Editorial

The article in this issue by Bersoux et al on pharmacotherapy to manage obesity¹ is apropos in light of a recent study² showing that patients are filling 15 times more prescriptions for antidiabetic medications (excluding insulin) than for antiobesity drugs. What makes this finding significant is that nearly 3 times more adults meet the criteria for use of antiobesity drugs than for antidiabetic drugs—116 million vs 30 million, respectively.

See related article

This underuse of antiobesity medications has been noted in other studies. In 1 study,³ only about 2% of adults eligible for weight-loss drug therapy received a prescription. Conversely, about 86% of adults diagnosed with diabetes received antidiabetic medications.³

WEIGHT LOSS: IT'S IMPORTANT

This underuse of weight-loss drugs occurs despite our understanding that obesity is a risk factor for developing diabetes and that weight loss in obese patients reduces the risk.

The landmark Diabetes Prevention Program study found that even modest weight loss of 7% reduced the risk of developing diabetes by 58% in overweight and prediabetic individuals.⁴ Additionally, a 5% to 10% weight loss can lead to significant improvements in many comorbidities, including diabetes, hyperlipidemia, hypertension, sleep apnea, and fatty liver disease.

Antiobesity medications can help patients achieve weight-loss goals, especially if lifestyle and behavioral modifications alone have been unsuccessful. Data show that these drugs result in an average weight loss of 5% to 15% when added to diet and exercise.

BARRIERS TO PRESCRIBING WEIGHT-LOSS DRUGS

Why are practitioners reluctant to prescribe these drugs despite the worsening obesity epidemic and despite knowing that obesity is a risk factor for diabetes? Many of us who practice obesity medicine believe there are several reasons.

One barrier is the misconception that obesity does not warrant treatment with weight-loss medications, even though most practitioners will readily admit that patients cannot achieve effective, durable, and meaningful weight loss with behavioral changes and lifestyle modifications alone.

Other barriers stem from issues such as time constraints in the office, lack of training to treat this condition, and not enough data on the newer chronic weight-loss medications. And there are stringent requirements for patient follow-up once a medication has been initiated. Finally, it’s often difficult to obtain insurance coverage.

Addressing the barriers

Of these, I believe the biggest barrier for busy practitioners is finding the time and effort they need to devote to prescribing weight-loss medications. There are ways to address these issues.

Regarding time constraints, practitioners can discuss weight loss at follow-up visits and refer patients to obesity specialists. Regarding gaps in training and knowledge of obesity management, there are consensus guidelines for the identification, evaluation, and treatment of the overweight or obese individual.^5–7 Guidelines provide extensive information on the pharmacologic treatment of obesity. These resources provide valuable evidence-based recommendations on how to manage this chronic disease.

ARMED WITH INFORMATION, PHARMACOLOGIC OPTIONS

Bersoux et al provide another valuable resource for clinical use of weight-loss drugs.¹ They accurately review the available medications, their mechanisms of action, dosing, efficacy, side effect profiles, and clinical indications. Their review is comprehensive in every aspect of this drug class.

This is important information for practitioners to have when considering prescribing antiobesity medications. It is especially important for primary care practitioners because of the large number of obese or overweight patients they treat.

Drug options have expanded

We did not always have this many drugs to choose from. As Bersoux et al note, practitioners had limited options for weight-loss medications during the 1990s and early 2000s, and several of those had to be taken off the market because of serious side effects. Then between 2012 and 2014, the US Food and Drug Administration approved 4 new medications, giving us a total of 6 weight-loss drugs. Those approvals greatly increased the available drug treatments, giving us much-needed options beyond lifestyle and behavioral modifications.

Although it is widely accepted that antiobesity drugs are underused, the study by Thomas et al was the first to quantify the extent of underuse, especially for the newer chronic weight-loss drugs.² Their data show that only about 19% of antiobesity prescriptions were for the newer drugs while 74% were for the older but short-term medication phentermine.

Bersoux et al seem to encourage primary care physicians, or anyone caring for overweight or obese patients, to consider prescribing these treatments if nonpharmacologic options are unsuccessful. I agree with this concept because there are not enough specialists to care for the more than 116 million individuals who are potential candidates for antiobesity medications.

THE TIME HAS COME

This new class of medications has been strongly endorsed by the most prestigious organizations and societies involved in developing treatment guidelines for the overweight or obese patient. It is time for everyone who sees overweight or obese patients in daily practice to consider adopting chronic weight-loss medications as adjunctive therapy if lifestyle and behavioral strategies are ineffective.

The article in this issue by Bersoux et al on pharmacotherapy to manage obesity¹ is apropos in light of a recent study² showing that patients are filling 15 times more prescriptions for antidiabetic medications (excluding insulin) than for antiobesity drugs. What makes this finding significant is that nearly 3 times more adults meet the criteria for use of antiobesity drugs than for antidiabetic drugs—116 million vs 30 million, respectively.

See related article

This underuse of antiobesity medications has been noted in other studies. In 1 study,³ only about 2% of adults eligible for weight-loss drug therapy received a prescription. Conversely, about 86% of adults diagnosed with diabetes received antidiabetic medications.³

WEIGHT LOSS: IT'S IMPORTANT

This underuse of weight-loss drugs occurs despite our understanding that obesity is a risk factor for developing diabetes and that weight loss in obese patients reduces the risk.

The landmark Diabetes Prevention Program study found that even modest weight loss of 7% reduced the risk of developing diabetes by 58% in overweight and prediabetic individuals.⁴ Additionally, a 5% to 10% weight loss can lead to significant improvements in many comorbidities, including diabetes, hyperlipidemia, hypertension, sleep apnea, and fatty liver disease.

Antiobesity medications can help patients achieve weight-loss goals, especially if lifestyle and behavioral modifications alone have been unsuccessful. Data show that these drugs result in an average weight loss of 5% to 15% when added to diet and exercise.

