Treating acute headache

For patients who present with an acute headache consistent with their usual type, treatment starts with known medications that are compatible with pregnancy and proceeds in a stepwise fashion:

1. Acetaminophen 1,000 mg orally with or without caffeine 130 mg orally (maximum dose, acetaminophen < 3.25–4 g per day, caffeine 200 mg per day)

2. Metoclopramide 10 mg intravenously with or without diphenhydramine 25 mg intravenously (for nausea and to counteract restlessness and offer sedation)

3. If headache continues after steps 1 and 2, consider the following secondary treatment options: magnesium sulfate 1–2 g intravenously, sumatriptan 6 mg subcutaneously or 20-mg nasal spray, ibuprofen 600 mg orally once, or ketorolac 30 mg intravenously once (second trimester only)

4. If continued treatment and/or hospitalization is required after step 3, steroids can be used: prednisone 20 mg 4 times a day for 2 days or methylprednisolone 4-mg dose pack over 6 days

5. Do not use butalbital, opioids, or ergotamines due to lack of efficacy in providing additional pain relief, potential for addiction, risk of medication overuse headaches, and association with fetal/ pregnancy abnormalities.

Consider secondary headache

An acute headache discordant from the patient’s usual type or with concerning symptoms (“red flags”) requires consideration of secondary headaches as well as a comprehensive symptom evaluation, imaging, and consultation as needed. While secondary headaches postpartum are most likely musculoskeletal in nature, the following symptoms need to be evaluated immediately:

• rapid onset/change from baseline
• “thunderclap” nature
• hypertension
• fever
• focal neurologic deficits (blurry vision or blindness, confusion, seizures)
• altered consciousness
• laboratory abnormalities.

The differential diagnosis includes preeclampsia, reversible cerebral vasoconstriction syndrome (RCVS), posterior reversible encephalopathy syndrome (PRES), infection, cerebral venous sinus thrombosis (CVST), post–dural puncture (PDP) headache, idiopathic intracranial hypertension (IIH), and less likely, carotid dissection, subarachnoid hemorrhage, intracranial hemorrhage, pituitary apoplexy, or neoplasm.

Treatment. Individualized treatment depends on the diagnosis. Preeclampsia with severe features is treated with antihypertensive medication, magnesium sulfate, and delivery planning. PDP headache is treated with epidural blood patch, sphenopalatine block, or occipital block with an anesthesiology consultation. If preeclampsia and PDP are ruled out, or if there are more concerning neurologic features, imaging is essential, as 25% of pregnant patients with acute headaches will have a secondary etiology. Magnetic resonance imaging without contrast is preferred due to concerns about gadolinium crossing the placenta and the lack of data on long-term accumulation in fetal  tissues. Once diagnosed on imaging, PRES and RCVS are treated with antihypertensives and delivery. CVST is treated with anticoagulation and a thrombophilia workup. IIH may be treated with acetazolamide after 20 weeks or serial lumbar punctures. Intracranial vascular abnormalities may be treated with endoscopic resection and steroids. ●

In the musical Hamilton, there is a line from the song “The Election of 1800” in which, after a tumultuous time, Thomas Jefferson pleads for a sense of normalcy with, “Can we get back to politics?”

Trying to get back to “normal,” whatever that is, characterized the year 2022. Peeking out from under the constant shadow of the COVID-19 pandemic (not really gone, definitely not forgotten) were some blockbuster obstetrical headlines, including those on the CHAP (Chronic Hypertension and Pregnancy) trial and the impact of the Dobbs v Jackson Supreme Court decision. As these have been extensively covered in both OBG Management and other publications, in this Update we simply ask, “Can we get back to obstetrics?” as we focus on some straightforward patient care guidelines.

Thus, we offer updated information on the use of progesterone for preterm birth prevention, management of pregnancies that result from in vitro fertilization (IVF), and headache management in pregnant and postpartum patients.

Society guidance and FDA  advisement on the use of  progesterone for the prevention  of spontaneous preterm birth

American College of Obstetricians and Gynecologists’ Committee on Practice Bulletins–Obstetrics. Prediction and prevention of spontaneous preterm birth. ACOG practice bulletin no. 234. Obstet Gynecol. 2021;138:e65-e90.

EPPPIC Group. Evaluating Progestogens for Preventing Preterm birth International Collaborative (EPPPIC): meta-analysis of individual participant data from randomised controlled trials. Lancet. 2021;397:1183-1194.

This is not déjà vu! Progesterone and spontaneous preterm birth (sPTB) is a hot topic again. If you wonder what to tell your patients, you are not alone. Preterm birth (PTB) continues to pose a challenge in obstetrics, with a most recently reported overall rate of 10.49%¹ in the United States—a 4% increase from 2019. Preterm birth accounts for approximately 75% of perinatal mortality and more than half of neonatal morbidity.²

What has not changed

A recent practice bulletin from the American College of Obstetricians and Gynecologists (ACOG) notes that some risk factors and screening assessments for PTB remain unchanged, including²:

• A history of PTB increases the risk for subsequent PTB. Risk increases with the number of prior preterm deliveries.
• A short cervix (<25 mm between 16 and  24 weeks’ gestation) is a risk factor for sPTB.
• The cervix should be visualized during the anatomy ultrasound exam (18 0/7 to 22 6/7 weeks’ gestation) in all pregnant patients regardless of prior birth history. If the cervix length (CL) appears shortened on transabdominal imaging, transvaginal (TV) imaging should be performed.
• Patients with a current singleton pregnancy and history of sPTB should have serial TV cervical measurements between 16 0/7 and 24 0/7 weeks’ gestation.²

EPPPIC changes and key takeaway points

In a meta-analysis of data from 31 randomized controlled trials, the EPPPIC (Evaluating Progestogens for Preventing Preterm birth International Collaborative) investigators compared vaginal progesterone, intramuscular 17-hydroxyprogesterone caproate  (17-OHPC), or oral progesterone with control or with each other in women at risk for PTB.³ Outcomes included PTB and the associated adverse neonatal and maternal outcomes.

The EPPPIC study’s main findings were:

• Singleton pregnancies at high risk for PTB due to prior sPTB or short cervix who received 17-OHPC or vaginal progesterone were less likely to deliver before  34 weeks’ gestation compared with those who received no treatment.
• There is a benefit to both 17-OHPC and vaginal progesterone in reducing the risk of PTB, with no clear evidence to support one intervention’s effectiveness over the other.
• There is benefit to either 17-OHPC or vaginal progesterone for CL less than 25 mm. The shorter the CL, the greater the absolute risk reduction on PTB.
• In multifetal pregnancies, use of 17-OHPC, when compared with placebo, was shown to increase the risk of preterm premature rupture of membranes. Neither 17-OHPC nor vaginal progesterone was found to reduce the risk of sPTB in multifetal pregnancies.³

What continues to change

While the March 30, 2021, statement from the Society for Maternal-Fetal Medicine (SMFM), “Response to EPPPIC and consideration for the use of progestogens for the prevention of preterm birth” (https://www .smfm.org/publications/383-smfm-stat ement-response-to-epppic-and-consider ations-of-the-use-of-progestogens-for-the -prevention-of-preterm-birth), stands, ACOG has withdrawn its accompanying Practice Advisory on guidance for integrating the EPPPIC findings.

In August 2022, the US Food and Drug Administration (FDA) granted a hearing on the Center for Drug Evaluation and Research’s proposal to withdraw approval for Makena (hydroxyprogesterone caproate injection, 250 mg/mL, once weekly) on the basis that available evidence does not demonstrate that it is effective for its approved indication to reduce the risk of PTB in women with a singleton pregnancy with a history of singleton sPTB.⁴

The key takeaway points from the FDA hearing (October 17–19, 2022) were:

• A better designed randomized controlled confirmatory trial is needed in the most at-risk patients to determine if Makena is effective for its approved indication.
• Makena and its approved generic equivalents remain on the market until the FDA makes its final decision regarding approval.⁴

Continue to: Managing pregnancies that result from IVF...

Society for Maternal-Fetal Medicine (SMFM); Ghidini A, Gandhi M, McCoy J, et al; Publications Committee. Society for Maternal-Fetal Medicine consult series #60: management of pregnancies resulting from in vitro fertilization. Am J Obstet Gynecol. 2022;226:B2-B12.

Assisted reproductive technology contributes to 1.6% of all infant births, and although most pregnancies are uncomplicated, some specific risks alter management.^5–7 For example, IVF is associated with increased rates of prematurity and its complications, fetal growth restriction, low birth weight, congenital anomalies, genetic abnormalities, and placental abnormalities. In addition, there is doubling of the risk of morbidities to the pregnant IVF patient, including but not limited to hypertensive disorders and diabetes. These complications are thought to be related to both the process of IVF itself as well as to conditions that contribute to subfertility and infertility in the first place.

Genetic screening and diagnostic testing options

IVF pregnancies have a documented increase in chromosomal abnormalities compared with spontaneously conceived pregnancies due to the following factors:

• karyotypic abnormalities in couples with infertility
• microdeletions on the Y chromosome in patients with oligospermia or azoospermia
• de novo chromosomal abnormalities in IVF pregnancies that utilize intracytoplasmic sperm injection (ICSI)
• fragile X mutations in patients with reduced ovarian reserve
• imprinting disorders in patients with fertility issues.

A common misconception is that preimplantation genetic testing renders prenatal genetic screening or testing unnecessary. However, preimplantation testing can be anywhere from 43% to 84% concordant with prenatal diagnostic testing due to biologic and technical factors. Therefore, all pregnancies should be offered the same options of aneuploidy screening as well as diagnostic testing. Pretest counseling should include an increased risk in IVF pregnancies of false-positives for the first-trimester screen and “no-call” results for cell-free fetal DNA. Additionally, diagnostic testing is recommended specifically in cases where mosaic embryos are transferred when euploid embryos are not available.

Counseling on fetal reduction for multifetal pregnancies

The risks of multifetal pregnancies (particularly higher order multiples) are significant and well documented for both the patient and the fetuses. It is therefore recommended that the option of multifetal pregnancy reduction be discussed, including the risks and benefits of reduction versus pregnancy continuation, timing, procedural considerations, and genetic testing options.^5,8

Detailed anatomic survey and fetal echocardiogram are indicated

Fetal anomalies, including congenital cardiac defects, occur at a higher rate in IVF pregnancies compared with spontaneously conceived pregnancies (475/10,000 live births vs 317/10,000 live births). Placental anomalies (such as placenta previa, vasa previa, and velamentous cord insertion) are also more common in this population. A detailed anatomic survey is therefore recommended for all IVF pregnancies and it is suggested that a fetal echocardiogram is offered these patients as well.

Pregnancy management and delivery considerations

Despite an increased risk of preterm birth, preeclampsia, and fetal growth restriction in IVF pregnancies (odds ratios range, 1.4–2), serial cervical lengths, serial growth ultrasound exams, and low-dose aspirin are not recommended for the sole indication of IVF. Due to lack of data on the utility of serial exams, a single screening cervical length at the time of anatomic survey and a third-trimester growth assessment are recommended. For aspirin, IVF qualifies as a “moderate” risk factor for preeclampsia; it is therefore recommended if another moderate risk factor is present (for example, nulliparity, obesity, or family history of preeclampsia).⁹

There is a 2- to 3-fold increased risk of stillbirth in IVF pregnancies; therefore, antenatal surveillance in the third trimester is recommended (weekly starting at 36 weeks for the sole indication of IVF).¹⁰ As no specific studies have evaluated the timing of delivery in IVF pregnancies, delivery recommendations include the option of 39-week delivery with shared decision-making with the patient.

Continue to: Evaluating and treating headaches in pregnancy and postpartum...

Evaluating and treating headaches in pregnancy and postpartum

American College of Obstetricians and Gynecologists. Clinical practice guideline no. 3: headaches in pregnancy and postpartum. Obstet Gynecol. 2022;139:944-972.

For obstetricians, headaches are a common and often frustrating condition to treat, as many of the available diagnostic tools and medications are either not recommended or have no data on use in pregnancy and lactation. Additionally, a headache is not always just a headache but could be a sign of a time-sensitive serious complication. An updated guideline from the American College of Obstetricians and Gynecologists approaches the topic of headaches in a stepwise algorithm that promotes efficiency and efficacy in diagnosis  and treatment.¹¹

Types of headaches

The primary headache types—migraine, cluster, and tension—are distinguished from each other by patient characteristics, quality, duration, location, and related symptoms. Reassuringly, headache frequency decreases by 30% to 80% during pregnancy, which allows for the option to decrease, change, or stop current medications, ideally prior to pregnancy. Prevention via use of calcium channel blockers, antihistamines, or β-blockers is recommended, as requiring acute treatments more than 2 days per week increases the risk of medication overuse headaches.

Treating acute headache

For patients who present with an acute headache consistent with their usual type, treatment starts with known medications that are compatible with pregnancy and proceeds in a stepwise fashion:

1. Acetaminophen 1,000 mg orally with or without caffeine 130 mg orally (maximum dose, acetaminophen < 3.25–4 g per day, caffeine 200 mg per day)

2. Metoclopramide 10 mg intravenously with or without diphenhydramine 25 mg intravenously (for nausea and to counteract restlessness and offer sedation)

3. If headache continues after steps 1 and 2, consider the following secondary treatment options: magnesium sulfate 1–2 g intravenously, sumatriptan 6 mg subcutaneously or 20-mg nasal spray, ibuprofen 600 mg orally once, or ketorolac 30 mg intravenously once (second trimester only)

4. If continued treatment and/or hospitalization is required after step 3, steroids can be used: prednisone 20 mg 4 times a day for 2 days or methylprednisolone 4-mg dose pack over 6 days

5. Do not use butalbital, opioids, or ergotamines due to lack of efficacy in providing additional pain relief, potential for addiction, risk of medication overuse headaches, and association with fetal/ pregnancy abnormalities.

Consider secondary headache

An acute headache discordant from the patient’s usual type or with concerning symptoms (“red flags”) requires consideration of secondary headaches as well as a comprehensive symptom evaluation, imaging, and consultation as needed. While secondary headaches postpartum are most likely musculoskeletal in nature, the following symptoms need to be evaluated immediately:

• rapid onset/change from baseline
• “thunderclap” nature
• hypertension
• fever
• focal neurologic deficits (blurry vision or blindness, confusion, seizures)
• altered consciousness
• laboratory abnormalities.

The differential diagnosis includes preeclampsia, reversible cerebral vasoconstriction syndrome (RCVS), posterior reversible encephalopathy syndrome (PRES), infection, cerebral venous sinus thrombosis (CVST), post–dural puncture (PDP) headache, idiopathic intracranial hypertension (IIH), and less likely, carotid dissection, subarachnoid hemorrhage, intracranial hemorrhage, pituitary apoplexy, or neoplasm.

Treatment. Individualized treatment depends on the diagnosis. Preeclampsia with severe features is treated with antihypertensive medication, magnesium sulfate, and delivery planning. PDP headache is treated with epidural blood patch, sphenopalatine block, or occipital block with an anesthesiology consultation. If preeclampsia and PDP are ruled out, or if there are more concerning neurologic features, imaging is essential, as 25% of pregnant patients with acute headaches will have a secondary etiology. Magnetic resonance imaging without contrast is preferred due to concerns about gadolinium crossing the placenta and the lack of data on long-term accumulation in fetal  tissues. Once diagnosed on imaging, PRES and RCVS are treated with antihypertensives and delivery. CVST is treated with anticoagulation and a thrombophilia workup. IIH may be treated with acetazolamide after 20 weeks or serial lumbar punctures. Intracranial vascular abnormalities may be treated with endoscopic resection and steroids. ●

In the musical Hamilton, there is a line from the song “The Election of 1800” in which, after a tumultuous time, Thomas Jefferson pleads for a sense of normalcy with, “Can we get back to politics?”

Trying to get back to “normal,” whatever that is, characterized the year 2022. Peeking out from under the constant shadow of the COVID-19 pandemic (not really gone, definitely not forgotten) were some blockbuster obstetrical headlines, including those on the CHAP (Chronic Hypertension and Pregnancy) trial and the impact of the Dobbs v Jackson Supreme Court decision. As these have been extensively covered in both OBG Management and other publications, in this Update we simply ask, “Can we get back to obstetrics?” as we focus on some straightforward patient care guidelines.

Thus, we offer updated information on the use of progesterone for preterm birth prevention, management of pregnancies that result from in vitro fertilization (IVF), and headache management in pregnant and postpartum patients.

Society guidance and FDA  advisement on the use of  progesterone for the prevention  of spontaneous preterm birth

American College of Obstetricians and Gynecologists’ Committee on Practice Bulletins–Obstetrics. Prediction and prevention of spontaneous preterm birth. ACOG practice bulletin no. 234. Obstet Gynecol. 2021;138:e65-e90.

EPPPIC Group. Evaluating Progestogens for Preventing Preterm birth International Collaborative (EPPPIC): meta-analysis of individual participant data from randomised controlled trials. Lancet. 2021;397:1183-1194.

This is not déjà vu! Progesterone and spontaneous preterm birth (sPTB) is a hot topic again. If you wonder what to tell your patients, you are not alone. Preterm birth (PTB) continues to pose a challenge in obstetrics, with a most recently reported overall rate of 10.49%¹ in the United States—a 4% increase from 2019. Preterm birth accounts for approximately 75% of perinatal mortality and more than half of neonatal morbidity.²

What has not changed

A recent practice bulletin from the American College of Obstetricians and Gynecologists (ACOG) notes that some risk factors and screening assessments for PTB remain unchanged, including²:

• A history of PTB increases the risk for subsequent PTB. Risk increases with the number of prior preterm deliveries.
• A short cervix (<25 mm between 16 and  24 weeks’ gestation) is a risk factor for sPTB.
• The cervix should be visualized during the anatomy ultrasound exam (18 0/7 to 22 6/7 weeks’ gestation) in all pregnant patients regardless of prior birth history. If the cervix length (CL) appears shortened on transabdominal imaging, transvaginal (TV) imaging should be performed.
• Patients with a current singleton pregnancy and history of sPTB should have serial TV cervical measurements between 16 0/7 and 24 0/7 weeks’ gestation.²

EPPPIC changes and key takeaway points

In a meta-analysis of data from 31 randomized controlled trials, the EPPPIC (Evaluating Progestogens for Preventing Preterm birth International Collaborative) investigators compared vaginal progesterone, intramuscular 17-hydroxyprogesterone caproate  (17-OHPC), or oral progesterone with control or with each other in women at risk for PTB.³ Outcomes included PTB and the associated adverse neonatal and maternal outcomes.

The EPPPIC study’s main findings were:

• Singleton pregnancies at high risk for PTB due to prior sPTB or short cervix who received 17-OHPC or vaginal progesterone were less likely to deliver before  34 weeks’ gestation compared with those who received no treatment.
• There is a benefit to both 17-OHPC and vaginal progesterone in reducing the risk of PTB, with no clear evidence to support one intervention’s effectiveness over the other.
• There is benefit to either 17-OHPC or vaginal progesterone for CL less than 25 mm. The shorter the CL, the greater the absolute risk reduction on PTB.
• In multifetal pregnancies, use of 17-OHPC, when compared with placebo, was shown to increase the risk of preterm premature rupture of membranes. Neither 17-OHPC nor vaginal progesterone was found to reduce the risk of sPTB in multifetal pregnancies.³

What continues to change

While the March 30, 2021, statement from the Society for Maternal-Fetal Medicine (SMFM), “Response to EPPPIC and consideration for the use of progestogens for the prevention of preterm birth” (https://www .smfm.org/publications/383-smfm-stat ement-response-to-epppic-and-consider ations-of-the-use-of-progestogens-for-the -prevention-of-preterm-birth), stands, ACOG has withdrawn its accompanying Practice Advisory on guidance for integrating the EPPPIC findings.

In August 2022, the US Food and Drug Administration (FDA) granted a hearing on the Center for Drug Evaluation and Research’s proposal to withdraw approval for Makena (hydroxyprogesterone caproate injection, 250 mg/mL, once weekly) on the basis that available evidence does not demonstrate that it is effective for its approved indication to reduce the risk of PTB in women with a singleton pregnancy with a history of singleton sPTB.⁴

The key takeaway points from the FDA hearing (October 17–19, 2022) were:

• A better designed randomized controlled confirmatory trial is needed in the most at-risk patients to determine if Makena is effective for its approved indication.
• Makena and its approved generic equivalents remain on the market until the FDA makes its final decision regarding approval.⁴

Continue to: Managing pregnancies that result from IVF...

Society for Maternal-Fetal Medicine (SMFM); Ghidini A, Gandhi M, McCoy J, et al; Publications Committee. Society for Maternal-Fetal Medicine consult series #60: management of pregnancies resulting from in vitro fertilization. Am J Obstet Gynecol. 2022;226:B2-B12.

Assisted reproductive technology contributes to 1.6% of all infant births, and although most pregnancies are uncomplicated, some specific risks alter management.^5–7 For example, IVF is associated with increased rates of prematurity and its complications, fetal growth restriction, low birth weight, congenital anomalies, genetic abnormalities, and placental abnormalities. In addition, there is doubling of the risk of morbidities to the pregnant IVF patient, including but not limited to hypertensive disorders and diabetes. These complications are thought to be related to both the process of IVF itself as well as to conditions that contribute to subfertility and infertility in the first place.

Genetic screening and diagnostic testing options

IVF pregnancies have a documented increase in chromosomal abnormalities compared with spontaneously conceived pregnancies due to the following factors:

• karyotypic abnormalities in couples with infertility
• microdeletions on the Y chromosome in patients with oligospermia or azoospermia
• de novo chromosomal abnormalities in IVF pregnancies that utilize intracytoplasmic sperm injection (ICSI)
• fragile X mutations in patients with reduced ovarian reserve
• imprinting disorders in patients with fertility issues.

A common misconception is that preimplantation genetic testing renders prenatal genetic screening or testing unnecessary. However, preimplantation testing can be anywhere from 43% to 84% concordant with prenatal diagnostic testing due to biologic and technical factors. Therefore, all pregnancies should be offered the same options of aneuploidy screening as well as diagnostic testing. Pretest counseling should include an increased risk in IVF pregnancies of false-positives for the first-trimester screen and “no-call” results for cell-free fetal DNA. Additionally, diagnostic testing is recommended specifically in cases where mosaic embryos are transferred when euploid embryos are not available.

Counseling on fetal reduction for multifetal pregnancies

The risks of multifetal pregnancies (particularly higher order multiples) are significant and well documented for both the patient and the fetuses. It is therefore recommended that the option of multifetal pregnancy reduction be discussed, including the risks and benefits of reduction versus pregnancy continuation, timing, procedural considerations, and genetic testing options.^5,8

Detailed anatomic survey and fetal echocardiogram are indicated

Fetal anomalies, including congenital cardiac defects, occur at a higher rate in IVF pregnancies compared with spontaneously conceived pregnancies (475/10,000 live births vs 317/10,000 live births). Placental anomalies (such as placenta previa, vasa previa, and velamentous cord insertion) are also more common in this population. A detailed anatomic survey is therefore recommended for all IVF pregnancies and it is suggested that a fetal echocardiogram is offered these patients as well.

Pregnancy management and delivery considerations

Despite an increased risk of preterm birth, preeclampsia, and fetal growth restriction in IVF pregnancies (odds ratios range, 1.4–2), serial cervical lengths, serial growth ultrasound exams, and low-dose aspirin are not recommended for the sole indication of IVF. Due to lack of data on the utility of serial exams, a single screening cervical length at the time of anatomic survey and a third-trimester growth assessment are recommended. For aspirin, IVF qualifies as a “moderate” risk factor for preeclampsia; it is therefore recommended if another moderate risk factor is present (for example, nulliparity, obesity, or family history of preeclampsia).⁹

There is a 2- to 3-fold increased risk of stillbirth in IVF pregnancies; therefore, antenatal surveillance in the third trimester is recommended (weekly starting at 36 weeks for the sole indication of IVF).¹⁰ As no specific studies have evaluated the timing of delivery in IVF pregnancies, delivery recommendations include the option of 39-week delivery with shared decision-making with the patient.

Continue to: Evaluating and treating headaches in pregnancy and postpartum...

Evaluating and treating headaches in pregnancy and postpartum

American College of Obstetricians and Gynecologists. Clinical practice guideline no. 3: headaches in pregnancy and postpartum. Obstet Gynecol. 2022;139:944-972.

For obstetricians, headaches are a common and often frustrating condition to treat, as many of the available diagnostic tools and medications are either not recommended or have no data on use in pregnancy and lactation. Additionally, a headache is not always just a headache but could be a sign of a time-sensitive serious complication. An updated guideline from the American College of Obstetricians and Gynecologists approaches the topic of headaches in a stepwise algorithm that promotes efficiency and efficacy in diagnosis  and treatment.¹¹

Types of headaches

The primary headache types—migraine, cluster, and tension—are distinguished from each other by patient characteristics, quality, duration, location, and related symptoms. Reassuringly, headache frequency decreases by 30% to 80% during pregnancy, which allows for the option to decrease, change, or stop current medications, ideally prior to pregnancy. Prevention via use of calcium channel blockers, antihistamines, or β-blockers is recommended, as requiring acute treatments more than 2 days per week increases the risk of medication overuse headaches.

Treating acute headache

For patients who present with an acute headache consistent with their usual type, treatment starts with known medications that are compatible with pregnancy and proceeds in a stepwise fashion:

1. Acetaminophen 1,000 mg orally with or without caffeine 130 mg orally (maximum dose, acetaminophen < 3.25–4 g per day, caffeine 200 mg per day)

2. Metoclopramide 10 mg intravenously with or without diphenhydramine 25 mg intravenously (for nausea and to counteract restlessness and offer sedation)

3. If headache continues after steps 1 and 2, consider the following secondary treatment options: magnesium sulfate 1–2 g intravenously, sumatriptan 6 mg subcutaneously or 20-mg nasal spray, ibuprofen 600 mg orally once, or ketorolac 30 mg intravenously once (second trimester only)

4. If continued treatment and/or hospitalization is required after step 3, steroids can be used: prednisone 20 mg 4 times a day for 2 days or methylprednisolone 4-mg dose pack over 6 days

5. Do not use butalbital, opioids, or ergotamines due to lack of efficacy in providing additional pain relief, potential for addiction, risk of medication overuse headaches, and association with fetal/ pregnancy abnormalities.

Consider secondary headache

An acute headache discordant from the patient’s usual type or with concerning symptoms (“red flags”) requires consideration of secondary headaches as well as a comprehensive symptom evaluation, imaging, and consultation as needed. While secondary headaches postpartum are most likely musculoskeletal in nature, the following symptoms need to be evaluated immediately:

• rapid onset/change from baseline
• “thunderclap” nature
• hypertension
• fever
• focal neurologic deficits (blurry vision or blindness, confusion, seizures)
• altered consciousness
• laboratory abnormalities.

The differential diagnosis includes preeclampsia, reversible cerebral vasoconstriction syndrome (RCVS), posterior reversible encephalopathy syndrome (PRES), infection, cerebral venous sinus thrombosis (CVST), post–dural puncture (PDP) headache, idiopathic intracranial hypertension (IIH), and less likely, carotid dissection, subarachnoid hemorrhage, intracranial hemorrhage, pituitary apoplexy, or neoplasm.

Treatment. Individualized treatment depends on the diagnosis. Preeclampsia with severe features is treated with antihypertensive medication, magnesium sulfate, and delivery planning. PDP headache is treated with epidural blood patch, sphenopalatine block, or occipital block with an anesthesiology consultation. If preeclampsia and PDP are ruled out, or if there are more concerning neurologic features, imaging is essential, as 25% of pregnant patients with acute headaches will have a secondary etiology. Magnetic resonance imaging without contrast is preferred due to concerns about gadolinium crossing the placenta and the lack of data on long-term accumulation in fetal  tissues. Once diagnosed on imaging, PRES and RCVS are treated with antihypertensives and delivery. CVST is treated with anticoagulation and a thrombophilia workup. IIH may be treated with acetazolamide after 20 weeks or serial lumbar punctures. Intracranial vascular abnormalities may be treated with endoscopic resection and steroids. ●

The approach to hysterectomy has been debated, with the need for individualization case by case stressed, and the expertise of the operating surgeon considered.

CASE Was surgeon experience a factor in case complications?

VM is a 46-year-old woman (G5 P4014) reporting persistent uterine bleeding that is refractory to medical therapy. The patient has uterine fibroids, 6 weeks in size on examination, with “mild” prolapse noted. Additional medical diagnoses included vulvitis, ovarian cyst in the past, cystic mastopathy, and prior evidence of pelvic adhesion, noted at the time of ovarian cystectomy. Prior surgical records were not obtained by the operating surgeon, although her obstetric history includes 2 prior vaginal deliveries and 2 cesarean deliveries (CDs). The patient had an umbilical herniorraphy a number of years ago. Her medications include hormonal therapy, for presumed menopause, and medication for depression (she reported “doing well” on medication). She reported smoking 1 PPD and had a prior tubal ligation.

VM was previously evaluated for Lynch Syndrome and informed of the potential for increased risks of colon, endometrial, and several other cancers. She did not have cancer as of the time of planned surgery.

The patient underwent robotic-assisted total laparoscopic hysterectomy and bilateral salpingo-oophorectomy. The operating surgeon did not have a lot of experience with robotic hysterectomies but told the patient preoperatively “I have done a few.” Perioperatively, blood loss was minimal, urine output was recorded as 25 mL, and according to the operative report there were extensive pelvic adhesions and no complications. The “ureters were identified” when the broad ligament was opened at the time of skeletonization of the uterine vessels and documented accordingly. The intraoperative Foley was discontinued at the end of the procedure. The pathology report noted diffuse adenomyosis and uterine fibroids; the uterus weighed 250 g. In addition, a “large hemorrhagic corpus luteum cyst” was noted on the right ovary.

The patient presented for a postoperative visit reporting “leaking” serosanguinous fluid that began 2.5 weeks postoperatively and required her to wear 3 to 4 “Depends” every day. She also reported constipation since beginning her prescribed pain medication. She requested a copy of her medical records and said she was dissatisfied with the care she had received related to the hysterectomy; she was “seeking a second opinion from a urologist.” The urologist suggested evaluation of the “leaking,” and a Foley catheter was placed. When she stood up, however, there was leaking around the catheter, and she reported a “yellowish-green,” foul smelling discharge. She called the urologist’s office, stating, “I think I have a bowel obstruction.” The patient was instructed to proceed to the emergency department at her local hospital. She was released with a diagnosis of constipation. Upon follow-up urologic evaluation, a vulvovaginal fistula was noted. Management was a “simple fistula repair,” and the patient did well subsequently.

The patient brought suit against the hospital and operating gynecologist. In part the hospital records noted, “relatively inexperienced robotic surgeon.” The hospital was taken to task for granting privileges to an individual that had prior privilege “problems.”

PHOTO: GETTY IMAGES LL28

Continue to: Medical opinion...

Medical opinion

This case demonstrates a number of issues. (We will discuss the credentials for the surgeon and hospital privileges in the legal considerations section.) From the medical perspective, the rate of urologic injury associated with all hysterectomies is 0.87%.¹ Robotic hysterectomy has been reported at 0.92% in a series published from Henry Ford Hospital.¹ The lowest rate of urologic injury is associated with vaginal hysterectomy, reported at 0.2%.² Reported rates of urologic injury by approach to hysterectomy are¹:

• robotic, 0.92%
• laparoscopic, 0.90%
• vaginal, 0.33%
• abdominal, 0.96%.

Complications by surgeon type also have been addressed, and the percent of total urologic complications are reported as¹:

• ObGyn, 47%
• gyn oncologist, 47%
• urogynecologist, 6%.

Intraoperative conversion to laparotomy from initial robotic approach has been addressed in a retrospective study over a 2-year period, with operative times ranging from 1 hr, 50 min to 9 hrs of surgical time.¹ The vast majority of intraoperative complications in a series reported from Finland were managed “within minutes,” and in the series of 83 patients, 5 (6%) required conversion to laparotomy.² Intraoperative complications reported include failed entry, vascular injury, nerve injury, visceral injury, solid organ injury, tumor fragmentation, and anesthetic-related complications.³ Of note, the vascular injuries included inferior vena cava, common iliac, and external iliac.

Mortality rates in association with benign laparoscopic and robotic procedures have been addressed and noted to be 1:6,456 cases based upon a meta-analysis.⁴ The analysis included 124,216 patients. Laparoscopic versus robotic mortality rates were not statistically different. Mortality was more common among cases of undiagnosed rare colorectal injury. This mortality is on par with complications from Roux-en-Y gastric bypass procedures. Procedures such as sacrocolpopexy are equated with higher mortality (1:1,246) in comparison with benign hysterectomy.⁵

Infectious complications following either laparoscopic or robotic hysterectomy were reported at less than 1% and not statistically different for either approach.⁶ The series authored by Marra et al evaluated 176,016 patients.

Overall, robotic-assisted gynecologic complications are rare. One series was focused on gynecological oncologic cases.⁷ Specific categories of complications included⁷:

• patient positioning and pneumoperitoneum
• injury to surrounding organs
• bowel injury
• port site metastasis
• surgical emphysema
• vaginal cuff dehiscence
• anesthesia-related problems.

The authors concluded, “robotic assisted surgery in gynecological oncology is safe and the incidence of complications is low.”⁷ The major cause of death related to robotic surgery is vascular injury–related. The authors emphasized the importance of knowledge of anatomy, basic principles of “traction and counter-traction” and proper dissection along tissue planes as key to minimizing complications. Consider placement of stents for ureter identification, as appropriate. Barbed-suturing does not prevent dehiscence.

Continue to: Legal considerations...

Robotic surgery presents many legal issues and promises to raise many more in the future. The law must control new technology while encouraging productive uses, and provide new remedies for harms while respecting traditional legal principles.⁸ There is no shortage of good ideas about controlling surgical robots,⁹ automated devices more generally,¹⁰ and artificial intelligence.¹¹ Those issues will be important, and watching them unfold will be intriguing.

In the meantime, physicians and other health care professionals, health care facilities, technology companies, and patients must work within current legal structures in implementing and using robotic surgery. These are extraordinarily complex issues, so it is possible only to review the current landscape and speculate what the near future may hold.

Regulating surgical robots

The US Food and Drug Administration (FDA) is the primary regulator of robots used in medicine.¹² It has the authority to regulate surgical devices, including surgical robots—which it refers to as “robotically-assisted surgical devices,” or RASD. In 2000, it approved Intuitive Surgical’s daVinci system for use in surgery. In 2017, the FDA expanded its clearance to include the Senhance System of TransEnterix Surgical Inc. for minimally invasive gynecologic surgery.¹³ In 2021, the FDA cleared the Hominis Surgical System for transvaginal hysterectomy “in certain patients.” However, the FDA emphasized that this clearance is for benign hysterectomy with salpingo-oophorectomy.¹⁴ (The FDA has cleared various robotic devices for several other areas of surgical practice, including neurosurgery, orthopedics, and urology.)

The use of robots in cancer surgery is limited. The FDA approved specific RASDs in some “surgical procedures commonly performed in patients with cancer, such as hysterectomy, prostatectomy, and colectomy.”¹⁵ However, it cautioned that this clearance was based only on a 30-day patient follow up. More specifically, the FDA “has not evaluated the safety or effectiveness of RASD devices for the prevention or treatment of cancer, based on cancer-related outcomes such as overall survival, recurrence, and disease-free survival.”¹⁵

The FDA has clearly warned physicians and patients that the agency has not granted the use of RASDs “for any cancer-related surgery marketing authorization, and therefore the survival benefits to patients compared to traditional surgery have not been established.”¹⁵ (This did not apply to the hysterectomy surgery as noted above. More specifically, that clearance did not apply to anything other than 30-day results, nor to the efficacy related to cancer survival.)

States also have some authority to regulate medical practice within their borders.⁹ When the FDA has approved a device as safe and effective, however, there are limits on what states can do to regulate or impose liability on the approved product. The Supreme Court held that the FDA approval “pre-empted” some state action regarding approved devices.¹⁶

Hospitals, of course, regulate what is allowed within the hospital. For example, it may require training before a physician is permitted to use equipment, limit the conditions for which the equipment may be used, or decline to obtain equipment for use in the hospitals.¹⁷ In the case of RASDs, however, the high cost of equipment may provide an incentive for hospitals to urge the wide use of the latest robotic acquisition.¹⁸

Regulation aims primarily to protect patients, usually from injury or inadequate treatment. Some robotic surgery is likely to be more expensive than the same surgery without robotic assistance. The cost to the patient is not usually part of the FDA’s consideration. Insurance companies (including Medicare and Medicaid), however, do care about costs and will set or negotiate how much the reimbursement will be for a procedure. Third-party payers may decline to cover the additional cost when there is no apparent benefit from using the robot.¹⁹ For some institutions, the public perception that it offers “the most modern technology” is an important public message and a strong incentive to have the equipment.²⁰

There are inconsistent studies about the advantages and disadvantages of RADS in gynecologic procedures, although there are few randomized studies.²¹ The demonstrated advantages are generally identified as somewhat shorter recovery time.²² The ultimate goal will be to minimize risks while maximizing the many potential benefits of robotic surgery.²³

Continue to: Liability...