BARRIERS TO PRESCRIBING WEIGHT-LOSS DRUGS

Why are practitioners reluctant to prescribe these drugs despite the worsening obesity epidemic and despite knowing that obesity is a risk factor for diabetes? Many of us who practice obesity medicine believe there are several reasons.

One barrier is the misconception that obesity does not warrant treatment with weight-loss medications, even though most practitioners will readily admit that patients cannot achieve effective, durable, and meaningful weight loss with behavioral changes and lifestyle modifications alone.

Other barriers stem from issues such as time constraints in the office, lack of training to treat this condition, and not enough data on the newer chronic weight-loss medications. And there are stringent requirements for patient follow-up once a medication has been initiated. Finally, it’s often difficult to obtain insurance coverage.

Addressing the barriers

Of these, I believe the biggest barrier for busy practitioners is finding the time and effort they need to devote to prescribing weight-loss medications. There are ways to address these issues.

Regarding time constraints, practitioners can discuss weight loss at follow-up visits and refer patients to obesity specialists. Regarding gaps in training and knowledge of obesity management, there are consensus guidelines for the identification, evaluation, and treatment of the overweight or obese individual.^5–7 Guidelines provide extensive information on the pharmacologic treatment of obesity. These resources provide valuable evidence-based recommendations on how to manage this chronic disease.

ARMED WITH INFORMATION, PHARMACOLOGIC OPTIONS

Bersoux et al provide another valuable resource for clinical use of weight-loss drugs.¹ They accurately review the available medications, their mechanisms of action, dosing, efficacy, side effect profiles, and clinical indications. Their review is comprehensive in every aspect of this drug class.

This is important information for practitioners to have when considering prescribing antiobesity medications. It is especially important for primary care practitioners because of the large number of obese or overweight patients they treat.

Drug options have expanded

We did not always have this many drugs to choose from. As Bersoux et al note, practitioners had limited options for weight-loss medications during the 1990s and early 2000s, and several of those had to be taken off the market because of serious side effects. Then between 2012 and 2014, the US Food and Drug Administration approved 4 new medications, giving us a total of 6 weight-loss drugs. Those approvals greatly increased the available drug treatments, giving us much-needed options beyond lifestyle and behavioral modifications.

Although it is widely accepted that antiobesity drugs are underused, the study by Thomas et al was the first to quantify the extent of underuse, especially for the newer chronic weight-loss drugs.² Their data show that only about 19% of antiobesity prescriptions were for the newer drugs while 74% were for the older but short-term medication phentermine.

Bersoux et al seem to encourage primary care physicians, or anyone caring for overweight or obese patients, to consider prescribing these treatments if nonpharmacologic options are unsuccessful. I agree with this concept because there are not enough specialists to care for the more than 116 million individuals who are potential candidates for antiobesity medications.

THE TIME HAS COME

This new class of medications has been strongly endorsed by the most prestigious organizations and societies involved in developing treatment guidelines for the overweight or obese patient. It is time for everyone who sees overweight or obese patients in daily practice to consider adopting chronic weight-loss medications as adjunctive therapy if lifestyle and behavioral strategies are ineffective.

The article in this issue by Bersoux et al on pharmacotherapy to manage obesity¹ is apropos in light of a recent study² showing that patients are filling 15 times more prescriptions for antidiabetic medications (excluding insulin) than for antiobesity drugs. What makes this finding significant is that nearly 3 times more adults meet the criteria for use of antiobesity drugs than for antidiabetic drugs—116 million vs 30 million, respectively.

See related article

This underuse of antiobesity medications has been noted in other studies. In 1 study,³ only about 2% of adults eligible for weight-loss drug therapy received a prescription. Conversely, about 86% of adults diagnosed with diabetes received antidiabetic medications.³

WEIGHT LOSS: IT'S IMPORTANT

This underuse of weight-loss drugs occurs despite our understanding that obesity is a risk factor for developing diabetes and that weight loss in obese patients reduces the risk.

The landmark Diabetes Prevention Program study found that even modest weight loss of 7% reduced the risk of developing diabetes by 58% in overweight and prediabetic individuals.⁴ Additionally, a 5% to 10% weight loss can lead to significant improvements in many comorbidities, including diabetes, hyperlipidemia, hypertension, sleep apnea, and fatty liver disease.

Antiobesity medications can help patients achieve weight-loss goals, especially if lifestyle and behavioral modifications alone have been unsuccessful. Data show that these drugs result in an average weight loss of 5% to 15% when added to diet and exercise.

BARRIERS TO PRESCRIBING WEIGHT-LOSS DRUGS

Why are practitioners reluctant to prescribe these drugs despite the worsening obesity epidemic and despite knowing that obesity is a risk factor for diabetes? Many of us who practice obesity medicine believe there are several reasons.

One barrier is the misconception that obesity does not warrant treatment with weight-loss medications, even though most practitioners will readily admit that patients cannot achieve effective, durable, and meaningful weight loss with behavioral changes and lifestyle modifications alone.

Other barriers stem from issues such as time constraints in the office, lack of training to treat this condition, and not enough data on the newer chronic weight-loss medications. And there are stringent requirements for patient follow-up once a medication has been initiated. Finally, it’s often difficult to obtain insurance coverage.

Addressing the barriers

Of these, I believe the biggest barrier for busy practitioners is finding the time and effort they need to devote to prescribing weight-loss medications. There are ways to address these issues.

Regarding time constraints, practitioners can discuss weight loss at follow-up visits and refer patients to obesity specialists. Regarding gaps in training and knowledge of obesity management, there are consensus guidelines for the identification, evaluation, and treatment of the overweight or obese individual.^5–7 Guidelines provide extensive information on the pharmacologic treatment of obesity. These resources provide valuable evidence-based recommendations on how to manage this chronic disease.