Liability

A recent study by De Ravin and colleagues of robotic surgery liability found a 250% increase in the total number of robotic surgery–related malpractice claims reported in 7 recent years (2014-2021), compared with the prior 7 (2006-2013).²⁴ However, the number of cases varied considerably from year to year. ObGyn had the most significant gain (from 19% to 49% of all claims). During the same time, urology claims declined from 56% to 16%. (The limitations of the study’s data are discussed later in this article.)

De Ravin et al reported the legal bases for the claims, but the specific legal claim was unclear in many cases.²⁴ For example, the vast majority were classified as “negligent surgery.” Many cases made more than 1 legal claim for liability, so the total percentages were greater than 100%. Of the specific claims, many appear unrelated to robotic surgery (misdiagnosis, delayed treatment, or infection). However, there were a significant number of cases that raised issues that were related to robotic surgery. The following are those claims that probably relate to the “robotic” surgery, along with the percentage of cases making such a claim as reported²⁴:

• “Patient not a candidate for surgery performed” appeared in about 13% of the cases.²⁴ Such claims could include that the surgeon should have performed the surgery with traditional laparoscopy or open technique, but instead using a robot led to the injury. Physicians may feel pressure from patients or hospitals, because of the equipment’s cost, to use robotic surgery as it seems to be the modern approach (and therefore better). Neither reason is sufficient for using robotic assistance unless it will benefit the patient.
• “Failure to calibrate or operate robot” was in 11% of the claims.²⁴ Physicians must properly calibrate and otherwise ensure that surgical equipment is operating correctly. In addition, the hospitals supplying the equipment must ensure that the equipment is maintained correctly. Finally, the equipment manufacturer may be liable through “products liability” if the equipment is defective.²⁵ The expanding use of artificial intelligence in medical equipment (including surgical robots) is increasing the complexity of determining what “defective” means.¹¹
• “Training deficiencies or credentialing” liability is a common problem with new technology. Physicians using new technology should be thoroughly trained and, where appropriate, certified in the use of the new technology.²⁶ Early adopters of the technology should be especially cautious because good training may be challenging to obtain. In the study, the claims of inadequate training were particularly high during the early 7 years (35%), but dropped during the later time (4%).²⁴
• “Improper positioning” of the patient or device or patient was raised in 7% of the cases.²⁴
• “Manufacturing problems” were claimed in a small number of cases—13% in 2006-2013, but 2% in 2014-2021.²⁴ These cases raise the complex question of products liability for robotic surgery and artificial intelligence (AI). Products liability has been part of surgical practice for many years. There usually will be liability if there are “defects” in a product, whether or not resulting from negligence. What a “defect” in a computer program means is a complicated issue that will be significant in future liability cases.²⁷

Several other cases reported in the De Ravin study were probably related to robotic surgery. For example, Informed Consent and Failure to Monitor each appeared in more than 30%, of 2014-2021 cases, and Failure to Refer in 16% of the cases.^24,27

The outcomes of the reported cases were mostly verdicts (or trial-related settlements) for defendants (doctors and hospitals). The defense prevailed 69% of the time in the early period and 78% of the time in 2014-2021. However, there were substantial damages in some cases. The range of damages in 2006-2013 was $95,000 to $6 million (mean, $2.5 million); in 2014-2021, it was $10,000 to $5 million (mean, $1.3 million).²⁴

An earlier study looked at reported cases against Intuitive Surgical, maker of the daVinci system, from 2000-2017.²⁸ Of the 108 claims in the study, 62% were gynecologic surgeries. Of these claims, 35% were dismissed, but “no other information regarding settlements or trial outcomes was available.” The study did not report the basis for the lawsuits involving gynecologic surgeries.

We should exercise caution in reviewing these studies. Although the studies were of considerable value, the authors note significant limitations of the databases available. The database was Westlaw in the first study discussed (“Robotic surgery: the impact”²⁴) and Bloomberg in the second (“Robotic urologic”²⁸). For example, the “impact” study was based on “jury verdict reports” excluding settlements, and the latter excluded class actions and cases settled. Thus the studies undoubtedly understated the number of claims made (those that resulted in settlement before a lawsuit was filed), cases filed but abandoned, and settlements made before trial.

Despite these limitations, the studies provide valuable insights into current malpractice risks and future directions. It is worth remembering that these cases nearly all involved a single robot, the daVinci, produced by Intuitive Surgical. It is not a “smart” robot and is commonly referred to as a “master-slave” machine. With much more intelligent and independent machines, the future will raise more complex problems in the FDA approval process and malpractice and product liability claims when things go wrong.

Continue to: What’s the verdict?...

The case of VM and operating surgeon Dr. G illustrates several important legal aspects of using surgical robots. It also demonstrates that the presence of the robot assist still requires the surgeon’s careful attention to issues of informed consent, adequate specific training, and thorough follow up. In the following discussion, we divide the case review into the elements of negligence-malpractice (duty and breach, causation, and damages) and conclude with a thought about how to proceed when things have gone wrong.

Dr. G’s statement, “I’ve done a few,” is indefinite, but it may suggest that Dr. G. had not received full, supervised training in the robotic assist he was planning to use. That problem was underlined by the conclusion that Dr. G was a “relatively inexperienced robotic surgeon.” If so, that failure could constitute a breach of the duty of care to the patient. In addition, if it is inaccurate or did not provide information VM reasonably needed in consenting to Dr. G proceeding with the surgery, there could be an issue of whether there was a partial failure of fully informed consent.

The hospital also may have potential liability. It was “taken to task for granting privileges to an individual that had prior privilege ‘problems,’” suggesting that it had not performed adequate review before granting hospital privileges. Furthermore, if Dr. G was not sufficiently practiced or supervised in robotic surgery, the hospital, which allowed Dr. G to proceed, might also be negligent.

VM had a series of problems postsurgery that ultimately resulted in additional care and “simple fistula repair.” Assuming that there was negligence, the next question is whether that failure caused the injury. Causation may be the most difficult part of the case for VM to prove. It would require expert testimony that the inadequate surgery (inappropriate use of robotic surgery or other error during surgery) and follow up resulted in the formation or increase in the likelihood of the fistula.

VM would also have to prove damages. Damages are those costs (the economic value) of injuries that would not have occurred but for negligence. Damages would include most of the cost of the follow-up medical care and any related additional future care required, plus costs that were a consequence of the negligence (such as lost work). In addition, damages would include pain and suffering that resulted from the negligence, subject to caps in some states.

When the patient was dissatisfied and reported a postsurgical problem, the hospital and Dr. G may have had an opportunity to avoid further dissatisfaction, complaints, and ultimately a lawsuit. Effective approaches for dealing with such dissatisfaction may serve the institution’s and physician’s values and financial best interests.

The jury verdict was in favor of the plaintiff. Jurors felt the operating surgeon should have conveyed his experience with robotic surgery more clearly as part of the informed consent process.

“Hey Siri! Perform a type 3 hysterectomy. Please watch out for the ureter!”²⁹

Medicine is still at the frontier of surgical robots. Over future decades, the number and sophistication of these machines will increase substantially. They likely will become much more like robots, guided by AI, and make independent judgments. These have the potential for significant medical progress that improves the treatment of patients. At the same time, the last 20 years suggest that robotic innovation will challenge medicine, the FDA and other regulators, lawmakers, and courts. In the future, regulators and patients should embrace genuine advances in robotic surgery but not be dazzled by these new machines’ luster (or potential for considerable profits).³⁰

The public may be wildly optimistic about the benefits without balancing the risks. The AI that runs them will be essentially invisible and constantly changing. Physicians and regulators must develop new techniques for assessing and controlling the software. Real surgical robots require rigorous testing, cautious promotion, disciplined use, and perpetual review. ●

The approach to hysterectomy has been debated, with the need for individualization case by case stressed, and the expertise of the operating surgeon considered.

CASE Was surgeon experience a factor in case complications?

VM is a 46-year-old woman (G5 P4014) reporting persistent uterine bleeding that is refractory to medical therapy. The patient has uterine fibroids, 6 weeks in size on examination, with “mild” prolapse noted. Additional medical diagnoses included vulvitis, ovarian cyst in the past, cystic mastopathy, and prior evidence of pelvic adhesion, noted at the time of ovarian cystectomy. Prior surgical records were not obtained by the operating surgeon, although her obstetric history includes 2 prior vaginal deliveries and 2 cesarean deliveries (CDs). The patient had an umbilical herniorraphy a number of years ago. Her medications include hormonal therapy, for presumed menopause, and medication for depression (she reported “doing well” on medication). She reported smoking 1 PPD and had a prior tubal ligation.

VM was previously evaluated for Lynch Syndrome and informed of the potential for increased risks of colon, endometrial, and several other cancers. She did not have cancer as of the time of planned surgery.

The patient underwent robotic-assisted total laparoscopic hysterectomy and bilateral salpingo-oophorectomy. The operating surgeon did not have a lot of experience with robotic hysterectomies but told the patient preoperatively “I have done a few.” Perioperatively, blood loss was minimal, urine output was recorded as 25 mL, and according to the operative report there were extensive pelvic adhesions and no complications. The “ureters were identified” when the broad ligament was opened at the time of skeletonization of the uterine vessels and documented accordingly. The intraoperative Foley was discontinued at the end of the procedure. The pathology report noted diffuse adenomyosis and uterine fibroids; the uterus weighed 250 g. In addition, a “large hemorrhagic corpus luteum cyst” was noted on the right ovary.

The patient presented for a postoperative visit reporting “leaking” serosanguinous fluid that began 2.5 weeks postoperatively and required her to wear 3 to 4 “Depends” every day. She also reported constipation since beginning her prescribed pain medication. She requested a copy of her medical records and said she was dissatisfied with the care she had received related to the hysterectomy; she was “seeking a second opinion from a urologist.” The urologist suggested evaluation of the “leaking,” and a Foley catheter was placed. When she stood up, however, there was leaking around the catheter, and she reported a “yellowish-green,” foul smelling discharge. She called the urologist’s office, stating, “I think I have a bowel obstruction.” The patient was instructed to proceed to the emergency department at her local hospital. She was released with a diagnosis of constipation. Upon follow-up urologic evaluation, a vulvovaginal fistula was noted. Management was a “simple fistula repair,” and the patient did well subsequently.

The patient brought suit against the hospital and operating gynecologist. In part the hospital records noted, “relatively inexperienced robotic surgeon.” The hospital was taken to task for granting privileges to an individual that had prior privilege “problems.”

PHOTO: GETTY IMAGES LL28

Continue to: Medical opinion...

Medical opinion

This case demonstrates a number of issues. (We will discuss the credentials for the surgeon and hospital privileges in the legal considerations section.) From the medical perspective, the rate of urologic injury associated with all hysterectomies is 0.87%.¹ Robotic hysterectomy has been reported at 0.92% in a series published from Henry Ford Hospital.¹ The lowest rate of urologic injury is associated with vaginal hysterectomy, reported at 0.2%.² Reported rates of urologic injury by approach to hysterectomy are¹:

• robotic, 0.92%
• laparoscopic, 0.90%
• vaginal, 0.33%
• abdominal, 0.96%.

Complications by surgeon type also have been addressed, and the percent of total urologic complications are reported as¹:

• ObGyn, 47%
• gyn oncologist, 47%
• urogynecologist, 6%.

Intraoperative conversion to laparotomy from initial robotic approach has been addressed in a retrospective study over a 2-year period, with operative times ranging from 1 hr, 50 min to 9 hrs of surgical time.¹ The vast majority of intraoperative complications in a series reported from Finland were managed “within minutes,” and in the series of 83 patients, 5 (6%) required conversion to laparotomy.² Intraoperative complications reported include failed entry, vascular injury, nerve injury, visceral injury, solid organ injury, tumor fragmentation, and anesthetic-related complications.³ Of note, the vascular injuries included inferior vena cava, common iliac, and external iliac.

Mortality rates in association with benign laparoscopic and robotic procedures have been addressed and noted to be 1:6,456 cases based upon a meta-analysis.⁴ The analysis included 124,216 patients. Laparoscopic versus robotic mortality rates were not statistically different. Mortality was more common among cases of undiagnosed rare colorectal injury. This mortality is on par with complications from Roux-en-Y gastric bypass procedures. Procedures such as sacrocolpopexy are equated with higher mortality (1:1,246) in comparison with benign hysterectomy.⁵

Infectious complications following either laparoscopic or robotic hysterectomy were reported at less than 1% and not statistically different for either approach.⁶ The series authored by Marra et al evaluated 176,016 patients.

Overall, robotic-assisted gynecologic complications are rare. One series was focused on gynecological oncologic cases.⁷ Specific categories of complications included⁷:

• patient positioning and pneumoperitoneum
• injury to surrounding organs
• bowel injury
• port site metastasis
• surgical emphysema
• vaginal cuff dehiscence
• anesthesia-related problems.

The authors concluded, “robotic assisted surgery in gynecological oncology is safe and the incidence of complications is low.”⁷ The major cause of death related to robotic surgery is vascular injury–related. The authors emphasized the importance of knowledge of anatomy, basic principles of “traction and counter-traction” and proper dissection along tissue planes as key to minimizing complications. Consider placement of stents for ureter identification, as appropriate. Barbed-suturing does not prevent dehiscence.

Continue to: Legal considerations...

Robotic surgery presents many legal issues and promises to raise many more in the future. The law must control new technology while encouraging productive uses, and provide new remedies for harms while respecting traditional legal principles.⁸ There is no shortage of good ideas about controlling surgical robots,⁹ automated devices more generally,¹⁰ and artificial intelligence.¹¹ Those issues will be important, and watching them unfold will be intriguing.

In the meantime, physicians and other health care professionals, health care facilities, technology companies, and patients must work within current legal structures in implementing and using robotic surgery. These are extraordinarily complex issues, so it is possible only to review the current landscape and speculate what the near future may hold.

Regulating surgical robots

The US Food and Drug Administration (FDA) is the primary regulator of robots used in medicine.¹² It has the authority to regulate surgical devices, including surgical robots—which it refers to as “robotically-assisted surgical devices,” or RASD. In 2000, it approved Intuitive Surgical’s daVinci system for use in surgery. In 2017, the FDA expanded its clearance to include the Senhance System of TransEnterix Surgical Inc. for minimally invasive gynecologic surgery.¹³ In 2021, the FDA cleared the Hominis Surgical System for transvaginal hysterectomy “in certain patients.” However, the FDA emphasized that this clearance is for benign hysterectomy with salpingo-oophorectomy.¹⁴ (The FDA has cleared various robotic devices for several other areas of surgical practice, including neurosurgery, orthopedics, and urology.)

The use of robots in cancer surgery is limited. The FDA approved specific RASDs in some “surgical procedures commonly performed in patients with cancer, such as hysterectomy, prostatectomy, and colectomy.”¹⁵ However, it cautioned that this clearance was based only on a 30-day patient follow up. More specifically, the FDA “has not evaluated the safety or effectiveness of RASD devices for the prevention or treatment of cancer, based on cancer-related outcomes such as overall survival, recurrence, and disease-free survival.”¹⁵

The FDA has clearly warned physicians and patients that the agency has not granted the use of RASDs “for any cancer-related surgery marketing authorization, and therefore the survival benefits to patients compared to traditional surgery have not been established.”¹⁵ (This did not apply to the hysterectomy surgery as noted above. More specifically, that clearance did not apply to anything other than 30-day results, nor to the efficacy related to cancer survival.)

States also have some authority to regulate medical practice within their borders.⁹ When the FDA has approved a device as safe and effective, however, there are limits on what states can do to regulate or impose liability on the approved product. The Supreme Court held that the FDA approval “pre-empted” some state action regarding approved devices.¹⁶

Hospitals, of course, regulate what is allowed within the hospital. For example, it may require training before a physician is permitted to use equipment, limit the conditions for which the equipment may be used, or decline to obtain equipment for use in the hospitals.¹⁷ In the case of RASDs, however, the high cost of equipment may provide an incentive for hospitals to urge the wide use of the latest robotic acquisition.¹⁸

Regulation aims primarily to protect patients, usually from injury or inadequate treatment. Some robotic surgery is likely to be more expensive than the same surgery without robotic assistance. The cost to the patient is not usually part of the FDA’s consideration. Insurance companies (including Medicare and Medicaid), however, do care about costs and will set or negotiate how much the reimbursement will be for a procedure. Third-party payers may decline to cover the additional cost when there is no apparent benefit from using the robot.¹⁹ For some institutions, the public perception that it offers “the most modern technology” is an important public message and a strong incentive to have the equipment.²⁰

There are inconsistent studies about the advantages and disadvantages of RADS in gynecologic procedures, although there are few randomized studies.²¹ The demonstrated advantages are generally identified as somewhat shorter recovery time.²² The ultimate goal will be to minimize risks while maximizing the many potential benefits of robotic surgery.²³

Continue to: Liability...

Liability

A recent study by De Ravin and colleagues of robotic surgery liability found a 250% increase in the total number of robotic surgery–related malpractice claims reported in 7 recent years (2014-2021), compared with the prior 7 (2006-2013).²⁴ However, the number of cases varied considerably from year to year. ObGyn had the most significant gain (from 19% to 49% of all claims). During the same time, urology claims declined from 56% to 16%. (The limitations of the study’s data are discussed later in this article.)

De Ravin et al reported the legal bases for the claims, but the specific legal claim was unclear in many cases.²⁴ For example, the vast majority were classified as “negligent surgery.” Many cases made more than 1 legal claim for liability, so the total percentages were greater than 100%. Of the specific claims, many appear unrelated to robotic surgery (misdiagnosis, delayed treatment, or infection). However, there were a significant number of cases that raised issues that were related to robotic surgery. The following are those claims that probably relate to the “robotic” surgery, along with the percentage of cases making such a claim as reported²⁴:

• “Patient not a candidate for surgery performed” appeared in about 13% of the cases.²⁴ Such claims could include that the surgeon should have performed the surgery with traditional laparoscopy or open technique, but instead using a robot led to the injury. Physicians may feel pressure from patients or hospitals, because of the equipment’s cost, to use robotic surgery as it seems to be the modern approach (and therefore better). Neither reason is sufficient for using robotic assistance unless it will benefit the patient.
• “Failure to calibrate or operate robot” was in 11% of the claims.²⁴ Physicians must properly calibrate and otherwise ensure that surgical equipment is operating correctly. In addition, the hospitals supplying the equipment must ensure that the equipment is maintained correctly. Finally, the equipment manufacturer may be liable through “products liability” if the equipment is defective.²⁵ The expanding use of artificial intelligence in medical equipment (including surgical robots) is increasing the complexity of determining what “defective” means.¹¹
• “Training deficiencies or credentialing” liability is a common problem with new technology. Physicians using new technology should be thoroughly trained and, where appropriate, certified in the use of the new technology.²⁶ Early adopters of the technology should be especially cautious because good training may be challenging to obtain. In the study, the claims of inadequate training were particularly high during the early 7 years (35%), but dropped during the later time (4%).²⁴
• “Improper positioning” of the patient or device or patient was raised in 7% of the cases.²⁴
• “Manufacturing problems” were claimed in a small number of cases—13% in 2006-2013, but 2% in 2014-2021.²⁴ These cases raise the complex question of products liability for robotic surgery and artificial intelligence (AI). Products liability has been part of surgical practice for many years. There usually will be liability if there are “defects” in a product, whether or not resulting from negligence. What a “defect” in a computer program means is a complicated issue that will be significant in future liability cases.²⁷

Several other cases reported in the De Ravin study were probably related to robotic surgery. For example, Informed Consent and Failure to Monitor each appeared in more than 30%, of 2014-2021 cases, and Failure to Refer in 16% of the cases.^24,27

The outcomes of the reported cases were mostly verdicts (or trial-related settlements) for defendants (doctors and hospitals). The defense prevailed 69% of the time in the early period and 78% of the time in 2014-2021. However, there were substantial damages in some cases. The range of damages in 2006-2013 was $95,000 to $6 million (mean, $2.5 million); in 2014-2021, it was $10,000 to $5 million (mean, $1.3 million).²⁴

An earlier study looked at reported cases against Intuitive Surgical, maker of the daVinci system, from 2000-2017.²⁸ Of the 108 claims in the study, 62% were gynecologic surgeries. Of these claims, 35% were dismissed, but “no other information regarding settlements or trial outcomes was available.” The study did not report the basis for the lawsuits involving gynecologic surgeries.