ARMED WITH INFORMATION, PHARMACOLOGIC OPTIONS

Bersoux et al provide another valuable resource for clinical use of weight-loss drugs.¹ They accurately review the available medications, their mechanisms of action, dosing, efficacy, side effect profiles, and clinical indications. Their review is comprehensive in every aspect of this drug class.

This is important information for practitioners to have when considering prescribing antiobesity medications. It is especially important for primary care practitioners because of the large number of obese or overweight patients they treat.

Drug options have expanded

We did not always have this many drugs to choose from. As Bersoux et al note, practitioners had limited options for weight-loss medications during the 1990s and early 2000s, and several of those had to be taken off the market because of serious side effects. Then between 2012 and 2014, the US Food and Drug Administration approved 4 new medications, giving us a total of 6 weight-loss drugs. Those approvals greatly increased the available drug treatments, giving us much-needed options beyond lifestyle and behavioral modifications.

Although it is widely accepted that antiobesity drugs are underused, the study by Thomas et al was the first to quantify the extent of underuse, especially for the newer chronic weight-loss drugs.² Their data show that only about 19% of antiobesity prescriptions were for the newer drugs while 74% were for the older but short-term medication phentermine.

Bersoux et al seem to encourage primary care physicians, or anyone caring for overweight or obese patients, to consider prescribing these treatments if nonpharmacologic options are unsuccessful. I agree with this concept because there are not enough specialists to care for the more than 116 million individuals who are potential candidates for antiobesity medications.

THE TIME HAS COME

This new class of medications has been strongly endorsed by the most prestigious organizations and societies involved in developing treatment guidelines for the overweight or obese patient. It is time for everyone who sees overweight or obese patients in daily practice to consider adopting chronic weight-loss medications as adjunctive therapy if lifestyle and behavioral strategies are ineffective.

In this issue of the Journal of Hospital Medicine, Lee et al.¹ describe a randomized trial to assess the effectiveness of four different approaches to teaching handoffs with the goal of improving process measures related to interns’ handoffs. The Society of Hospital Medicine (SHM), The Joint Commission (TJC), Accreditation Council for Graduate Medical Education (ACGME), and others have all emphasized the importance of high-quality handoffs as an essential component of safe patient care.^2-4 The ACGME specifically requires that all institutions that sponsor ACGME-accredited programs provide both structure and monitoring, and the SHM complements this with evidence-based guidelines for handoffs.

Lee’s team trained 4 groups of residents in handoffs using 4 different hour-long sessions, each with a different focus and educational format. A control group received a 1-hour didactic, which they had already heard; an I-PASS–based training group included role plays; and Policy Mandate and PDSA (Plan, Do, Study, Act) groups included group discussions. The prioritization of content in the sessions varied considerably among the groups, and the results should be interpreted within the context of the variation in both delivery and content.

Consistent with the focus of each intervention, the I-PASS–based training group had the greatest improvement in transfer of patient information, the policy mandate training group (focused on specific tasks) had the greatest improvement in task accountability, and the PDSA-training group (focused on intern-driven improvements) had the greatest improvement in personal responsibility. The control 60-minute didactic group did not show significant improvement in any domains. The lack of improvement in the control group doesn’t imply that the content wasn’t valuable, just that repetition didn’t add anything to baseline. One takeaway from the primary results of this study is that residents are likely to practice and improve what they are taught, and therefore, faculty should teach them purposefully. If residents aren’t taught handoff skills, they are unlikely to master them.

The interventions used in this study are neither mutually exclusive nor duplicative. In the final conclusions, the authors described the potential for a curriculum that includes elements from all 3 interventions. One could certainly imagine a handoff training program that includes elements of the I-PASS handoff bundle including role plays, additional emphasis on personal responsibility for specific tasks, as well as a focus on PDSA cycles of improvement for handoff processes. This likely could be accomplished with efficiency and might add only an hour to the 1-hour trainings. Evidence from the I-PASS study⁵ suggests that improving handoffs can decrease medical errors by 21% and adverse events by 30%; this certainly seems worth the time.

Checklist-based observation tools can provide valuable data to assess handoffs.⁶ Lee’s study used a checklist based on TJC recommendations, and the 17 checklist elements overlapped somewhat with the SHM guidelines,² providing some evidence for content validity. The dependent variable was total number of checklist items included in handoffs, a methodology that assumes that all handoff elements are equally important (eg, gender is weighted equally to if-then plans). This checklist also has a large proportion of items related to 2-way and closed-loop communication and therefore, places heavy weight on this component of handoffs. Adapting this checklist into an assessment tool would require additional validity evidence but could make it a very useful tool for completing handoff assessments and providing meaningful feedback.

The ideal data collection instrument would also include outcome measures, in addition to process measures. Improvements in outcome measures such as medical errors and adverse events, are more difficult to document but also provide more valuable data about the impact of curricula. In designing new hybrid curricula, it will be extremely important to focus on those outcomes that reflect the greatest impact on patient safety.

Finally, this study reminds us that the delivery modes of curricula are important factors in learning. The control group received an exclusively didactic presentation that they had heard before, while the other 3 groups had interactive components including role plays and group discussions. The improvements in different domains with different training formats provide evidence for the complementary nature. Interactive curricula involving role plays, simulations, and small-group discussions are more resource-intense than simple didactics, but they are also likely to be more impactful.

Teaching and assessing the quality of handoffs is critical to the safe practice of medicine. New ACGME duty hour requirements, which began in July, will allow for increased flexibility allowing longer shifts with shorter breaks.⁷ Regardless of the shift/call schedules programs design for their trainees, safe handoffs are essential. The strategies described here may be useful for helping institutions improve patient safety through better handoffs. This study adds to the bulk of data demonstrating that handoffs are a skill that should be both taught and assessed during residency training.