We should exercise caution in reviewing these studies. Although the studies were of considerable value, the authors note significant limitations of the databases available. The database was Westlaw in the first study discussed (“Robotic surgery: the impact”²⁴) and Bloomberg in the second (“Robotic urologic”²⁸). For example, the “impact” study was based on “jury verdict reports” excluding settlements, and the latter excluded class actions and cases settled. Thus the studies undoubtedly understated the number of claims made (those that resulted in settlement before a lawsuit was filed), cases filed but abandoned, and settlements made before trial.

Despite these limitations, the studies provide valuable insights into current malpractice risks and future directions. It is worth remembering that these cases nearly all involved a single robot, the daVinci, produced by Intuitive Surgical. It is not a “smart” robot and is commonly referred to as a “master-slave” machine. With much more intelligent and independent machines, the future will raise more complex problems in the FDA approval process and malpractice and product liability claims when things go wrong.

Continue to: What’s the verdict?...

The case of VM and operating surgeon Dr. G illustrates several important legal aspects of using surgical robots. It also demonstrates that the presence of the robot assist still requires the surgeon’s careful attention to issues of informed consent, adequate specific training, and thorough follow up. In the following discussion, we divide the case review into the elements of negligence-malpractice (duty and breach, causation, and damages) and conclude with a thought about how to proceed when things have gone wrong.

Dr. G’s statement, “I’ve done a few,” is indefinite, but it may suggest that Dr. G. had not received full, supervised training in the robotic assist he was planning to use. That problem was underlined by the conclusion that Dr. G was a “relatively inexperienced robotic surgeon.” If so, that failure could constitute a breach of the duty of care to the patient. In addition, if it is inaccurate or did not provide information VM reasonably needed in consenting to Dr. G proceeding with the surgery, there could be an issue of whether there was a partial failure of fully informed consent.

The hospital also may have potential liability. It was “taken to task for granting privileges to an individual that had prior privilege ‘problems,’” suggesting that it had not performed adequate review before granting hospital privileges. Furthermore, if Dr. G was not sufficiently practiced or supervised in robotic surgery, the hospital, which allowed Dr. G to proceed, might also be negligent.

VM had a series of problems postsurgery that ultimately resulted in additional care and “simple fistula repair.” Assuming that there was negligence, the next question is whether that failure caused the injury. Causation may be the most difficult part of the case for VM to prove. It would require expert testimony that the inadequate surgery (inappropriate use of robotic surgery or other error during surgery) and follow up resulted in the formation or increase in the likelihood of the fistula.

VM would also have to prove damages. Damages are those costs (the economic value) of injuries that would not have occurred but for negligence. Damages would include most of the cost of the follow-up medical care and any related additional future care required, plus costs that were a consequence of the negligence (such as lost work). In addition, damages would include pain and suffering that resulted from the negligence, subject to caps in some states.

When the patient was dissatisfied and reported a postsurgical problem, the hospital and Dr. G may have had an opportunity to avoid further dissatisfaction, complaints, and ultimately a lawsuit. Effective approaches for dealing with such dissatisfaction may serve the institution’s and physician’s values and financial best interests.

The jury verdict was in favor of the plaintiff. Jurors felt the operating surgeon should have conveyed his experience with robotic surgery more clearly as part of the informed consent process.

“Hey Siri! Perform a type 3 hysterectomy. Please watch out for the ureter!”²⁹

Medicine is still at the frontier of surgical robots. Over future decades, the number and sophistication of these machines will increase substantially. They likely will become much more like robots, guided by AI, and make independent judgments. These have the potential for significant medical progress that improves the treatment of patients. At the same time, the last 20 years suggest that robotic innovation will challenge medicine, the FDA and other regulators, lawmakers, and courts. In the future, regulators and patients should embrace genuine advances in robotic surgery but not be dazzled by these new machines’ luster (or potential for considerable profits).³⁰

The public may be wildly optimistic about the benefits without balancing the risks. The AI that runs them will be essentially invisible and constantly changing. Physicians and regulators must develop new techniques for assessing and controlling the software. Real surgical robots require rigorous testing, cautious promotion, disciplined use, and perpetual review. ●

The approach to hysterectomy has been debated, with the need for individualization case by case stressed, and the expertise of the operating surgeon considered.

CASE Was surgeon experience a factor in case complications?

VM is a 46-year-old woman (G5 P4014) reporting persistent uterine bleeding that is refractory to medical therapy. The patient has uterine fibroids, 6 weeks in size on examination, with “mild” prolapse noted. Additional medical diagnoses included vulvitis, ovarian cyst in the past, cystic mastopathy, and prior evidence of pelvic adhesion, noted at the time of ovarian cystectomy. Prior surgical records were not obtained by the operating surgeon, although her obstetric history includes 2 prior vaginal deliveries and 2 cesarean deliveries (CDs). The patient had an umbilical herniorraphy a number of years ago. Her medications include hormonal therapy, for presumed menopause, and medication for depression (she reported “doing well” on medication). She reported smoking 1 PPD and had a prior tubal ligation.

VM was previously evaluated for Lynch Syndrome and informed of the potential for increased risks of colon, endometrial, and several other cancers. She did not have cancer as of the time of planned surgery.

The patient underwent robotic-assisted total laparoscopic hysterectomy and bilateral salpingo-oophorectomy. The operating surgeon did not have a lot of experience with robotic hysterectomies but told the patient preoperatively “I have done a few.” Perioperatively, blood loss was minimal, urine output was recorded as 25 mL, and according to the operative report there were extensive pelvic adhesions and no complications. The “ureters were identified” when the broad ligament was opened at the time of skeletonization of the uterine vessels and documented accordingly. The intraoperative Foley was discontinued at the end of the procedure. The pathology report noted diffuse adenomyosis and uterine fibroids; the uterus weighed 250 g. In addition, a “large hemorrhagic corpus luteum cyst” was noted on the right ovary.

The patient presented for a postoperative visit reporting “leaking” serosanguinous fluid that began 2.5 weeks postoperatively and required her to wear 3 to 4 “Depends” every day. She also reported constipation since beginning her prescribed pain medication. She requested a copy of her medical records and said she was dissatisfied with the care she had received related to the hysterectomy; she was “seeking a second opinion from a urologist.” The urologist suggested evaluation of the “leaking,” and a Foley catheter was placed. When she stood up, however, there was leaking around the catheter, and she reported a “yellowish-green,” foul smelling discharge. She called the urologist’s office, stating, “I think I have a bowel obstruction.” The patient was instructed to proceed to the emergency department at her local hospital. She was released with a diagnosis of constipation. Upon follow-up urologic evaluation, a vulvovaginal fistula was noted. Management was a “simple fistula repair,” and the patient did well subsequently.

The patient brought suit against the hospital and operating gynecologist. In part the hospital records noted, “relatively inexperienced robotic surgeon.” The hospital was taken to task for granting privileges to an individual that had prior privilege “problems.”

PHOTO: GETTY IMAGES LL28

Continue to: Medical opinion...

Medical opinion

This case demonstrates a number of issues. (We will discuss the credentials for the surgeon and hospital privileges in the legal considerations section.) From the medical perspective, the rate of urologic injury associated with all hysterectomies is 0.87%.¹ Robotic hysterectomy has been reported at 0.92% in a series published from Henry Ford Hospital.¹ The lowest rate of urologic injury is associated with vaginal hysterectomy, reported at 0.2%.² Reported rates of urologic injury by approach to hysterectomy are¹:

• robotic, 0.92%
• laparoscopic, 0.90%
• vaginal, 0.33%
• abdominal, 0.96%.

Complications by surgeon type also have been addressed, and the percent of total urologic complications are reported as¹:

• ObGyn, 47%
• gyn oncologist, 47%
• urogynecologist, 6%.

Intraoperative conversion to laparotomy from initial robotic approach has been addressed in a retrospective study over a 2-year period, with operative times ranging from 1 hr, 50 min to 9 hrs of surgical time.¹ The vast majority of intraoperative complications in a series reported from Finland were managed “within minutes,” and in the series of 83 patients, 5 (6%) required conversion to laparotomy.² Intraoperative complications reported include failed entry, vascular injury, nerve injury, visceral injury, solid organ injury, tumor fragmentation, and anesthetic-related complications.³ Of note, the vascular injuries included inferior vena cava, common iliac, and external iliac.

Mortality rates in association with benign laparoscopic and robotic procedures have been addressed and noted to be 1:6,456 cases based upon a meta-analysis.⁴ The analysis included 124,216 patients. Laparoscopic versus robotic mortality rates were not statistically different. Mortality was more common among cases of undiagnosed rare colorectal injury. This mortality is on par with complications from Roux-en-Y gastric bypass procedures. Procedures such as sacrocolpopexy are equated with higher mortality (1:1,246) in comparison with benign hysterectomy.⁵

Infectious complications following either laparoscopic or robotic hysterectomy were reported at less than 1% and not statistically different for either approach.⁶ The series authored by Marra et al evaluated 176,016 patients.

Overall, robotic-assisted gynecologic complications are rare. One series was focused on gynecological oncologic cases.⁷ Specific categories of complications included⁷:

• patient positioning and pneumoperitoneum
• injury to surrounding organs
• bowel injury
• port site metastasis
• surgical emphysema
• vaginal cuff dehiscence
• anesthesia-related problems.

The authors concluded, “robotic assisted surgery in gynecological oncology is safe and the incidence of complications is low.”⁷ The major cause of death related to robotic surgery is vascular injury–related. The authors emphasized the importance of knowledge of anatomy, basic principles of “traction and counter-traction” and proper dissection along tissue planes as key to minimizing complications. Consider placement of stents for ureter identification, as appropriate. Barbed-suturing does not prevent dehiscence.

Continue to: Legal considerations...

Robotic surgery presents many legal issues and promises to raise many more in the future. The law must control new technology while encouraging productive uses, and provide new remedies for harms while respecting traditional legal principles.⁸ There is no shortage of good ideas about controlling surgical robots,⁹ automated devices more generally,¹⁰ and artificial intelligence.¹¹ Those issues will be important, and watching them unfold will be intriguing.

In the meantime, physicians and other health care professionals, health care facilities, technology companies, and patients must work within current legal structures in implementing and using robotic surgery. These are extraordinarily complex issues, so it is possible only to review the current landscape and speculate what the near future may hold.

Regulating surgical robots

The US Food and Drug Administration (FDA) is the primary regulator of robots used in medicine.¹² It has the authority to regulate surgical devices, including surgical robots—which it refers to as “robotically-assisted surgical devices,” or RASD. In 2000, it approved Intuitive Surgical’s daVinci system for use in surgery. In 2017, the FDA expanded its clearance to include the Senhance System of TransEnterix Surgical Inc. for minimally invasive gynecologic surgery.¹³ In 2021, the FDA cleared the Hominis Surgical System for transvaginal hysterectomy “in certain patients.” However, the FDA emphasized that this clearance is for benign hysterectomy with salpingo-oophorectomy.¹⁴ (The FDA has cleared various robotic devices for several other areas of surgical practice, including neurosurgery, orthopedics, and urology.)

The use of robots in cancer surgery is limited. The FDA approved specific RASDs in some “surgical procedures commonly performed in patients with cancer, such as hysterectomy, prostatectomy, and colectomy.”¹⁵ However, it cautioned that this clearance was based only on a 30-day patient follow up. More specifically, the FDA “has not evaluated the safety or effectiveness of RASD devices for the prevention or treatment of cancer, based on cancer-related outcomes such as overall survival, recurrence, and disease-free survival.”¹⁵

The FDA has clearly warned physicians and patients that the agency has not granted the use of RASDs “for any cancer-related surgery marketing authorization, and therefore the survival benefits to patients compared to traditional surgery have not been established.”¹⁵ (This did not apply to the hysterectomy surgery as noted above. More specifically, that clearance did not apply to anything other than 30-day results, nor to the efficacy related to cancer survival.)

States also have some authority to regulate medical practice within their borders.⁹ When the FDA has approved a device as safe and effective, however, there are limits on what states can do to regulate or impose liability on the approved product. The Supreme Court held that the FDA approval “pre-empted” some state action regarding approved devices.¹⁶

Hospitals, of course, regulate what is allowed within the hospital. For example, it may require training before a physician is permitted to use equipment, limit the conditions for which the equipment may be used, or decline to obtain equipment for use in the hospitals.¹⁷ In the case of RASDs, however, the high cost of equipment may provide an incentive for hospitals to urge the wide use of the latest robotic acquisition.¹⁸

Regulation aims primarily to protect patients, usually from injury or inadequate treatment. Some robotic surgery is likely to be more expensive than the same surgery without robotic assistance. The cost to the patient is not usually part of the FDA’s consideration. Insurance companies (including Medicare and Medicaid), however, do care about costs and will set or negotiate how much the reimbursement will be for a procedure. Third-party payers may decline to cover the additional cost when there is no apparent benefit from using the robot.¹⁹ For some institutions, the public perception that it offers “the most modern technology” is an important public message and a strong incentive to have the equipment.²⁰

There are inconsistent studies about the advantages and disadvantages of RADS in gynecologic procedures, although there are few randomized studies.²¹ The demonstrated advantages are generally identified as somewhat shorter recovery time.²² The ultimate goal will be to minimize risks while maximizing the many potential benefits of robotic surgery.²³

Continue to: Liability...

Liability

A recent study by De Ravin and colleagues of robotic surgery liability found a 250% increase in the total number of robotic surgery–related malpractice claims reported in 7 recent years (2014-2021), compared with the prior 7 (2006-2013).²⁴ However, the number of cases varied considerably from year to year. ObGyn had the most significant gain (from 19% to 49% of all claims). During the same time, urology claims declined from 56% to 16%. (The limitations of the study’s data are discussed later in this article.)

De Ravin et al reported the legal bases for the claims, but the specific legal claim was unclear in many cases.²⁴ For example, the vast majority were classified as “negligent surgery.” Many cases made more than 1 legal claim for liability, so the total percentages were greater than 100%. Of the specific claims, many appear unrelated to robotic surgery (misdiagnosis, delayed treatment, or infection). However, there were a significant number of cases that raised issues that were related to robotic surgery. The following are those claims that probably relate to the “robotic” surgery, along with the percentage of cases making such a claim as reported²⁴:

• “Patient not a candidate for surgery performed” appeared in about 13% of the cases.²⁴ Such claims could include that the surgeon should have performed the surgery with traditional laparoscopy or open technique, but instead using a robot led to the injury. Physicians may feel pressure from patients or hospitals, because of the equipment’s cost, to use robotic surgery as it seems to be the modern approach (and therefore better). Neither reason is sufficient for using robotic assistance unless it will benefit the patient.
• “Failure to calibrate or operate robot” was in 11% of the claims.²⁴ Physicians must properly calibrate and otherwise ensure that surgical equipment is operating correctly. In addition, the hospitals supplying the equipment must ensure that the equipment is maintained correctly. Finally, the equipment manufacturer may be liable through “products liability” if the equipment is defective.²⁵ The expanding use of artificial intelligence in medical equipment (including surgical robots) is increasing the complexity of determining what “defective” means.¹¹
• “Training deficiencies or credentialing” liability is a common problem with new technology. Physicians using new technology should be thoroughly trained and, where appropriate, certified in the use of the new technology.²⁶ Early adopters of the technology should be especially cautious because good training may be challenging to obtain. In the study, the claims of inadequate training were particularly high during the early 7 years (35%), but dropped during the later time (4%).²⁴
• “Improper positioning” of the patient or device or patient was raised in 7% of the cases.²⁴
• “Manufacturing problems” were claimed in a small number of cases—13% in 2006-2013, but 2% in 2014-2021.²⁴ These cases raise the complex question of products liability for robotic surgery and artificial intelligence (AI). Products liability has been part of surgical practice for many years. There usually will be liability if there are “defects” in a product, whether or not resulting from negligence. What a “defect” in a computer program means is a complicated issue that will be significant in future liability cases.²⁷

Several other cases reported in the De Ravin study were probably related to robotic surgery. For example, Informed Consent and Failure to Monitor each appeared in more than 30%, of 2014-2021 cases, and Failure to Refer in 16% of the cases.^24,27

The outcomes of the reported cases were mostly verdicts (or trial-related settlements) for defendants (doctors and hospitals). The defense prevailed 69% of the time in the early period and 78% of the time in 2014-2021. However, there were substantial damages in some cases. The range of damages in 2006-2013 was $95,000 to $6 million (mean, $2.5 million); in 2014-2021, it was $10,000 to $5 million (mean, $1.3 million).²⁴

An earlier study looked at reported cases against Intuitive Surgical, maker of the daVinci system, from 2000-2017.²⁸ Of the 108 claims in the study, 62% were gynecologic surgeries. Of these claims, 35% were dismissed, but “no other information regarding settlements or trial outcomes was available.” The study did not report the basis for the lawsuits involving gynecologic surgeries.

We should exercise caution in reviewing these studies. Although the studies were of considerable value, the authors note significant limitations of the databases available. The database was Westlaw in the first study discussed (“Robotic surgery: the impact”²⁴) and Bloomberg in the second (“Robotic urologic”²⁸). For example, the “impact” study was based on “jury verdict reports” excluding settlements, and the latter excluded class actions and cases settled. Thus the studies undoubtedly understated the number of claims made (those that resulted in settlement before a lawsuit was filed), cases filed but abandoned, and settlements made before trial.