In this issue of the Journal of Hospital Medicine, Lee et al.¹ describe a randomized trial to assess the effectiveness of four different approaches to teaching handoffs with the goal of improving process measures related to interns’ handoffs. The Society of Hospital Medicine (SHM), The Joint Commission (TJC), Accreditation Council for Graduate Medical Education (ACGME), and others have all emphasized the importance of high-quality handoffs as an essential component of safe patient care.^2-4 The ACGME specifically requires that all institutions that sponsor ACGME-accredited programs provide both structure and monitoring, and the SHM complements this with evidence-based guidelines for handoffs.

Lee’s team trained 4 groups of residents in handoffs using 4 different hour-long sessions, each with a different focus and educational format. A control group received a 1-hour didactic, which they had already heard; an I-PASS–based training group included role plays; and Policy Mandate and PDSA (Plan, Do, Study, Act) groups included group discussions. The prioritization of content in the sessions varied considerably among the groups, and the results should be interpreted within the context of the variation in both delivery and content.

Consistent with the focus of each intervention, the I-PASS–based training group had the greatest improvement in transfer of patient information, the policy mandate training group (focused on specific tasks) had the greatest improvement in task accountability, and the PDSA-training group (focused on intern-driven improvements) had the greatest improvement in personal responsibility. The control 60-minute didactic group did not show significant improvement in any domains. The lack of improvement in the control group doesn’t imply that the content wasn’t valuable, just that repetition didn’t add anything to baseline. One takeaway from the primary results of this study is that residents are likely to practice and improve what they are taught, and therefore, faculty should teach them purposefully. If residents aren’t taught handoff skills, they are unlikely to master them.

The interventions used in this study are neither mutually exclusive nor duplicative. In the final conclusions, the authors described the potential for a curriculum that includes elements from all 3 interventions. One could certainly imagine a handoff training program that includes elements of the I-PASS handoff bundle including role plays, additional emphasis on personal responsibility for specific tasks, as well as a focus on PDSA cycles of improvement for handoff processes. This likely could be accomplished with efficiency and might add only an hour to the 1-hour trainings. Evidence from the I-PASS study⁵ suggests that improving handoffs can decrease medical errors by 21% and adverse events by 30%; this certainly seems worth the time.

Checklist-based observation tools can provide valuable data to assess handoffs.⁶ Lee’s study used a checklist based on TJC recommendations, and the 17 checklist elements overlapped somewhat with the SHM guidelines,² providing some evidence for content validity. The dependent variable was total number of checklist items included in handoffs, a methodology that assumes that all handoff elements are equally important (eg, gender is weighted equally to if-then plans). This checklist also has a large proportion of items related to 2-way and closed-loop communication and therefore, places heavy weight on this component of handoffs. Adapting this checklist into an assessment tool would require additional validity evidence but could make it a very useful tool for completing handoff assessments and providing meaningful feedback.

The ideal data collection instrument would also include outcome measures, in addition to process measures. Improvements in outcome measures such as medical errors and adverse events, are more difficult to document but also provide more valuable data about the impact of curricula. In designing new hybrid curricula, it will be extremely important to focus on those outcomes that reflect the greatest impact on patient safety.

Finally, this study reminds us that the delivery modes of curricula are important factors in learning. The control group received an exclusively didactic presentation that they had heard before, while the other 3 groups had interactive components including role plays and group discussions. The improvements in different domains with different training formats provide evidence for the complementary nature. Interactive curricula involving role plays, simulations, and small-group discussions are more resource-intense than simple didactics, but they are also likely to be more impactful.

Teaching and assessing the quality of handoffs is critical to the safe practice of medicine. New ACGME duty hour requirements, which began in July, will allow for increased flexibility allowing longer shifts with shorter breaks.⁷ Regardless of the shift/call schedules programs design for their trainees, safe handoffs are essential. The strategies described here may be useful for helping institutions improve patient safety through better handoffs. This study adds to the bulk of data demonstrating that handoffs are a skill that should be both taught and assessed during residency training.

In this issue of the Journal of Hospital Medicine, Lee et al.¹ describe a randomized trial to assess the effectiveness of four different approaches to teaching handoffs with the goal of improving process measures related to interns’ handoffs. The Society of Hospital Medicine (SHM), The Joint Commission (TJC), Accreditation Council for Graduate Medical Education (ACGME), and others have all emphasized the importance of high-quality handoffs as an essential component of safe patient care.^2-4 The ACGME specifically requires that all institutions that sponsor ACGME-accredited programs provide both structure and monitoring, and the SHM complements this with evidence-based guidelines for handoffs.

Lee’s team trained 4 groups of residents in handoffs using 4 different hour-long sessions, each with a different focus and educational format. A control group received a 1-hour didactic, which they had already heard; an I-PASS–based training group included role plays; and Policy Mandate and PDSA (Plan, Do, Study, Act) groups included group discussions. The prioritization of content in the sessions varied considerably among the groups, and the results should be interpreted within the context of the variation in both delivery and content.

Consistent with the focus of each intervention, the I-PASS–based training group had the greatest improvement in transfer of patient information, the policy mandate training group (focused on specific tasks) had the greatest improvement in task accountability, and the PDSA-training group (focused on intern-driven improvements) had the greatest improvement in personal responsibility. The control 60-minute didactic group did not show significant improvement in any domains. The lack of improvement in the control group doesn’t imply that the content wasn’t valuable, just that repetition didn’t add anything to baseline. One takeaway from the primary results of this study is that residents are likely to practice and improve what they are taught, and therefore, faculty should teach them purposefully. If residents aren’t taught handoff skills, they are unlikely to master them.