Despite these limitations, the studies provide valuable insights into current malpractice risks and future directions. It is worth remembering that these cases nearly all involved a single robot, the daVinci, produced by Intuitive Surgical. It is not a “smart” robot and is commonly referred to as a “master-slave” machine. With much more intelligent and independent machines, the future will raise more complex problems in the FDA approval process and malpractice and product liability claims when things go wrong.

Continue to: What’s the verdict?...

The case of VM and operating surgeon Dr. G illustrates several important legal aspects of using surgical robots. It also demonstrates that the presence of the robot assist still requires the surgeon’s careful attention to issues of informed consent, adequate specific training, and thorough follow up. In the following discussion, we divide the case review into the elements of negligence-malpractice (duty and breach, causation, and damages) and conclude with a thought about how to proceed when things have gone wrong.

Dr. G’s statement, “I’ve done a few,” is indefinite, but it may suggest that Dr. G. had not received full, supervised training in the robotic assist he was planning to use. That problem was underlined by the conclusion that Dr. G was a “relatively inexperienced robotic surgeon.” If so, that failure could constitute a breach of the duty of care to the patient. In addition, if it is inaccurate or did not provide information VM reasonably needed in consenting to Dr. G proceeding with the surgery, there could be an issue of whether there was a partial failure of fully informed consent.

The hospital also may have potential liability. It was “taken to task for granting privileges to an individual that had prior privilege ‘problems,’” suggesting that it had not performed adequate review before granting hospital privileges. Furthermore, if Dr. G was not sufficiently practiced or supervised in robotic surgery, the hospital, which allowed Dr. G to proceed, might also be negligent.

VM had a series of problems postsurgery that ultimately resulted in additional care and “simple fistula repair.” Assuming that there was negligence, the next question is whether that failure caused the injury. Causation may be the most difficult part of the case for VM to prove. It would require expert testimony that the inadequate surgery (inappropriate use of robotic surgery or other error during surgery) and follow up resulted in the formation or increase in the likelihood of the fistula.

VM would also have to prove damages. Damages are those costs (the economic value) of injuries that would not have occurred but for negligence. Damages would include most of the cost of the follow-up medical care and any related additional future care required, plus costs that were a consequence of the negligence (such as lost work). In addition, damages would include pain and suffering that resulted from the negligence, subject to caps in some states.

When the patient was dissatisfied and reported a postsurgical problem, the hospital and Dr. G may have had an opportunity to avoid further dissatisfaction, complaints, and ultimately a lawsuit. Effective approaches for dealing with such dissatisfaction may serve the institution’s and physician’s values and financial best interests.

The jury verdict was in favor of the plaintiff. Jurors felt the operating surgeon should have conveyed his experience with robotic surgery more clearly as part of the informed consent process.

“Hey Siri! Perform a type 3 hysterectomy. Please watch out for the ureter!”²⁹

Medicine is still at the frontier of surgical robots. Over future decades, the number and sophistication of these machines will increase substantially. They likely will become much more like robots, guided by AI, and make independent judgments. These have the potential for significant medical progress that improves the treatment of patients. At the same time, the last 20 years suggest that robotic innovation will challenge medicine, the FDA and other regulators, lawmakers, and courts. In the future, regulators and patients should embrace genuine advances in robotic surgery but not be dazzled by these new machines’ luster (or potential for considerable profits).³⁰

The public may be wildly optimistic about the benefits without balancing the risks. The AI that runs them will be essentially invisible and constantly changing. Physicians and regulators must develop new techniques for assessing and controlling the software. Real surgical robots require rigorous testing, cautious promotion, disciplined use, and perpetual review. ●

CASE Patient wants to reduce her risk of cesarean delivery (CD)

A 30-year-old primigravid woman expresses concern about her increased risk for CD as a Black woman. She has been reading in the news about the increased risks of CD and birth complications, and she asks what she can do to decrease her risk of having a CD.

What is the problem?

Recently, attention has been called to the stark racial disparities in severe maternal morbidity and mortality. Cesarean delivery rates illustrate an area in obstetric management in which racial disparities exist. It is well known that morbidity associated with CD is much higher than morbidity associated with vaginal delivery, which begs the question of whether disparities in mode of delivery may play a role in the disparity in maternal morbidity and mortality.

In the United States, 32% of all births between 2018 and 2020 were by CD. However, only 31% of White women delivered via CD as compared with 36% of Black women and 33% of Asian women.¹ In 2021, the primary CD rates were 26% for Black women, 24% for Asian women, 21% for Hispanic women, and 22% for White women.² This racial disparity, particularly between Black and White women, has been seen across nulliparous, term, singleton, vertex (NTSV) groups as well as multiparous women with prior vaginal delivery.^3,4 The disparity persists after adjusting for risk factors.

A secondary analysis of groups deemed at low risk for CD within the ARRIVE trial study group reported the adjusted relative risk of CD birth for Black women as 1.21 (95% confidence interval [CI], 1.03–1.42) compared with White women and 1.26 (95% CI, 1.08–1.46) for Hispanic women.⁵ The investigators estimated that this accounted for 15% of excess maternal morbidity.⁵ These studies also have shown that a disparity exists in indication for CD, with Black women more likely to have a CD for the diagnosis of nonreassuring fetal tracing while White women are more likely to have a CD for failure to progress.

Patients who undergo CD are less likely to breastfeed, and they have a more difficult recovery, increased risks of infection, thromboembolic events, and increased risks for future pregnancy. Along with increased focus on racial disparities in obstetrics outcomes within the medical community, patients also have become more attuned to these racial disparities in maternal morbidity as this has increasingly become a topic of focus within the mainstream media.

What is behind differences in mode of delivery?

The drivers of racial inequities in mode of delivery remain unclear. One might question whether increased prevalence of morbidities in pregnancy, such as diabetes and hypertension, in minority women might influence the disparity in CD. However, the disparity persists in studies of low-risk women and in studies that statistically adjust for factors that include preeclampsia, obesity, diabetes, and fetal growth restriction, which argues that maternal morbidity alone is not responsible for the differences observed.

Race is a social construct, and as such there is no biologically plausible explanation for the racial disparities in CD rates. Differences in health outcomes should be considered a result of the impact of racism. Disparities can be influenced by patient level, provider level, and systemic level factors.⁶ Provider biases have a negative impact on care for minority groups and they influence disparities in health care.⁷ The subjectivity involved in diagnoses of nonreassuring fetal tracing as an indication for CD creates an opportunity for implicit biases and discrimination to enter decision-making for indications for CD. Furthermore, no differences have been seen in Apgar score or admission to the neonatal intensive care unit in studies where indication of nonreassuring fetal heart tracing drove the disparity for CD.⁵

A study that retrospectively compared labor management strategies intended to reduce CD rates, such as application of guidelines for failed induction of labor, arrest of dilation, arrest of descent, nonreassuring fetus status, or cervical ripening, did not observe differential use of labor management strategies intended to reduce CD rate.⁸ By contrast, Hamm and colleagues observed that implementation of a standardized induction protocol was associated with a decreased CD rate among Black women but not non-Black women and the standardized protocol was associated with a decrease in the racial disparity in CD.⁹ A theory behind their findings is that provider bias is less when there is implementation of a standardized protocol, algorithm, or guidelines, which in turn reduces disparity in mode of delivery.

Clearly, more research is needed for the mechanisms behind inequities in mode of delivery and the influence of provider factors. Future studies also are needed to evaluate how patient level factors, including belief systems and culture preferences, and how system level factors, such as access to prenatal care and the health system processes, are associated with CD rates.

Next steps

While the mechanisms that drive the disparities in CD rate and indication may remain unclear, there are potential areas of intervention to decrease CD rates among minority and Black women.

Continuous support from a doula or layperson has been shown to decrease rates of cesarean birth,^10,11 and evidence indicates that minority women are interested in doula support but are less likely than White women to have access to doula care.¹² Programs that provide doula support for Black women are an intervention that would increase access to support and advocacy during labor for Black women.

CASE Patient wants to reduce her risk of cesarean delivery (CD)

A 30-year-old primigravid woman expresses concern about her increased risk for CD as a Black woman. She has been reading in the news about the increased risks of CD and birth complications, and she asks what she can do to decrease her risk of having a CD.

What is the problem?

Recently, attention has been called to the stark racial disparities in severe maternal morbidity and mortality. Cesarean delivery rates illustrate an area in obstetric management in which racial disparities exist. It is well known that morbidity associated with CD is much higher than morbidity associated with vaginal delivery, which begs the question of whether disparities in mode of delivery may play a role in the disparity in maternal morbidity and mortality.

In the United States, 32% of all births between 2018 and 2020 were by CD. However, only 31% of White women delivered via CD as compared with 36% of Black women and 33% of Asian women.¹ In 2021, the primary CD rates were 26% for Black women, 24% for Asian women, 21% for Hispanic women, and 22% for White women.² This racial disparity, particularly between Black and White women, has been seen across nulliparous, term, singleton, vertex (NTSV) groups as well as multiparous women with prior vaginal delivery.^3,4 The disparity persists after adjusting for risk factors.

A secondary analysis of groups deemed at low risk for CD within the ARRIVE trial study group reported the adjusted relative risk of CD birth for Black women as 1.21 (95% confidence interval [CI], 1.03–1.42) compared with White women and 1.26 (95% CI, 1.08–1.46) for Hispanic women.⁵ The investigators estimated that this accounted for 15% of excess maternal morbidity.⁵ These studies also have shown that a disparity exists in indication for CD, with Black women more likely to have a CD for the diagnosis of nonreassuring fetal tracing while White women are more likely to have a CD for failure to progress.

Patients who undergo CD are less likely to breastfeed, and they have a more difficult recovery, increased risks of infection, thromboembolic events, and increased risks for future pregnancy. Along with increased focus on racial disparities in obstetrics outcomes within the medical community, patients also have become more attuned to these racial disparities in maternal morbidity as this has increasingly become a topic of focus within the mainstream media.

What is behind differences in mode of delivery?

The drivers of racial inequities in mode of delivery remain unclear. One might question whether increased prevalence of morbidities in pregnancy, such as diabetes and hypertension, in minority women might influence the disparity in CD. However, the disparity persists in studies of low-risk women and in studies that statistically adjust for factors that include preeclampsia, obesity, diabetes, and fetal growth restriction, which argues that maternal morbidity alone is not responsible for the differences observed.

Race is a social construct, and as such there is no biologically plausible explanation for the racial disparities in CD rates. Differences in health outcomes should be considered a result of the impact of racism. Disparities can be influenced by patient level, provider level, and systemic level factors.⁶ Provider biases have a negative impact on care for minority groups and they influence disparities in health care.⁷ The subjectivity involved in diagnoses of nonreassuring fetal tracing as an indication for CD creates an opportunity for implicit biases and discrimination to enter decision-making for indications for CD. Furthermore, no differences have been seen in Apgar score or admission to the neonatal intensive care unit in studies where indication of nonreassuring fetal heart tracing drove the disparity for CD.⁵

A study that retrospectively compared labor management strategies intended to reduce CD rates, such as application of guidelines for failed induction of labor, arrest of dilation, arrest of descent, nonreassuring fetus status, or cervical ripening, did not observe differential use of labor management strategies intended to reduce CD rate.⁸ By contrast, Hamm and colleagues observed that implementation of a standardized induction protocol was associated with a decreased CD rate among Black women but not non-Black women and the standardized protocol was associated with a decrease in the racial disparity in CD.⁹ A theory behind their findings is that provider bias is less when there is implementation of a standardized protocol, algorithm, or guidelines, which in turn reduces disparity in mode of delivery.

Clearly, more research is needed for the mechanisms behind inequities in mode of delivery and the influence of provider factors. Future studies also are needed to evaluate how patient level factors, including belief systems and culture preferences, and how system level factors, such as access to prenatal care and the health system processes, are associated with CD rates.

Next steps

While the mechanisms that drive the disparities in CD rate and indication may remain unclear, there are potential areas of intervention to decrease CD rates among minority and Black women.

Continuous support from a doula or layperson has been shown to decrease rates of cesarean birth,^10,11 and evidence indicates that minority women are interested in doula support but are less likely than White women to have access to doula care.¹² Programs that provide doula support for Black women are an intervention that would increase access to support and advocacy during labor for Black women.

CASE Patient wants to reduce her risk of cesarean delivery (CD)

A 30-year-old primigravid woman expresses concern about her increased risk for CD as a Black woman. She has been reading in the news about the increased risks of CD and birth complications, and she asks what she can do to decrease her risk of having a CD.

What is the problem?

Recently, attention has been called to the stark racial disparities in severe maternal morbidity and mortality. Cesarean delivery rates illustrate an area in obstetric management in which racial disparities exist. It is well known that morbidity associated with CD is much higher than morbidity associated with vaginal delivery, which begs the question of whether disparities in mode of delivery may play a role in the disparity in maternal morbidity and mortality.

In the United States, 32% of all births between 2018 and 2020 were by CD. However, only 31% of White women delivered via CD as compared with 36% of Black women and 33% of Asian women.¹ In 2021, the primary CD rates were 26% for Black women, 24% for Asian women, 21% for Hispanic women, and 22% for White women.² This racial disparity, particularly between Black and White women, has been seen across nulliparous, term, singleton, vertex (NTSV) groups as well as multiparous women with prior vaginal delivery.^3,4 The disparity persists after adjusting for risk factors.

A secondary analysis of groups deemed at low risk for CD within the ARRIVE trial study group reported the adjusted relative risk of CD birth for Black women as 1.21 (95% confidence interval [CI], 1.03–1.42) compared with White women and 1.26 (95% CI, 1.08–1.46) for Hispanic women.⁵ The investigators estimated that this accounted for 15% of excess maternal morbidity.⁵ These studies also have shown that a disparity exists in indication for CD, with Black women more likely to have a CD for the diagnosis of nonreassuring fetal tracing while White women are more likely to have a CD for failure to progress.

Patients who undergo CD are less likely to breastfeed, and they have a more difficult recovery, increased risks of infection, thromboembolic events, and increased risks for future pregnancy. Along with increased focus on racial disparities in obstetrics outcomes within the medical community, patients also have become more attuned to these racial disparities in maternal morbidity as this has increasingly become a topic of focus within the mainstream media.

What is behind differences in mode of delivery?

The drivers of racial inequities in mode of delivery remain unclear. One might question whether increased prevalence of morbidities in pregnancy, such as diabetes and hypertension, in minority women might influence the disparity in CD. However, the disparity persists in studies of low-risk women and in studies that statistically adjust for factors that include preeclampsia, obesity, diabetes, and fetal growth restriction, which argues that maternal morbidity alone is not responsible for the differences observed.

Race is a social construct, and as such there is no biologically plausible explanation for the racial disparities in CD rates. Differences in health outcomes should be considered a result of the impact of racism. Disparities can be influenced by patient level, provider level, and systemic level factors.⁶ Provider biases have a negative impact on care for minority groups and they influence disparities in health care.⁷ The subjectivity involved in diagnoses of nonreassuring fetal tracing as an indication for CD creates an opportunity for implicit biases and discrimination to enter decision-making for indications for CD. Furthermore, no differences have been seen in Apgar score or admission to the neonatal intensive care unit in studies where indication of nonreassuring fetal heart tracing drove the disparity for CD.⁵

A study that retrospectively compared labor management strategies intended to reduce CD rates, such as application of guidelines for failed induction of labor, arrest of dilation, arrest of descent, nonreassuring fetus status, or cervical ripening, did not observe differential use of labor management strategies intended to reduce CD rate.⁸ By contrast, Hamm and colleagues observed that implementation of a standardized induction protocol was associated with a decreased CD rate among Black women but not non-Black women and the standardized protocol was associated with a decrease in the racial disparity in CD.⁹ A theory behind their findings is that provider bias is less when there is implementation of a standardized protocol, algorithm, or guidelines, which in turn reduces disparity in mode of delivery.

Clearly, more research is needed for the mechanisms behind inequities in mode of delivery and the influence of provider factors. Future studies also are needed to evaluate how patient level factors, including belief systems and culture preferences, and how system level factors, such as access to prenatal care and the health system processes, are associated with CD rates.

Next steps

While the mechanisms that drive the disparities in CD rate and indication may remain unclear, there are potential areas of intervention to decrease CD rates among minority and Black women.

Continuous support from a doula or layperson has been shown to decrease rates of cesarean birth,^10,11 and evidence indicates that minority women are interested in doula support but are less likely than White women to have access to doula care.¹² Programs that provide doula support for Black women are an intervention that would increase access to support and advocacy during labor for Black women.

Hereditary alpha tryptasemia (HaT), an autosomal-dominant disorder of tryptase overproduction, was first described in 2014 by Lyons et al.¹ It has been associated with multiple dermatologic, allergic, gastrointestinal (GI) tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities. These multisystem concerns may include cutaneous flushing, chronic pruritus, urticaria, GI tract symptoms, arthralgia, and autonomic dysfunction.² The diverse symptoms and the recent discovery of HaT make recognition of this disorder challenging. Currently, it also is believed that HaT is associated with an elevated risk for anaphylaxis and is a biomarker for severe symptoms in disorders with increased mast cell burden such as mastocytosis.^3-5

Given the potential cutaneous manifestations and the fact that dermatologic symptoms may be the initial presentation of HaT, awareness and recognition of this condition by dermatologists are essential for diagnosis and treatment. This review summarizes the cutaneous presentations consistent with HaT and discusses various conditions that share overlapping dermatologic symptoms with HaT.