The interventions used in this study are neither mutually exclusive nor duplicative. In the final conclusions, the authors described the potential for a curriculum that includes elements from all 3 interventions. One could certainly imagine a handoff training program that includes elements of the I-PASS handoff bundle including role plays, additional emphasis on personal responsibility for specific tasks, as well as a focus on PDSA cycles of improvement for handoff processes. This likely could be accomplished with efficiency and might add only an hour to the 1-hour trainings. Evidence from the I-PASS study⁵ suggests that improving handoffs can decrease medical errors by 21% and adverse events by 30%; this certainly seems worth the time.

Checklist-based observation tools can provide valuable data to assess handoffs.⁶ Lee’s study used a checklist based on TJC recommendations, and the 17 checklist elements overlapped somewhat with the SHM guidelines,² providing some evidence for content validity. The dependent variable was total number of checklist items included in handoffs, a methodology that assumes that all handoff elements are equally important (eg, gender is weighted equally to if-then plans). This checklist also has a large proportion of items related to 2-way and closed-loop communication and therefore, places heavy weight on this component of handoffs. Adapting this checklist into an assessment tool would require additional validity evidence but could make it a very useful tool for completing handoff assessments and providing meaningful feedback.

The ideal data collection instrument would also include outcome measures, in addition to process measures. Improvements in outcome measures such as medical errors and adverse events, are more difficult to document but also provide more valuable data about the impact of curricula. In designing new hybrid curricula, it will be extremely important to focus on those outcomes that reflect the greatest impact on patient safety.

Finally, this study reminds us that the delivery modes of curricula are important factors in learning. The control group received an exclusively didactic presentation that they had heard before, while the other 3 groups had interactive components including role plays and group discussions. The improvements in different domains with different training formats provide evidence for the complementary nature. Interactive curricula involving role plays, simulations, and small-group discussions are more resource-intense than simple didactics, but they are also likely to be more impactful.

Teaching and assessing the quality of handoffs is critical to the safe practice of medicine. New ACGME duty hour requirements, which began in July, will allow for increased flexibility allowing longer shifts with shorter breaks.⁷ Regardless of the shift/call schedules programs design for their trainees, safe handoffs are essential. The strategies described here may be useful for helping institutions improve patient safety through better handoffs. This study adds to the bulk of data demonstrating that handoffs are a skill that should be both taught and assessed during residency training.

“I didn’t have time to write a short letter, so I wrote a long one instead.”

-Mark Twain

Sepsis is a logical target for quality measures. Specifically, sepsis represents the perfect storm of immense public health burden^1-3 combined with unexplained practice^4-6 and outcomes⁷ variation. Thus, it is not surprising that in October 2015, the Centers of Medicare and Medicaid Services (CMS) adopted a sepsis quality measure.⁸ More surprising were the complex contents of the CMS Sepsis Core Measure “SEP-1” quality measure.⁹ CMS had written a “long letter.”

The multiple processes targeted with the CMS SEP-1 quality measure can best be understood with a brief account of history. SEP-1 arose from the National Quality Forum’s (NQF) project #0500: “Severe Sepsis and Septic Shock: Management Bundle,” a measure based upon Rivers et al.’s¹⁰ single-center, randomized, controlled trial of early goal-directed therapy (EGDT) for severe sepsis. EGDT was an intervention that consisted of fluid resuscitation and hemodynamic management based upon fulfilling specific targets of central venous pressure, superior vena cava oxygen saturation (or lactic acid), and hemoglobin and mean arterial pressures.¹¹ The large mortality benefits, physiological rationale, and algorithmic responses to a variety of abnormal clinical values provided an appealing protocol to critical care and emergency physicians trained to normalize measured values, as well as policy makers looking for quality measures. Observational studies consistently showed associations between adoption of guideline-based “sepsis bundles” and improved patient outcomes,^12-14 setting the stage for the transition of NQF #0500 into SEP-1.

However, the transition from EGDT-based NQF #0500 to SEP-1 has been tumultuous. Soon after adoption of SEP-1, the consensus definitions of sepsis changed markedly. Sepsis went from being defined as the presence of infection with concomitant systemic inflammatory response syndrome (sepsis), organ dysfunction (severe sepsis), and/or shock,¹⁵ to being defined as a dysregulated response to infection resulting in life-threatening organ dysfunction (sepsis) and/or fluid-resistant hypotension requiring vasopressors and lactate greater than 2 mmol/L.¹⁶ As the study by Barbash et al.¹⁷in this issue clearly outlines, conflicting definitions of “sepsis” have left clinicians confused regarding whom the SEP-1 measure should apply. At the same time, results of 3 large, international, randomized trials investigating the efficacy of EGDT were published, providing strong evidence that EGDT did not provide improved patient outcomes over usual care.¹⁸ SEP-1 adapted with the evolving evidence base, adding putative “usual care” processes such as evaluation of skin and peripheral pulses, and use of dynamic measures of fluid responsiveness, as quality measures.¹⁹ However, as Barbash et al. also outline, the resulting process measure was incredibly complex, with potentially more than 50 data elements collected over 6 hours in the initial management of sepsis.

In addition to its unprecedented complexity, SEP-1 received criticism for the weak evidence base of its individual components. The general concepts behind SEP-1 are well-accepted tenets of sepsis management: rapid recognition, assessment and treatment of underlying infection, and institution of intravenous fluids and vasopressor support for septic shock. However, the “all or none” prescriptive nature of the SEP-1 bundle was based on a somewhat arbitrary set of measures and targets. For example, patients with septic shock must receive 30 cc/kg of intravenous fluids to be “SEP-1 compliant.” The value “30 cc/kg” was taken from the average volume of fluids reported in prior sepsis trials, essentially based on a very low level of evidence.²⁰ The strict 30 cc/kg cutoff did not take into account that “the median isn’t the message”²¹ in fluid management: optimal resuscitation targets are unclear,²² and selecting the median as a target ignores the fact that 50% of patients enrolled in international trials of EGDT received less than 30 cc/kg of initial fluid resuscitation (the interquartile range was 16-42 cc/kg).¹⁸ Thus, most participants in trials upon which the SEP-1 fluid measure was based would ironically not have met the SEP-1 measure. Mandates for physical exam and physiological measures were based on similarly low levels of evidence.

Into this context, Barbash et al. use a representative sample of US hospitals to explore the opinions of hospital quality leaders regarding the SEP-1 measure. First, the qualitative methods used by Barbash et al. warrant some explanation. Much of biomedical research is characterized by hypothesis-driven, deductive reasoning: theories are tested using observations. In contrast, the methods of Barbash et al. use inductive reasoning: observations are used to develop theories within a systematic approach called “grounded theory” that explores common themes emerging from structured interviews.²³ Inductive reasoning can later inform deductive reasoning, feeding theories into testable hypotheses. However, qualitative, inductive research is not meant to test hypotheses and is not subject to typical notions of “power and sample size” often expected of quantitative statistical analyses. Qualitative studies reach sufficient sample size when no further themes emerge, a situation called “thematic saturation”; the sample size here of 29 participants rests comfortably in the range of participants commonly needed for thematic saturation.²³

Barbash et al. identified common themes in opinions of quality leaders regarding SEP-1. Namely, the complexity of SEP-1 necessitated a major resource investment into sepsis care and data collection. The major infrastructure investments needed to comply with SEP-1 also bred frustration regarding lack of perceived fairness around the “all or none” nature of the measure and raised multiple additional challenges including lack of clinician buy-in and resistance to protocolized care. Prior qualitative studies evaluating hospital quality leaders’ opinions on performance measures identified similar concerns about lack of “fairness,”²⁴ but the implementation of SEP-1 has raised additional concern regarding the large burdens of instituting major infrastructure changes to monitor processes of care required to report on this measure. Despite the major challenges of responding to SEP-1, quality leaders expressed optimism that increased attention to sepsis would ultimately lead to better patient outcomes.

How might future sepsis quality measures achieve the adequate balance between focusing attention on improving care processes for high-impact diseases, without imposing additional burdens on the healthcare system? Lessons from Barbash et al. help us move forward. First, rather than taxing hospitals with administratively complex process measures, initial attempts at quality measures should start simply. Policy makers should consider moving forward into new areas of quality measurement in 2 ways: (1) pursue 1 or 2 processes with strong etiological links to important patient outcomes (eg, timely antibiotics in septic shock),^25-28 and/or (2) use risk-adjusted outcomes and allow individual hospitals to adopt processes that improve local patient outcomes. Evidence suggests that the introduction of a quality measure may result in improved outcomes regardless of adoption of specific target processes,²⁹ although results are mixed.^30,31 In either case, complex “all or none” measures based upon weak evidence run a high risk of inciting clinician resentment and paradoxically perpetuating poor quality by increasing healthcare costs (decreased efficiency) without gains in safety, effectiveness, timeliness, or equity.³² It has been estimated that hospitals spend on average $2 million to implement SEP-1,³³ with unclear return on the investment. The experience of SEP-1 is a reminder that, as evidence evolves, quality measures must adapt lest they become irrelevant. However, it is also a reminder that quality measures should not sit precariously on the edge of evidence. Withdrawal of process-based measures due to a changing evidence landscape breeds mistrust and impairs future attempts to improve quality.

Sepsis quality measures face additional challenges. If recent experience with interpretation of sepsis definitions can serve as a guide, variable uptake of newer sepsis definitions between/across hospitals will impair the ability to risk-adjust outcome measures and increase bias in identifying outlier hospitals.³⁴ In addition, recent studies have already raised skepticism regarding the effectiveness of individual SEP-1 bundle components, confirming suspicions that the 30 cc/kg fluid bolus is not a magic quality target. Rather, the effectiveness of prior sepsis bundles has likely been driven by improved time to antibiotics, a process unstudied in sepsis trials, but driven by increased attention to the importance of early sepsis recognition and timely management.²⁸ Timeliness of antibiotics can act as an effect modifier for more complex sepsis therapies, with quicker time to antibiotics associated with reversal of previously described effectiveness of activated protein C,³⁵ and EGDT.²⁸

Sepsis has a legacy in which improving simple processes (ie, time to antibiotics) obviates the need for more complex interventions (eg, activated protein C, EGDT). To the extent that CMS remains committed to using process-based measures of quality, those focused on sepsis are likely to be most effective when pared down to the simplest and strongest evidence base—improved recognition³⁶ and timely antibiotics (for patients with infection-induced organ dysfunction and shock). Taking the time to start simply may best serve our current patients and preserve stakeholder buy-in for quality initiatives likely to benefit our future patients.

Disclosure

Dr. Lindenauer reports that he received support from the Centers for Medicare and Medicaid Services to develop and maintain hospital outcome measures for pneumonia and COPD. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. Dr. Walkey was supported by grants K01-HL116768 and R01-HL139751 from the National Heart, Lung, and Blood Institute.

“I didn’t have time to write a short letter, so I wrote a long one instead.”

-Mark Twain

Sepsis is a logical target for quality measures. Specifically, sepsis represents the perfect storm of immense public health burden^1-3 combined with unexplained practice^4-6 and outcomes⁷ variation. Thus, it is not surprising that in October 2015, the Centers of Medicare and Medicaid Services (CMS) adopted a sepsis quality measure.⁸ More surprising were the complex contents of the CMS Sepsis Core Measure “SEP-1” quality measure.⁹ CMS had written a “long letter.”