Background on HaT

Mast cells are known to secrete several vasoactive mediators including tryptase and histamine when activated by foreign substances, similar to IgE-mediated hypersensitivity reactions. In their baseline state, mast cells continuously secrete immature forms of tryptases called protryptases.⁶ These protryptases come in 2 forms: α and β. Although mature tryptase is acutely elevatedin anaphylaxis, persistently elevated total serum tryptase levels frequently are regarded as indicative of a systemic mast cell disorder such as systemic mastocytosis (SM).³ Despite the wide-ranging phenotype of HaT, all individuals with the disorder have an elevated basal serum tryptase level (>8 ng/mL). Hereditary alpha tryptasemia has been identified as another possible cause of persistently elevated levels.^2,6

Genetics and Epidemiology of HaT—The humantryptase locus at chromosome 16p13.3 is composed of 4 paralog genes: TPSG1, TPSB2, TPSAB1, and TPSD1.⁴ Only TPSAB1 encodes for α-tryptase, while both TPSB2 and TPSAB1 encode for β-tryptase.⁴ Hereditary alpha tryptasemia is an autosomal-dominant disorder resulting from a copy number increase in the α-tryptase encoding sequence within the TPSAB1 gene. Despite the wide-ranging phenotype of HaT, all individuals identified with the disorder have a basal serum tryptase level greater than 8 ng/mL, with mean (SD) levels of 15 (5) ng/mL and 24 (6) ng/mL with gene duplication and triplication, respectively (reference range, 0–11.4 ng/mL).^2,6 Hereditary alpha tryptasemia likely is common and largely undiagnosed, with a recently estimated prevalence of 5% in the United Kingdom⁷ and 5.6% in a cohort of 125 individuals from Italy, Slovenia, and the United States.⁵

Implications of Increased α-tryptase Levels—After an inciting stimulus, the active portions of α-protryptase and β-protryptase are secreted as tetramers by activated mast cells via degranulation. In vitro, β-tryptase homotetramers have been found to play a role in anaphylaxis, while α-homotetramers are nearly inactive.^8,9 Recently, however, it has been discovered that α2β2 tetramers also can form and do so in a higher ratio in individuals with increased α-tryptase–encoding gene copies, such as those with HaT.⁸ These heterotetramers exhibit unique properties compared with the homotetramers and may stimulate epidermal growth factor–like module-containing mucinlike hormone receptor 2 and protease-activated receptor 2 (PAR2). Epidermal growth factor–like module-containing mucinlike hormone receptor 2 activation likely contributes to vibratory urticaria in patients, while activation of PAR2 may have a range of clinical effects, including worsening asthma, inflammatory bowel disease, pruritus, and the exacerbation of dermal inflammation and hyperalgesia.^8,10 Thus, α- and β-tryptase tetramers can be considered mediators that may influence the severity of disorders in which mast cells are naturally prevalent and likely contribute to the phenotype of those with HaT.⁷ Furthermore, these characteristics have been shown to potentially increase in severity with increasing tryptase levels and with increased TPSAB1 duplications.^1,2 In contrast, more than 25% of the population is deficient in α-tryptase without known deleterious effects.⁵

Cutaneous Manifestations of HaT

A case series reported by Lyons et al¹ in 2014 detailed persistent elevated basal serum tryptase levels in 9 families with an autosomal-dominant pattern of inheritance. In this cohort, 31 of 33 (94%) affected individuals had a history of atopic dermatitis (AD), and 26 of 33 (79%) affected individuals reported symptoms consistent with mast cell degranulation, including urticaria; flushing; and/or crampy abdominal pain unprovoked or triggered by heat, exercise, vibration, stress, certain foods, or minor physical stimulation.¹ A later report by Lyons et al² in 2016 identified the TPSAB1 α-tryptase–encoding sequence copy number increase as the causative entity for HaT by examining a group of 96 patients from 35 families with frequent recurrent cutaneous flushing and pruritus, sometimes associated with urticaria and sleep disruption. Flushing and pruritus were found in 45% (33/73) of those with a TPSAB1 duplication and 80% (12/15) of those with a triplication (P=.022), suggesting a gene dose effect regarding α-tryptase encoding sequence copy number and these symptoms.²

A 2019 study further explored the clinical finding of urticaria in patients with HaT by specifically examining if vibration-induced urticaria was affected by TPSAB1 gene dosage.⁸ A cohort of 56 volunteers—35 healthy and 21 with HaT—underwent tryptase genotyping and cutaneous vibratory challenge. The presence of TPSAB1 was significantly correlated with induction of vibration-induced urticaria (P<.01), as the severity and prevalence of the urticarial response increased along with α- and β-tryptase gene ratios.⁸

Urticaria and angioedema also were seen in 51% (36/70) of patients in a cohort of HaT patients in the United Kingdom, in which 41% (29/70) also had skin flushing. In contrast to prior studies, these manifestations were not more common in patients with gene triplications or quintuplications than those with duplications.⁷ In another recent retrospective evaluation conducted at Brigham and Women’s Hospital (Boston, Massachusetts)(N=101), 80% of patients aged 4 to 85 years with confirmed diagnoses of HaT had skin manifestations such as urticaria, flushing, and pruritus.⁴

HaT and Mast Cell Activation Syndrome—In 2019, a Mast Cell Disorders Committee Work Group Report outlined recommendations for diagnosing and treating primary mast cell activation syndrome (MCAS), a disorder in which mast cells seem to be more easily activated. Mast cell activation syndrome is defined as a primary clinical condition in which there are episodic signs and symptoms of systemic anaphylaxis (Table) concurrently affecting at least 2 organ systems, resulting from secreted mast cell mediators.^9,11 The 2019 report also touched on clinical criteria that lack precision for diagnosing MCAS yet are in use, including dermographism and several types of rashes.⁹ Episode triggers frequent in MCAS include hot water, alcohol, stress, exercise, infection, hormonal changes, and physical stimuli.

Hereditary alpha tryptasemia has been suggested to be a risk factor for MCAS, which also can be associated with SM and clonal MCAS.⁹ Patients with MCAS should be tested for increased α-tryptase gene copy number given the overlap in symptoms, the likely predisposition of those with HaT to develop MCAS, and the fact that these patients could be at an increased risk for anaphylaxis.^4,7,9,11 However, the clinical phenotype for HaT includes allergic disorders affecting the skin as well as neuropsychiatric and connective tissue abnormalities that are distinctive from MCAS. Although HaT may be considered a heritable risk factor for MCAS, MCAS is only 1 potential phenotype associated with HaT.⁹

Implications of HaT

Hereditary alpha tryptasemia should be considered in all patients with basal tryptase levels greater than 8 ng/mL. Cutaneous symptoms are among the most common presentations for individuals with HaT and can include AD, chronic or episodic urticaria, pruritus, flushing, and angioedema. However, HaT is unique because of the coupling of these common dermatologic findings with other abnormalities, including abdominal pain and diarrhea, hypermobile joints, and autonomic dysfunction. Patients with HaT also may manifest psychiatric concerns of anxiety, depression, and chronic pain, all of which have been linked to this disorder.

It is unclear in HaT if the presence of extra-allelic copies of tryptase in an individual is directly pathogenic. The effects of increased basal tryptase and α2β2 tetramers have been shown to likely be responsible for some of the clinical features in these individuals but also may magnify other individual underlying disease(s) or diathesis in which mast cells are naturally abundant.⁸ In the skin, this increased mast cell activation and subsequent histamine release frequently are visible as dermatographia and urticaria. However, mast cell numbers also are known to be increased in both psoriatic and AD skin lesions,¹² thus severe presentation of these diseases in conjunction with the other symptoms associated with mast cell activation should prompt suspicion for HaT.

Effects of HaT on Other Cutaneous Disease—Given the increase of mast cells in AD skin lesions and fact that 94% of patients in the 2014 Lyons et al¹ study cited a history of AD, HaT may be a risk factor in the development of AD. Interestingly, in addition to the increased mast cells in AD lesions, PAR2+ nerve fibers also are increased in AD lesions and have been implicated in the nonhistaminergic pruritus experienced by patients with AD.¹² Thus, given the proposed propensity for α2β2 tetramers to activate PAR2, it is possible this mechanism may contribute to severe pruritus in individuals with AD and concurrent HaT, as those with HaT express increased α2β2 tetramers. However, no study to date has directly compared AD symptoms in patients with concurrent HaT vs patients without it. Further research is needed on how HaT impacts other allergic and inflammatory skin diseases such as AD and psoriasis, but one may reasonably consider HaT when treating chronic inflammatory skin diseases refractory to typical interventions and/or severe presentations. Although HaT is an autosomal-dominant disorder, it is not detected by standard whole exome sequencing or microarrays. A commercial test is available, utilizing a buccal swab to test for TPSAB1 copy number.

HaT and Mast Cell Disorders—When evaluating someone with suspected HaT, it is important to screen for other symptoms of mast cell activation. For instance, in the GI tract increased mast cell activation results in activation of motor neurons and nociceptors and increases secretion and peristalsis with consequent bloating, abdominal pain, and diarrhea.¹⁰ Likewise, tryptase also has neuromodulatory effects that amplify the perception of pain and are likely responsible for the feelings of hyperalgesia reported in patients with HaT.¹³

There is substantial overlap in the clinical pictures of HaT and MCAS, and HaT is considered a heritable risk factor for MCAS. Consequently, any patient undergoing workup for MCAS also should be tested for HaT. Although HaT is associated with consistently elevated tryptase, MCAS is episodic in nature, and an increase in tryptase levels of at least 20% plus 2 ng/mL from baseline only in the presence of other symptoms reflective of mast cell activation (Table) is a prerequisite for diagnosis.⁹ Chronic signs and symptoms of atopy, chronic urticaria, and severe asthma are not indicative of MCAS but are frequently seen in HaT.

Another cause of persistently elevated tryptase levels is SM. Systemic mastocytosis is defined by aberrant clonal mast cell expansion and systemic involvement¹¹ and can cause persistent symptoms, unlike MCAS alone. However, SM also can be associated with MCAS.⁹ Notably, a baseline serum tryptase level greater than 20 ng/mL—much higher than the threshold of greater than 8 ng/mL for suspicion of HaT—is seen in 75% of SM cases and is part of the minor diagnostic criteria for the disease.^9,11 However, the 2016 study identifying increased TPSAB1 α-tryptase–encoding sequences as the causative entity for HaT by Lyons et al² found the average (SD) basal serum tryptase level in individuals with α-tryptase–encoding sequence duplications to be 15 (5) ng/mL and 24 (6) ng/mL in those with triplications. Thus, there likely is no threshold for elevated baseline tryptase levels that would indicate SM over HaT as a more likely diagnosis. However, SM will present with new persistently elevated tryptase levels, whereas the elevation in HaT is believed to be lifelong.⁵ Also in contrast to HaT, SM can present with liver, spleen, and lymph node involvement; bone sclerosis; and cytopenia.^11,14

Mastocytosis is much rarer than HaT, with an estimated prevalence of 9 cases per 100,000 individuals in the United States.¹¹ Although HaT diagnostic testing is noninvasive, SM requires a bone marrow biopsy for definitive diagnosis. Given the likely much higher prevalence of HaT than SM and the patient burden of a bone marrow biopsy, HaT should be considered before proceeding with a bone marrow biopsy to evaluate for SM when a patient presents with persistent systemic symptoms of mast cell activation and elevated baseline tryptase levels. Furthermore, it also would be prudent to test for HaT in patients with known SM, as a cohort study by Lyons et al⁵ indicated that HaT is likely more common in those with SM (12.2% [10/82] of cohort with known SM vs 5.3% of 398 controls), and patients with concurrent SM and HaT were at a higher risk for severe anaphylaxis (RR=9.5; P=.007).

Studies thus far surrounding HaT have not evaluated timing of initial symptom onset or age of initial presentation for HaT. Furthermore, there is no guarantee that those with increased TPSAB1 copy number will be symptomatic, as there have been reports of asymptomatic individuals with HaT who had basal serum levels greater than 8 ng/mL.⁷ As research into HaT continues and larger cohorts are evaluated, questions surrounding timing of symptom onset and various factors that may make someone more likely to display a particular phenotype will be answered.

Treatment—Long-term prognosis for individuals with HaT is largely unknown. Unfortunately, there are limited data to support a single effective treatment strategy for managing HaT, and treatment has varied based on predominant symptoms. For cutaneous and GI tract symptoms, trials of maximal H₁ and H₂ antihistamines twice daily have been recommended.⁴ Omalizumab was reported to improve chronic urticaria in 3 of 3 patients, showing potential promise as a treatment.⁴ Mast cell stabilizers, such as oral cromolyn, have been used for severe GI symptoms, while some patients also have reported improvement with oral ketotifen.⁶ Other medications, such as tricyclic antidepressants, clemastine fumarate, and gabapentin, have been beneficial anecdotally.⁶ Given the lack of harmful effects seen in individuals who are α-tryptase deficient, α-tryptase inhibition is an intriguing target for future therapies.

Conclusion

Patients who present with a constellation of dermatologic, allergic, GI tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities consistent with HaT may receive a prompt diagnosis if the association is recognized. The full relationship between HaT and other chronic dermatologic disorders is still unknown. Ultimately, heightened interest and research into HaT will lead to more treatment options available for affected patients.

Hereditary alpha tryptasemia (HaT), an autosomal-dominant disorder of tryptase overproduction, was first described in 2014 by Lyons et al.¹ It has been associated with multiple dermatologic, allergic, gastrointestinal (GI) tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities. These multisystem concerns may include cutaneous flushing, chronic pruritus, urticaria, GI tract symptoms, arthralgia, and autonomic dysfunction.² The diverse symptoms and the recent discovery of HaT make recognition of this disorder challenging. Currently, it also is believed that HaT is associated with an elevated risk for anaphylaxis and is a biomarker for severe symptoms in disorders with increased mast cell burden such as mastocytosis.^3-5

Given the potential cutaneous manifestations and the fact that dermatologic symptoms may be the initial presentation of HaT, awareness and recognition of this condition by dermatologists are essential for diagnosis and treatment. This review summarizes the cutaneous presentations consistent with HaT and discusses various conditions that share overlapping dermatologic symptoms with HaT.

Background on HaT

Mast cells are known to secrete several vasoactive mediators including tryptase and histamine when activated by foreign substances, similar to IgE-mediated hypersensitivity reactions. In their baseline state, mast cells continuously secrete immature forms of tryptases called protryptases.⁶ These protryptases come in 2 forms: α and β. Although mature tryptase is acutely elevatedin anaphylaxis, persistently elevated total serum tryptase levels frequently are regarded as indicative of a systemic mast cell disorder such as systemic mastocytosis (SM).³ Despite the wide-ranging phenotype of HaT, all individuals with the disorder have an elevated basal serum tryptase level (>8 ng/mL). Hereditary alpha tryptasemia has been identified as another possible cause of persistently elevated levels.^2,6

Genetics and Epidemiology of HaT—The humantryptase locus at chromosome 16p13.3 is composed of 4 paralog genes: TPSG1, TPSB2, TPSAB1, and TPSD1.⁴ Only TPSAB1 encodes for α-tryptase, while both TPSB2 and TPSAB1 encode for β-tryptase.⁴ Hereditary alpha tryptasemia is an autosomal-dominant disorder resulting from a copy number increase in the α-tryptase encoding sequence within the TPSAB1 gene. Despite the wide-ranging phenotype of HaT, all individuals identified with the disorder have a basal serum tryptase level greater than 8 ng/mL, with mean (SD) levels of 15 (5) ng/mL and 24 (6) ng/mL with gene duplication and triplication, respectively (reference range, 0–11.4 ng/mL).^2,6 Hereditary alpha tryptasemia likely is common and largely undiagnosed, with a recently estimated prevalence of 5% in the United Kingdom⁷ and 5.6% in a cohort of 125 individuals from Italy, Slovenia, and the United States.⁵

Implications of Increased α-tryptase Levels—After an inciting stimulus, the active portions of α-protryptase and β-protryptase are secreted as tetramers by activated mast cells via degranulation. In vitro, β-tryptase homotetramers have been found to play a role in anaphylaxis, while α-homotetramers are nearly inactive.^8,9 Recently, however, it has been discovered that α2β2 tetramers also can form and do so in a higher ratio in individuals with increased α-tryptase–encoding gene copies, such as those with HaT.⁸ These heterotetramers exhibit unique properties compared with the homotetramers and may stimulate epidermal growth factor–like module-containing mucinlike hormone receptor 2 and protease-activated receptor 2 (PAR2). Epidermal growth factor–like module-containing mucinlike hormone receptor 2 activation likely contributes to vibratory urticaria in patients, while activation of PAR2 may have a range of clinical effects, including worsening asthma, inflammatory bowel disease, pruritus, and the exacerbation of dermal inflammation and hyperalgesia.^8,10 Thus, α- and β-tryptase tetramers can be considered mediators that may influence the severity of disorders in which mast cells are naturally prevalent and likely contribute to the phenotype of those with HaT.⁷ Furthermore, these characteristics have been shown to potentially increase in severity with increasing tryptase levels and with increased TPSAB1 duplications.^1,2 In contrast, more than 25% of the population is deficient in α-tryptase without known deleterious effects.⁵

Cutaneous Manifestations of HaT

A case series reported by Lyons et al¹ in 2014 detailed persistent elevated basal serum tryptase levels in 9 families with an autosomal-dominant pattern of inheritance. In this cohort, 31 of 33 (94%) affected individuals had a history of atopic dermatitis (AD), and 26 of 33 (79%) affected individuals reported symptoms consistent with mast cell degranulation, including urticaria; flushing; and/or crampy abdominal pain unprovoked or triggered by heat, exercise, vibration, stress, certain foods, or minor physical stimulation.¹ A later report by Lyons et al² in 2016 identified the TPSAB1 α-tryptase–encoding sequence copy number increase as the causative entity for HaT by examining a group of 96 patients from 35 families with frequent recurrent cutaneous flushing and pruritus, sometimes associated with urticaria and sleep disruption. Flushing and pruritus were found in 45% (33/73) of those with a TPSAB1 duplication and 80% (12/15) of those with a triplication (P=.022), suggesting a gene dose effect regarding α-tryptase encoding sequence copy number and these symptoms.²

A 2019 study further explored the clinical finding of urticaria in patients with HaT by specifically examining if vibration-induced urticaria was affected by TPSAB1 gene dosage.⁸ A cohort of 56 volunteers—35 healthy and 21 with HaT—underwent tryptase genotyping and cutaneous vibratory challenge. The presence of TPSAB1 was significantly correlated with induction of vibration-induced urticaria (P<.01), as the severity and prevalence of the urticarial response increased along with α- and β-tryptase gene ratios.⁸

Urticaria and angioedema also were seen in 51% (36/70) of patients in a cohort of HaT patients in the United Kingdom, in which 41% (29/70) also had skin flushing. In contrast to prior studies, these manifestations were not more common in patients with gene triplications or quintuplications than those with duplications.⁷ In another recent retrospective evaluation conducted at Brigham and Women’s Hospital (Boston, Massachusetts)(N=101), 80% of patients aged 4 to 85 years with confirmed diagnoses of HaT had skin manifestations such as urticaria, flushing, and pruritus.⁴

HaT and Mast Cell Activation Syndrome—In 2019, a Mast Cell Disorders Committee Work Group Report outlined recommendations for diagnosing and treating primary mast cell activation syndrome (MCAS), a disorder in which mast cells seem to be more easily activated. Mast cell activation syndrome is defined as a primary clinical condition in which there are episodic signs and symptoms of systemic anaphylaxis (Table) concurrently affecting at least 2 organ systems, resulting from secreted mast cell mediators.^9,11 The 2019 report also touched on clinical criteria that lack precision for diagnosing MCAS yet are in use, including dermographism and several types of rashes.⁹ Episode triggers frequent in MCAS include hot water, alcohol, stress, exercise, infection, hormonal changes, and physical stimuli.

Hereditary alpha tryptasemia has been suggested to be a risk factor for MCAS, which also can be associated with SM and clonal MCAS.⁹ Patients with MCAS should be tested for increased α-tryptase gene copy number given the overlap in symptoms, the likely predisposition of those with HaT to develop MCAS, and the fact that these patients could be at an increased risk for anaphylaxis.^4,7,9,11 However, the clinical phenotype for HaT includes allergic disorders affecting the skin as well as neuropsychiatric and connective tissue abnormalities that are distinctive from MCAS. Although HaT may be considered a heritable risk factor for MCAS, MCAS is only 1 potential phenotype associated with HaT.⁹

Implications of HaT

Hereditary alpha tryptasemia should be considered in all patients with basal tryptase levels greater than 8 ng/mL. Cutaneous symptoms are among the most common presentations for individuals with HaT and can include AD, chronic or episodic urticaria, pruritus, flushing, and angioedema. However, HaT is unique because of the coupling of these common dermatologic findings with other abnormalities, including abdominal pain and diarrhea, hypermobile joints, and autonomic dysfunction. Patients with HaT also may manifest psychiatric concerns of anxiety, depression, and chronic pain, all of which have been linked to this disorder.

It is unclear in HaT if the presence of extra-allelic copies of tryptase in an individual is directly pathogenic. The effects of increased basal tryptase and α2β2 tetramers have been shown to likely be responsible for some of the clinical features in these individuals but also may magnify other individual underlying disease(s) or diathesis in which mast cells are naturally abundant.⁸ In the skin, this increased mast cell activation and subsequent histamine release frequently are visible as dermatographia and urticaria. However, mast cell numbers also are known to be increased in both psoriatic and AD skin lesions,¹² thus severe presentation of these diseases in conjunction with the other symptoms associated with mast cell activation should prompt suspicion for HaT.

Effects of HaT on Other Cutaneous Disease—Given the increase of mast cells in AD skin lesions and fact that 94% of patients in the 2014 Lyons et al¹ study cited a history of AD, HaT may be a risk factor in the development of AD. Interestingly, in addition to the increased mast cells in AD lesions, PAR2+ nerve fibers also are increased in AD lesions and have been implicated in the nonhistaminergic pruritus experienced by patients with AD.¹² Thus, given the proposed propensity for α2β2 tetramers to activate PAR2, it is possible this mechanism may contribute to severe pruritus in individuals with AD and concurrent HaT, as those with HaT express increased α2β2 tetramers. However, no study to date has directly compared AD symptoms in patients with concurrent HaT vs patients without it. Further research is needed on how HaT impacts other allergic and inflammatory skin diseases such as AD and psoriasis, but one may reasonably consider HaT when treating chronic inflammatory skin diseases refractory to typical interventions and/or severe presentations. Although HaT is an autosomal-dominant disorder, it is not detected by standard whole exome sequencing or microarrays. A commercial test is available, utilizing a buccal swab to test for TPSAB1 copy number.

HaT and Mast Cell Disorders—When evaluating someone with suspected HaT, it is important to screen for other symptoms of mast cell activation. For instance, in the GI tract increased mast cell activation results in activation of motor neurons and nociceptors and increases secretion and peristalsis with consequent bloating, abdominal pain, and diarrhea.¹⁰ Likewise, tryptase also has neuromodulatory effects that amplify the perception of pain and are likely responsible for the feelings of hyperalgesia reported in patients with HaT.¹³

There is substantial overlap in the clinical pictures of HaT and MCAS, and HaT is considered a heritable risk factor for MCAS. Consequently, any patient undergoing workup for MCAS also should be tested for HaT. Although HaT is associated with consistently elevated tryptase, MCAS is episodic in nature, and an increase in tryptase levels of at least 20% plus 2 ng/mL from baseline only in the presence of other symptoms reflective of mast cell activation (Table) is a prerequisite for diagnosis.⁹ Chronic signs and symptoms of atopy, chronic urticaria, and severe asthma are not indicative of MCAS but are frequently seen in HaT.

Another cause of persistently elevated tryptase levels is SM. Systemic mastocytosis is defined by aberrant clonal mast cell expansion and systemic involvement¹¹ and can cause persistent symptoms, unlike MCAS alone. However, SM also can be associated with MCAS.⁹ Notably, a baseline serum tryptase level greater than 20 ng/mL—much higher than the threshold of greater than 8 ng/mL for suspicion of HaT—is seen in 75% of SM cases and is part of the minor diagnostic criteria for the disease.^9,11 However, the 2016 study identifying increased TPSAB1 α-tryptase–encoding sequences as the causative entity for HaT by Lyons et al² found the average (SD) basal serum tryptase level in individuals with α-tryptase–encoding sequence duplications to be 15 (5) ng/mL and 24 (6) ng/mL in those with triplications. Thus, there likely is no threshold for elevated baseline tryptase levels that would indicate SM over HaT as a more likely diagnosis. However, SM will present with new persistently elevated tryptase levels, whereas the elevation in HaT is believed to be lifelong.⁵ Also in contrast to HaT, SM can present with liver, spleen, and lymph node involvement; bone sclerosis; and cytopenia.^11,14

Mastocytosis is much rarer than HaT, with an estimated prevalence of 9 cases per 100,000 individuals in the United States.¹¹ Although HaT diagnostic testing is noninvasive, SM requires a bone marrow biopsy for definitive diagnosis. Given the likely much higher prevalence of HaT than SM and the patient burden of a bone marrow biopsy, HaT should be considered before proceeding with a bone marrow biopsy to evaluate for SM when a patient presents with persistent systemic symptoms of mast cell activation and elevated baseline tryptase levels. Furthermore, it also would be prudent to test for HaT in patients with known SM, as a cohort study by Lyons et al⁵ indicated that HaT is likely more common in those with SM (12.2% [10/82] of cohort with known SM vs 5.3% of 398 controls), and patients with concurrent SM and HaT were at a higher risk for severe anaphylaxis (RR=9.5; P=.007).

Studies thus far surrounding HaT have not evaluated timing of initial symptom onset or age of initial presentation for HaT. Furthermore, there is no guarantee that those with increased TPSAB1 copy number will be symptomatic, as there have been reports of asymptomatic individuals with HaT who had basal serum levels greater than 8 ng/mL.⁷ As research into HaT continues and larger cohorts are evaluated, questions surrounding timing of symptom onset and various factors that may make someone more likely to display a particular phenotype will be answered.

Treatment—Long-term prognosis for individuals with HaT is largely unknown. Unfortunately, there are limited data to support a single effective treatment strategy for managing HaT, and treatment has varied based on predominant symptoms. For cutaneous and GI tract symptoms, trials of maximal H₁ and H₂ antihistamines twice daily have been recommended.⁴ Omalizumab was reported to improve chronic urticaria in 3 of 3 patients, showing potential promise as a treatment.⁴ Mast cell stabilizers, such as oral cromolyn, have been used for severe GI symptoms, while some patients also have reported improvement with oral ketotifen.⁶ Other medications, such as tricyclic antidepressants, clemastine fumarate, and gabapentin, have been beneficial anecdotally.⁶ Given the lack of harmful effects seen in individuals who are α-tryptase deficient, α-tryptase inhibition is an intriguing target for future therapies.

Conclusion

Patients who present with a constellation of dermatologic, allergic, GI tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities consistent with HaT may receive a prompt diagnosis if the association is recognized. The full relationship between HaT and other chronic dermatologic disorders is still unknown. Ultimately, heightened interest and research into HaT will lead to more treatment options available for affected patients.

Hereditary alpha tryptasemia (HaT), an autosomal-dominant disorder of tryptase overproduction, was first described in 2014 by Lyons et al.¹ It has been associated with multiple dermatologic, allergic, gastrointestinal (GI) tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities. These multisystem concerns may include cutaneous flushing, chronic pruritus, urticaria, GI tract symptoms, arthralgia, and autonomic dysfunction.² The diverse symptoms and the recent discovery of HaT make recognition of this disorder challenging. Currently, it also is believed that HaT is associated with an elevated risk for anaphylaxis and is a biomarker for severe symptoms in disorders with increased mast cell burden such as mastocytosis.^3-5

Given the potential cutaneous manifestations and the fact that dermatologic symptoms may be the initial presentation of HaT, awareness and recognition of this condition by dermatologists are essential for diagnosis and treatment. This review summarizes the cutaneous presentations consistent with HaT and discusses various conditions that share overlapping dermatologic symptoms with HaT.

Background on HaT

Mast cells are known to secrete several vasoactive mediators including tryptase and histamine when activated by foreign substances, similar to IgE-mediated hypersensitivity reactions. In their baseline state, mast cells continuously secrete immature forms of tryptases called protryptases.⁶ These protryptases come in 2 forms: α and β. Although mature tryptase is acutely elevatedin anaphylaxis, persistently elevated total serum tryptase levels frequently are regarded as indicative of a systemic mast cell disorder such as systemic mastocytosis (SM).³ Despite the wide-ranging phenotype of HaT, all individuals with the disorder have an elevated basal serum tryptase level (>8 ng/mL). Hereditary alpha tryptasemia has been identified as another possible cause of persistently elevated levels.^2,6

Genetics and Epidemiology of HaT—The humantryptase locus at chromosome 16p13.3 is composed of 4 paralog genes: TPSG1, TPSB2, TPSAB1, and TPSD1.⁴ Only TPSAB1 encodes for α-tryptase, while both TPSB2 and TPSAB1 encode for β-tryptase.⁴ Hereditary alpha tryptasemia is an autosomal-dominant disorder resulting from a copy number increase in the α-tryptase encoding sequence within the TPSAB1 gene. Despite the wide-ranging phenotype of HaT, all individuals identified with the disorder have a basal serum tryptase level greater than 8 ng/mL, with mean (SD) levels of 15 (5) ng/mL and 24 (6) ng/mL with gene duplication and triplication, respectively (reference range, 0–11.4 ng/mL).^2,6 Hereditary alpha tryptasemia likely is common and largely undiagnosed, with a recently estimated prevalence of 5% in the United Kingdom⁷ and 5.6% in a cohort of 125 individuals from Italy, Slovenia, and the United States.⁵

Implications of Increased α-tryptase Levels—After an inciting stimulus, the active portions of α-protryptase and β-protryptase are secreted as tetramers by activated mast cells via degranulation. In vitro, β-tryptase homotetramers have been found to play a role in anaphylaxis, while α-homotetramers are nearly inactive.^8,9 Recently, however, it has been discovered that α2β2 tetramers also can form and do so in a higher ratio in individuals with increased α-tryptase–encoding gene copies, such as those with HaT.⁸ These heterotetramers exhibit unique properties compared with the homotetramers and may stimulate epidermal growth factor–like module-containing mucinlike hormone receptor 2 and protease-activated receptor 2 (PAR2). Epidermal growth factor–like module-containing mucinlike hormone receptor 2 activation likely contributes to vibratory urticaria in patients, while activation of PAR2 may have a range of clinical effects, including worsening asthma, inflammatory bowel disease, pruritus, and the exacerbation of dermal inflammation and hyperalgesia.^8,10 Thus, α- and β-tryptase tetramers can be considered mediators that may influence the severity of disorders in which mast cells are naturally prevalent and likely contribute to the phenotype of those with HaT.⁷ Furthermore, these characteristics have been shown to potentially increase in severity with increasing tryptase levels and with increased TPSAB1 duplications.^1,2 In contrast, more than 25% of the population is deficient in α-tryptase without known deleterious effects.⁵

Cutaneous Manifestations of HaT

A case series reported by Lyons et al¹ in 2014 detailed persistent elevated basal serum tryptase levels in 9 families with an autosomal-dominant pattern of inheritance. In this cohort, 31 of 33 (94%) affected individuals had a history of atopic dermatitis (AD), and 26 of 33 (79%) affected individuals reported symptoms consistent with mast cell degranulation, including urticaria; flushing; and/or crampy abdominal pain unprovoked or triggered by heat, exercise, vibration, stress, certain foods, or minor physical stimulation.¹ A later report by Lyons et al² in 2016 identified the TPSAB1 α-tryptase–encoding sequence copy number increase as the causative entity for HaT by examining a group of 96 patients from 35 families with frequent recurrent cutaneous flushing and pruritus, sometimes associated with urticaria and sleep disruption. Flushing and pruritus were found in 45% (33/73) of those with a TPSAB1 duplication and 80% (12/15) of those with a triplication (P=.022), suggesting a gene dose effect regarding α-tryptase encoding sequence copy number and these symptoms.²

A 2019 study further explored the clinical finding of urticaria in patients with HaT by specifically examining if vibration-induced urticaria was affected by TPSAB1 gene dosage.⁸ A cohort of 56 volunteers—35 healthy and 21 with HaT—underwent tryptase genotyping and cutaneous vibratory challenge. The presence of TPSAB1 was significantly correlated with induction of vibration-induced urticaria (P<.01), as the severity and prevalence of the urticarial response increased along with α- and β-tryptase gene ratios.⁸

Urticaria and angioedema also were seen in 51% (36/70) of patients in a cohort of HaT patients in the United Kingdom, in which 41% (29/70) also had skin flushing. In contrast to prior studies, these manifestations were not more common in patients with gene triplications or quintuplications than those with duplications.⁷ In another recent retrospective evaluation conducted at Brigham and Women’s Hospital (Boston, Massachusetts)(N=101), 80% of patients aged 4 to 85 years with confirmed diagnoses of HaT had skin manifestations such as urticaria, flushing, and pruritus.⁴

HaT and Mast Cell Activation Syndrome—In 2019, a Mast Cell Disorders Committee Work Group Report outlined recommendations for diagnosing and treating primary mast cell activation syndrome (MCAS), a disorder in which mast cells seem to be more easily activated. Mast cell activation syndrome is defined as a primary clinical condition in which there are episodic signs and symptoms of systemic anaphylaxis (Table) concurrently affecting at least 2 organ systems, resulting from secreted mast cell mediators.^9,11 The 2019 report also touched on clinical criteria that lack precision for diagnosing MCAS yet are in use, including dermographism and several types of rashes.⁹ Episode triggers frequent in MCAS include hot water, alcohol, stress, exercise, infection, hormonal changes, and physical stimuli.

Hereditary alpha tryptasemia has been suggested to be a risk factor for MCAS, which also can be associated with SM and clonal MCAS.⁹ Patients with MCAS should be tested for increased α-tryptase gene copy number given the overlap in symptoms, the likely predisposition of those with HaT to develop MCAS, and the fact that these patients could be at an increased risk for anaphylaxis.^4,7,9,11 However, the clinical phenotype for HaT includes allergic disorders affecting the skin as well as neuropsychiatric and connective tissue abnormalities that are distinctive from MCAS. Although HaT may be considered a heritable risk factor for MCAS, MCAS is only 1 potential phenotype associated with HaT.⁹

Implications of HaT

Hereditary alpha tryptasemia should be considered in all patients with basal tryptase levels greater than 8 ng/mL. Cutaneous symptoms are among the most common presentations for individuals with HaT and can include AD, chronic or episodic urticaria, pruritus, flushing, and angioedema. However, HaT is unique because of the coupling of these common dermatologic findings with other abnormalities, including abdominal pain and diarrhea, hypermobile joints, and autonomic dysfunction. Patients with HaT also may manifest psychiatric concerns of anxiety, depression, and chronic pain, all of which have been linked to this disorder.

It is unclear in HaT if the presence of extra-allelic copies of tryptase in an individual is directly pathogenic. The effects of increased basal tryptase and α2β2 tetramers have been shown to likely be responsible for some of the clinical features in these individuals but also may magnify other individual underlying disease(s) or diathesis in which mast cells are naturally abundant.⁸ In the skin, this increased mast cell activation and subsequent histamine release frequently are visible as dermatographia and urticaria. However, mast cell numbers also are known to be increased in both psoriatic and AD skin lesions,¹² thus severe presentation of these diseases in conjunction with the other symptoms associated with mast cell activation should prompt suspicion for HaT.

Effects of HaT on Other Cutaneous Disease—Given the increase of mast cells in AD skin lesions and fact that 94% of patients in the 2014 Lyons et al¹ study cited a history of AD, HaT may be a risk factor in the development of AD. Interestingly, in addition to the increased mast cells in AD lesions, PAR2+ nerve fibers also are increased in AD lesions and have been implicated in the nonhistaminergic pruritus experienced by patients with AD.¹² Thus, given the proposed propensity for α2β2 tetramers to activate PAR2, it is possible this mechanism may contribute to severe pruritus in individuals with AD and concurrent HaT, as those with HaT express increased α2β2 tetramers. However, no study to date has directly compared AD symptoms in patients with concurrent HaT vs patients without it. Further research is needed on how HaT impacts other allergic and inflammatory skin diseases such as AD and psoriasis, but one may reasonably consider HaT when treating chronic inflammatory skin diseases refractory to typical interventions and/or severe presentations. Although HaT is an autosomal-dominant disorder, it is not detected by standard whole exome sequencing or microarrays. A commercial test is available, utilizing a buccal swab to test for TPSAB1 copy number.

HaT and Mast Cell Disorders—When evaluating someone with suspected HaT, it is important to screen for other symptoms of mast cell activation. For instance, in the GI tract increased mast cell activation results in activation of motor neurons and nociceptors and increases secretion and peristalsis with consequent bloating, abdominal pain, and diarrhea.¹⁰ Likewise, tryptase also has neuromodulatory effects that amplify the perception of pain and are likely responsible for the feelings of hyperalgesia reported in patients with HaT.¹³

There is substantial overlap in the clinical pictures of HaT and MCAS, and HaT is considered a heritable risk factor for MCAS. Consequently, any patient undergoing workup for MCAS also should be tested for HaT. Although HaT is associated with consistently elevated tryptase, MCAS is episodic in nature, and an increase in tryptase levels of at least 20% plus 2 ng/mL from baseline only in the presence of other symptoms reflective of mast cell activation (Table) is a prerequisite for diagnosis.⁹ Chronic signs and symptoms of atopy, chronic urticaria, and severe asthma are not indicative of MCAS but are frequently seen in HaT.