The multiple processes targeted with the CMS SEP-1 quality measure can best be understood with a brief account of history. SEP-1 arose from the National Quality Forum’s (NQF) project #0500: “Severe Sepsis and Septic Shock: Management Bundle,” a measure based upon Rivers et al.’s¹⁰ single-center, randomized, controlled trial of early goal-directed therapy (EGDT) for severe sepsis. EGDT was an intervention that consisted of fluid resuscitation and hemodynamic management based upon fulfilling specific targets of central venous pressure, superior vena cava oxygen saturation (or lactic acid), and hemoglobin and mean arterial pressures.¹¹ The large mortality benefits, physiological rationale, and algorithmic responses to a variety of abnormal clinical values provided an appealing protocol to critical care and emergency physicians trained to normalize measured values, as well as policy makers looking for quality measures. Observational studies consistently showed associations between adoption of guideline-based “sepsis bundles” and improved patient outcomes,^12-14 setting the stage for the transition of NQF #0500 into SEP-1.

However, the transition from EGDT-based NQF #0500 to SEP-1 has been tumultuous. Soon after adoption of SEP-1, the consensus definitions of sepsis changed markedly. Sepsis went from being defined as the presence of infection with concomitant systemic inflammatory response syndrome (sepsis), organ dysfunction (severe sepsis), and/or shock,¹⁵ to being defined as a dysregulated response to infection resulting in life-threatening organ dysfunction (sepsis) and/or fluid-resistant hypotension requiring vasopressors and lactate greater than 2 mmol/L.¹⁶ As the study by Barbash et al.¹⁷in this issue clearly outlines, conflicting definitions of “sepsis” have left clinicians confused regarding whom the SEP-1 measure should apply. At the same time, results of 3 large, international, randomized trials investigating the efficacy of EGDT were published, providing strong evidence that EGDT did not provide improved patient outcomes over usual care.¹⁸ SEP-1 adapted with the evolving evidence base, adding putative “usual care” processes such as evaluation of skin and peripheral pulses, and use of dynamic measures of fluid responsiveness, as quality measures.¹⁹ However, as Barbash et al. also outline, the resulting process measure was incredibly complex, with potentially more than 50 data elements collected over 6 hours in the initial management of sepsis.

In addition to its unprecedented complexity, SEP-1 received criticism for the weak evidence base of its individual components. The general concepts behind SEP-1 are well-accepted tenets of sepsis management: rapid recognition, assessment and treatment of underlying infection, and institution of intravenous fluids and vasopressor support for septic shock. However, the “all or none” prescriptive nature of the SEP-1 bundle was based on a somewhat arbitrary set of measures and targets. For example, patients with septic shock must receive 30 cc/kg of intravenous fluids to be “SEP-1 compliant.” The value “30 cc/kg” was taken from the average volume of fluids reported in prior sepsis trials, essentially based on a very low level of evidence.²⁰ The strict 30 cc/kg cutoff did not take into account that “the median isn’t the message”²¹ in fluid management: optimal resuscitation targets are unclear,²² and selecting the median as a target ignores the fact that 50% of patients enrolled in international trials of EGDT received less than 30 cc/kg of initial fluid resuscitation (the interquartile range was 16-42 cc/kg).¹⁸ Thus, most participants in trials upon which the SEP-1 fluid measure was based would ironically not have met the SEP-1 measure. Mandates for physical exam and physiological measures were based on similarly low levels of evidence.

Into this context, Barbash et al. use a representative sample of US hospitals to explore the opinions of hospital quality leaders regarding the SEP-1 measure. First, the qualitative methods used by Barbash et al. warrant some explanation. Much of biomedical research is characterized by hypothesis-driven, deductive reasoning: theories are tested using observations. In contrast, the methods of Barbash et al. use inductive reasoning: observations are used to develop theories within a systematic approach called “grounded theory” that explores common themes emerging from structured interviews.²³ Inductive reasoning can later inform deductive reasoning, feeding theories into testable hypotheses. However, qualitative, inductive research is not meant to test hypotheses and is not subject to typical notions of “power and sample size” often expected of quantitative statistical analyses. Qualitative studies reach sufficient sample size when no further themes emerge, a situation called “thematic saturation”; the sample size here of 29 participants rests comfortably in the range of participants commonly needed for thematic saturation.²³

Barbash et al. identified common themes in opinions of quality leaders regarding SEP-1. Namely, the complexity of SEP-1 necessitated a major resource investment into sepsis care and data collection. The major infrastructure investments needed to comply with SEP-1 also bred frustration regarding lack of perceived fairness around the “all or none” nature of the measure and raised multiple additional challenges including lack of clinician buy-in and resistance to protocolized care. Prior qualitative studies evaluating hospital quality leaders’ opinions on performance measures identified similar concerns about lack of “fairness,”²⁴ but the implementation of SEP-1 has raised additional concern regarding the large burdens of instituting major infrastructure changes to monitor processes of care required to report on this measure. Despite the major challenges of responding to SEP-1, quality leaders expressed optimism that increased attention to sepsis would ultimately lead to better patient outcomes.

How might future sepsis quality measures achieve the adequate balance between focusing attention on improving care processes for high-impact diseases, without imposing additional burdens on the healthcare system? Lessons from Barbash et al. help us move forward. First, rather than taxing hospitals with administratively complex process measures, initial attempts at quality measures should start simply. Policy makers should consider moving forward into new areas of quality measurement in 2 ways: (1) pursue 1 or 2 processes with strong etiological links to important patient outcomes (eg, timely antibiotics in septic shock),^25-28 and/or (2) use risk-adjusted outcomes and allow individual hospitals to adopt processes that improve local patient outcomes. Evidence suggests that the introduction of a quality measure may result in improved outcomes regardless of adoption of specific target processes,²⁹ although results are mixed.^30,31 In either case, complex “all or none” measures based upon weak evidence run a high risk of inciting clinician resentment and paradoxically perpetuating poor quality by increasing healthcare costs (decreased efficiency) without gains in safety, effectiveness, timeliness, or equity.³² It has been estimated that hospitals spend on average $2 million to implement SEP-1,³³ with unclear return on the investment. The experience of SEP-1 is a reminder that, as evidence evolves, quality measures must adapt lest they become irrelevant. However, it is also a reminder that quality measures should not sit precariously on the edge of evidence. Withdrawal of process-based measures due to a changing evidence landscape breeds mistrust and impairs future attempts to improve quality.