Another cause of persistently elevated tryptase levels is SM. Systemic mastocytosis is defined by aberrant clonal mast cell expansion and systemic involvement¹¹ and can cause persistent symptoms, unlike MCAS alone. However, SM also can be associated with MCAS.⁹ Notably, a baseline serum tryptase level greater than 20 ng/mL—much higher than the threshold of greater than 8 ng/mL for suspicion of HaT—is seen in 75% of SM cases and is part of the minor diagnostic criteria for the disease.^9,11 However, the 2016 study identifying increased TPSAB1 α-tryptase–encoding sequences as the causative entity for HaT by Lyons et al² found the average (SD) basal serum tryptase level in individuals with α-tryptase–encoding sequence duplications to be 15 (5) ng/mL and 24 (6) ng/mL in those with triplications. Thus, there likely is no threshold for elevated baseline tryptase levels that would indicate SM over HaT as a more likely diagnosis. However, SM will present with new persistently elevated tryptase levels, whereas the elevation in HaT is believed to be lifelong.⁵ Also in contrast to HaT, SM can present with liver, spleen, and lymph node involvement; bone sclerosis; and cytopenia.^11,14

Mastocytosis is much rarer than HaT, with an estimated prevalence of 9 cases per 100,000 individuals in the United States.¹¹ Although HaT diagnostic testing is noninvasive, SM requires a bone marrow biopsy for definitive diagnosis. Given the likely much higher prevalence of HaT than SM and the patient burden of a bone marrow biopsy, HaT should be considered before proceeding with a bone marrow biopsy to evaluate for SM when a patient presents with persistent systemic symptoms of mast cell activation and elevated baseline tryptase levels. Furthermore, it also would be prudent to test for HaT in patients with known SM, as a cohort study by Lyons et al⁵ indicated that HaT is likely more common in those with SM (12.2% [10/82] of cohort with known SM vs 5.3% of 398 controls), and patients with concurrent SM and HaT were at a higher risk for severe anaphylaxis (RR=9.5; P=.007).

Studies thus far surrounding HaT have not evaluated timing of initial symptom onset or age of initial presentation for HaT. Furthermore, there is no guarantee that those with increased TPSAB1 copy number will be symptomatic, as there have been reports of asymptomatic individuals with HaT who had basal serum levels greater than 8 ng/mL.⁷ As research into HaT continues and larger cohorts are evaluated, questions surrounding timing of symptom onset and various factors that may make someone more likely to display a particular phenotype will be answered.

Treatment—Long-term prognosis for individuals with HaT is largely unknown. Unfortunately, there are limited data to support a single effective treatment strategy for managing HaT, and treatment has varied based on predominant symptoms. For cutaneous and GI tract symptoms, trials of maximal H₁ and H₂ antihistamines twice daily have been recommended.⁴ Omalizumab was reported to improve chronic urticaria in 3 of 3 patients, showing potential promise as a treatment.⁴ Mast cell stabilizers, such as oral cromolyn, have been used for severe GI symptoms, while some patients also have reported improvement with oral ketotifen.⁶ Other medications, such as tricyclic antidepressants, clemastine fumarate, and gabapentin, have been beneficial anecdotally.⁶ Given the lack of harmful effects seen in individuals who are α-tryptase deficient, α-tryptase inhibition is an intriguing target for future therapies.

Conclusion

Patients who present with a constellation of dermatologic, allergic, GI tract, neuropsychiatric, respiratory, autonomic, and connective tissue abnormalities consistent with HaT may receive a prompt diagnosis if the association is recognized. The full relationship between HaT and other chronic dermatologic disorders is still unknown. Ultimately, heightened interest and research into HaT will lead to more treatment options available for affected patients.

ILLUSTRATION: PAUL ZWOLAK

While many anticipated the fall of Roe v Wade after the leaked Supreme Court of the United States (SCOTUS) decision in the Dobbs v Jackson case, few may have fully comprehended the myriad of ways this ruling would create a national health care crisis overnight. Since the ruling, abortion has been banned, or a 6-week gestational age limit has been implemented, in a total of 13 states, all within the South and Midwest regions of the country.¹ Many additional states will almost assuredly enact bans on access to reproductive health care in the near future. While the specific case of the 10-year-old rape victim in Ohio and her gynecologic care by Dr. Caitlin Bernard, an Indiana ObGyn, has garnered national attention, most of the devastating effects have not yet been realized.² Recent published data highlights the substantially negative impact these legislative changes already have had regarding the treatment of early spontaneous abortions and premature rupture of membranes.^3,4 Physicians could face legal consequences for treating emergencies, such as ectopic pregnancies, in some states.⁵

The 2022 American College of Obstetricians and Gynecologists (ACOG) Annual Clinical and Scientific Meeting, held shortly after the leaked SCOTUS opinion, was unlike most others. ACOG staff appropriately recognized the vastly different ways this ruling would affect patients and providers alike, simply based on the states in which they reside. ACOG staff organized the large group of attendees according to self-identified status (ie, whether they worked in states with protected, restricted, or threatened access to abortion care). Since this is such a vast topic, attendees also were asked to identify an area upon which to focus, such as the provision of health care, advocacy, or education. As a clinician practicing in Massachusetts, Dr. Bradley found herself meeting with an ACOG leader from California as they brainstormed how to best help our own communities. In conversing with attendees from other parts of the country, it became apparent the challenges others would be facing elsewhere were far more substantive than those we would be facing in “blue states.” After the Dobbs ruling, those predictions became harsh realities.

As we begin to see and hear reports of the devastating consequences of this ruling in “red states,” those of us in protected states have been struggling to try and ascertain how to help. Many of us have worked with our own legislatures to further enshrine protections for our patients and clinicians. New York and Massachusetts exemplify these efforts.^6,7 These legislative efforts have included liability protections for patients and their clinicians who care for those who travel from restricted to protected states. Others involve codifying the principles of Roe and clarifying existing law to improve access. An online fundraiser organized by physicians to assist Dr. Bernard with her legal costs as she faces politically motivated investigation by Indiana state authorities has raised more than $260,000.⁸ Many expressed the potential legal and medical peril for examiners and examinees if the American Board of Obstetrics and Gynecology held in-person oral examinations in Texas as previously scheduled.⁹ An online petition to change the format to virtual had 728 signatories, and the format was changed back to virtual.¹⁰

The implications on medical schools, residencies, and fellowships cannot be overstated. The Dobbs ruling almost immediately affected nearly half of the training programs, which is particularly problematic given the Accreditation Council for Graduate Medical Education requirement that all ObGyn residents have access to abortion training.¹¹ Other programs already are starting to try to meet this vast training need. The University of California San Francisco started offering training to physicians from Texas who were affected by the strict restrictions that predated Dobbs in the SB8 legislation, which turned ordinary citizens into vigilantes.¹²

ACOG has created an online resource (https://www.acog.org/advocacy/abortion-is-essential) with a number of different sections regarding clinical care, education and training, advocacy at the state level, and how to use effective language when talking about abortion in our communities. Planned Parenthood also suggests a myriad of ways those directly and indirectly affected could get involved:

1. Donate to the National Network of Abortion Funds. This fund (https://secure.actblue.com/donate/fundabortionnow) facilitates care for those without the financial means to obtain it, supporting travel, lodging, and child care.
2. Share #AbortionAccess posts on social media. These stories are a powerful reminder of the incredibly harmful impact this legislation can have on our patients.
3. Donate to the If When How’s Legal Repro Defense Fund (https:/www.ifwhenhow.org/), which helps cover legal costs for those facing state persecution related to reproductive health care.
4. Volunteer to help protect abortion health care at the state level.
5. Engage with members of Congress in their home districts. (https://www.congress.gov/members/find-your-member)
6. Contact the Planned Parenthood Local Engagement Team to facilitate your group, business, or organization’s involvement.
7. Partner. Facilitate your organization and other companies to partner with Planned Parenthood and sign up for Bans off our Bodies (https://docs.google.com/forms/d/e/1FAIpQLSdrmxwMcwNXJ8I NE8S2gYjDDXuT76ws_Fr7CLm3 qbtR8dcZHw/viewform).
8. Record your perspective about abortion (https://www.together.plannedparenthood.org/articles/6-share-abortion-story), whether it’s having had one, supported someone who had one, or advocated for others to have access to the procedure.¹³

ACOG also outlines several ways those of us in protected states could help shape the landscape in other communities in addition to advocating for state medical society resolutions, writing op-eds and letters to the editor, and utilizing ACOG’s social media graphics.¹⁴ In recognition of the often sensitive, polarizing nature of these discussions, ACOG is offering a workshop entitled “Building Evidence-Based Skills for Effective Conversations about Abortion.”¹⁵

Abortion traditionally was a policy issue other medical organizations shied away from developing official policy on and speaking out in support of, but recognizing the devastating scope of the public health crisis, 75 medical professional organizations recently released a strongly worded joint statement noting, “As leading medical and health care organizations dedicated to patient care and public health, we condemn this and all interference in the patient–clinician relationship.”¹⁶ Clinicians could work to expand this list to include all aspects of organized medicine. Initiatives to get out the vote may be helpful in vulnerable states, as well.

Clinicians in protected states are not necessarily directly affected in our daily interactions with patients, but we stand in solidarity with those who are. We must remain united as a profession as different state legislatures seek to divide us. We must support those who are struggling every day. Our colleagues and fellow citizens deserve nothing less. ●

ILLUSTRATION: PAUL ZWOLAK

While many anticipated the fall of Roe v Wade after the leaked Supreme Court of the United States (SCOTUS) decision in the Dobbs v Jackson case, few may have fully comprehended the myriad of ways this ruling would create a national health care crisis overnight. Since the ruling, abortion has been banned, or a 6-week gestational age limit has been implemented, in a total of 13 states, all within the South and Midwest regions of the country.¹ Many additional states will almost assuredly enact bans on access to reproductive health care in the near future. While the specific case of the 10-year-old rape victim in Ohio and her gynecologic care by Dr. Caitlin Bernard, an Indiana ObGyn, has garnered national attention, most of the devastating effects have not yet been realized.² Recent published data highlights the substantially negative impact these legislative changes already have had regarding the treatment of early spontaneous abortions and premature rupture of membranes.^3,4 Physicians could face legal consequences for treating emergencies, such as ectopic pregnancies, in some states.⁵

The 2022 American College of Obstetricians and Gynecologists (ACOG) Annual Clinical and Scientific Meeting, held shortly after the leaked SCOTUS opinion, was unlike most others. ACOG staff appropriately recognized the vastly different ways this ruling would affect patients and providers alike, simply based on the states in which they reside. ACOG staff organized the large group of attendees according to self-identified status (ie, whether they worked in states with protected, restricted, or threatened access to abortion care). Since this is such a vast topic, attendees also were asked to identify an area upon which to focus, such as the provision of health care, advocacy, or education. As a clinician practicing in Massachusetts, Dr. Bradley found herself meeting with an ACOG leader from California as they brainstormed how to best help our own communities. In conversing with attendees from other parts of the country, it became apparent the challenges others would be facing elsewhere were far more substantive than those we would be facing in “blue states.” After the Dobbs ruling, those predictions became harsh realities.

As we begin to see and hear reports of the devastating consequences of this ruling in “red states,” those of us in protected states have been struggling to try and ascertain how to help. Many of us have worked with our own legislatures to further enshrine protections for our patients and clinicians. New York and Massachusetts exemplify these efforts.^6,7 These legislative efforts have included liability protections for patients and their clinicians who care for those who travel from restricted to protected states. Others involve codifying the principles of Roe and clarifying existing law to improve access. An online fundraiser organized by physicians to assist Dr. Bernard with her legal costs as she faces politically motivated investigation by Indiana state authorities has raised more than $260,000.⁸ Many expressed the potential legal and medical peril for examiners and examinees if the American Board of Obstetrics and Gynecology held in-person oral examinations in Texas as previously scheduled.⁹ An online petition to change the format to virtual had 728 signatories, and the format was changed back to virtual.¹⁰

The implications on medical schools, residencies, and fellowships cannot be overstated. The Dobbs ruling almost immediately affected nearly half of the training programs, which is particularly problematic given the Accreditation Council for Graduate Medical Education requirement that all ObGyn residents have access to abortion training.¹¹ Other programs already are starting to try to meet this vast training need. The University of California San Francisco started offering training to physicians from Texas who were affected by the strict restrictions that predated Dobbs in the SB8 legislation, which turned ordinary citizens into vigilantes.¹²

ACOG has created an online resource (https://www.acog.org/advocacy/abortion-is-essential) with a number of different sections regarding clinical care, education and training, advocacy at the state level, and how to use effective language when talking about abortion in our communities. Planned Parenthood also suggests a myriad of ways those directly and indirectly affected could get involved:

1. Donate to the National Network of Abortion Funds. This fund (https://secure.actblue.com/donate/fundabortionnow) facilitates care for those without the financial means to obtain it, supporting travel, lodging, and child care.
2. Share #AbortionAccess posts on social media. These stories are a powerful reminder of the incredibly harmful impact this legislation can have on our patients.
3. Donate to the If When How’s Legal Repro Defense Fund (https:/www.ifwhenhow.org/), which helps cover legal costs for those facing state persecution related to reproductive health care.
4. Volunteer to help protect abortion health care at the state level.
5. Engage with members of Congress in their home districts. (https://www.congress.gov/members/find-your-member)
6. Contact the Planned Parenthood Local Engagement Team to facilitate your group, business, or organization’s involvement.
7. Partner. Facilitate your organization and other companies to partner with Planned Parenthood and sign up for Bans off our Bodies (https://docs.google.com/forms/d/e/1FAIpQLSdrmxwMcwNXJ8I NE8S2gYjDDXuT76ws_Fr7CLm3 qbtR8dcZHw/viewform).
8. Record your perspective about abortion (https://www.together.plannedparenthood.org/articles/6-share-abortion-story), whether it’s having had one, supported someone who had one, or advocated for others to have access to the procedure.¹³

ACOG also outlines several ways those of us in protected states could help shape the landscape in other communities in addition to advocating for state medical society resolutions, writing op-eds and letters to the editor, and utilizing ACOG’s social media graphics.¹⁴ In recognition of the often sensitive, polarizing nature of these discussions, ACOG is offering a workshop entitled “Building Evidence-Based Skills for Effective Conversations about Abortion.”¹⁵

Abortion traditionally was a policy issue other medical organizations shied away from developing official policy on and speaking out in support of, but recognizing the devastating scope of the public health crisis, 75 medical professional organizations recently released a strongly worded joint statement noting, “As leading medical and health care organizations dedicated to patient care and public health, we condemn this and all interference in the patient–clinician relationship.”¹⁶ Clinicians could work to expand this list to include all aspects of organized medicine. Initiatives to get out the vote may be helpful in vulnerable states, as well.

Clinicians in protected states are not necessarily directly affected in our daily interactions with patients, but we stand in solidarity with those who are. We must remain united as a profession as different state legislatures seek to divide us. We must support those who are struggling every day. Our colleagues and fellow citizens deserve nothing less. ●

ILLUSTRATION: PAUL ZWOLAK

While many anticipated the fall of Roe v Wade after the leaked Supreme Court of the United States (SCOTUS) decision in the Dobbs v Jackson case, few may have fully comprehended the myriad of ways this ruling would create a national health care crisis overnight. Since the ruling, abortion has been banned, or a 6-week gestational age limit has been implemented, in a total of 13 states, all within the South and Midwest regions of the country.¹ Many additional states will almost assuredly enact bans on access to reproductive health care in the near future. While the specific case of the 10-year-old rape victim in Ohio and her gynecologic care by Dr. Caitlin Bernard, an Indiana ObGyn, has garnered national attention, most of the devastating effects have not yet been realized.² Recent published data highlights the substantially negative impact these legislative changes already have had regarding the treatment of early spontaneous abortions and premature rupture of membranes.^3,4 Physicians could face legal consequences for treating emergencies, such as ectopic pregnancies, in some states.⁵

The 2022 American College of Obstetricians and Gynecologists (ACOG) Annual Clinical and Scientific Meeting, held shortly after the leaked SCOTUS opinion, was unlike most others. ACOG staff appropriately recognized the vastly different ways this ruling would affect patients and providers alike, simply based on the states in which they reside. ACOG staff organized the large group of attendees according to self-identified status (ie, whether they worked in states with protected, restricted, or threatened access to abortion care). Since this is such a vast topic, attendees also were asked to identify an area upon which to focus, such as the provision of health care, advocacy, or education. As a clinician practicing in Massachusetts, Dr. Bradley found herself meeting with an ACOG leader from California as they brainstormed how to best help our own communities. In conversing with attendees from other parts of the country, it became apparent the challenges others would be facing elsewhere were far more substantive than those we would be facing in “blue states.” After the Dobbs ruling, those predictions became harsh realities.

As we begin to see and hear reports of the devastating consequences of this ruling in “red states,” those of us in protected states have been struggling to try and ascertain how to help. Many of us have worked with our own legislatures to further enshrine protections for our patients and clinicians. New York and Massachusetts exemplify these efforts.^6,7 These legislative efforts have included liability protections for patients and their clinicians who care for those who travel from restricted to protected states. Others involve codifying the principles of Roe and clarifying existing law to improve access. An online fundraiser organized by physicians to assist Dr. Bernard with her legal costs as she faces politically motivated investigation by Indiana state authorities has raised more than $260,000.⁸ Many expressed the potential legal and medical peril for examiners and examinees if the American Board of Obstetrics and Gynecology held in-person oral examinations in Texas as previously scheduled.⁹ An online petition to change the format to virtual had 728 signatories, and the format was changed back to virtual.¹⁰

The implications on medical schools, residencies, and fellowships cannot be overstated. The Dobbs ruling almost immediately affected nearly half of the training programs, which is particularly problematic given the Accreditation Council for Graduate Medical Education requirement that all ObGyn residents have access to abortion training.¹¹ Other programs already are starting to try to meet this vast training need. The University of California San Francisco started offering training to physicians from Texas who were affected by the strict restrictions that predated Dobbs in the SB8 legislation, which turned ordinary citizens into vigilantes.¹²

ACOG has created an online resource (https://www.acog.org/advocacy/abortion-is-essential) with a number of different sections regarding clinical care, education and training, advocacy at the state level, and how to use effective language when talking about abortion in our communities. Planned Parenthood also suggests a myriad of ways those directly and indirectly affected could get involved:

1. Donate to the National Network of Abortion Funds. This fund (https://secure.actblue.com/donate/fundabortionnow) facilitates care for those without the financial means to obtain it, supporting travel, lodging, and child care.
2. Share #AbortionAccess posts on social media. These stories are a powerful reminder of the incredibly harmful impact this legislation can have on our patients.
3. Donate to the If When How’s Legal Repro Defense Fund (https:/www.ifwhenhow.org/), which helps cover legal costs for those facing state persecution related to reproductive health care.
4. Volunteer to help protect abortion health care at the state level.
5. Engage with members of Congress in their home districts. (https://www.congress.gov/members/find-your-member)
6. Contact the Planned Parenthood Local Engagement Team to facilitate your group, business, or organization’s involvement.
7. Partner. Facilitate your organization and other companies to partner with Planned Parenthood and sign up for Bans off our Bodies (https://docs.google.com/forms/d/e/1FAIpQLSdrmxwMcwNXJ8I NE8S2gYjDDXuT76ws_Fr7CLm3 qbtR8dcZHw/viewform).
8. Record your perspective about abortion (https://www.together.plannedparenthood.org/articles/6-share-abortion-story), whether it’s having had one, supported someone who had one, or advocated for others to have access to the procedure.¹³