Sepsis quality measures face additional challenges. If recent experience with interpretation of sepsis definitions can serve as a guide, variable uptake of newer sepsis definitions between/across hospitals will impair the ability to risk-adjust outcome measures and increase bias in identifying outlier hospitals.³⁴ In addition, recent studies have already raised skepticism regarding the effectiveness of individual SEP-1 bundle components, confirming suspicions that the 30 cc/kg fluid bolus is not a magic quality target. Rather, the effectiveness of prior sepsis bundles has likely been driven by improved time to antibiotics, a process unstudied in sepsis trials, but driven by increased attention to the importance of early sepsis recognition and timely management.²⁸ Timeliness of antibiotics can act as an effect modifier for more complex sepsis therapies, with quicker time to antibiotics associated with reversal of previously described effectiveness of activated protein C,³⁵ and EGDT.²⁸

Sepsis has a legacy in which improving simple processes (ie, time to antibiotics) obviates the need for more complex interventions (eg, activated protein C, EGDT). To the extent that CMS remains committed to using process-based measures of quality, those focused on sepsis are likely to be most effective when pared down to the simplest and strongest evidence base—improved recognition³⁶ and timely antibiotics (for patients with infection-induced organ dysfunction and shock). Taking the time to start simply may best serve our current patients and preserve stakeholder buy-in for quality initiatives likely to benefit our future patients.

Disclosure

Dr. Lindenauer reports that he received support from the Centers for Medicare and Medicaid Services to develop and maintain hospital outcome measures for pneumonia and COPD. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. Dr. Walkey was supported by grants K01-HL116768 and R01-HL139751 from the National Heart, Lung, and Blood Institute.

“I didn’t have time to write a short letter, so I wrote a long one instead.”

-Mark Twain

Sepsis is a logical target for quality measures. Specifically, sepsis represents the perfect storm of immense public health burden^1-3 combined with unexplained practice^4-6 and outcomes⁷ variation. Thus, it is not surprising that in October 2015, the Centers of Medicare and Medicaid Services (CMS) adopted a sepsis quality measure.⁸ More surprising were the complex contents of the CMS Sepsis Core Measure “SEP-1” quality measure.⁹ CMS had written a “long letter.”

The multiple processes targeted with the CMS SEP-1 quality measure can best be understood with a brief account of history. SEP-1 arose from the National Quality Forum’s (NQF) project #0500: “Severe Sepsis and Septic Shock: Management Bundle,” a measure based upon Rivers et al.’s¹⁰ single-center, randomized, controlled trial of early goal-directed therapy (EGDT) for severe sepsis. EGDT was an intervention that consisted of fluid resuscitation and hemodynamic management based upon fulfilling specific targets of central venous pressure, superior vena cava oxygen saturation (or lactic acid), and hemoglobin and mean arterial pressures.¹¹ The large mortality benefits, physiological rationale, and algorithmic responses to a variety of abnormal clinical values provided an appealing protocol to critical care and emergency physicians trained to normalize measured values, as well as policy makers looking for quality measures. Observational studies consistently showed associations between adoption of guideline-based “sepsis bundles” and improved patient outcomes,^12-14 setting the stage for the transition of NQF #0500 into SEP-1.

However, the transition from EGDT-based NQF #0500 to SEP-1 has been tumultuous. Soon after adoption of SEP-1, the consensus definitions of sepsis changed markedly. Sepsis went from being defined as the presence of infection with concomitant systemic inflammatory response syndrome (sepsis), organ dysfunction (severe sepsis), and/or shock,¹⁵ to being defined as a dysregulated response to infection resulting in life-threatening organ dysfunction (sepsis) and/or fluid-resistant hypotension requiring vasopressors and lactate greater than 2 mmol/L.¹⁶ As the study by Barbash et al.¹⁷in this issue clearly outlines, conflicting definitions of “sepsis” have left clinicians confused regarding whom the SEP-1 measure should apply. At the same time, results of 3 large, international, randomized trials investigating the efficacy of EGDT were published, providing strong evidence that EGDT did not provide improved patient outcomes over usual care.¹⁸ SEP-1 adapted with the evolving evidence base, adding putative “usual care” processes such as evaluation of skin and peripheral pulses, and use of dynamic measures of fluid responsiveness, as quality measures.¹⁹ However, as Barbash et al. also outline, the resulting process measure was incredibly complex, with potentially more than 50 data elements collected over 6 hours in the initial management of sepsis.

In addition to its unprecedented complexity, SEP-1 received criticism for the weak evidence base of its individual components. The general concepts behind SEP-1 are well-accepted tenets of sepsis management: rapid recognition, assessment and treatment of underlying infection, and institution of intravenous fluids and vasopressor support for septic shock. However, the “all or none” prescriptive nature of the SEP-1 bundle was based on a somewhat arbitrary set of measures and targets. For example, patients with septic shock must receive 30 cc/kg of intravenous fluids to be “SEP-1 compliant.” The value “30 cc/kg” was taken from the average volume of fluids reported in prior sepsis trials, essentially based on a very low level of evidence.²⁰ The strict 30 cc/kg cutoff did not take into account that “the median isn’t the message”²¹ in fluid management: optimal resuscitation targets are unclear,²² and selecting the median as a target ignores the fact that 50% of patients enrolled in international trials of EGDT received less than 30 cc/kg of initial fluid resuscitation (the interquartile range was 16-42 cc/kg).¹⁸ Thus, most participants in trials upon which the SEP-1 fluid measure was based would ironically not have met the SEP-1 measure. Mandates for physical exam and physiological measures were based on similarly low levels of evidence.

Into this context, Barbash et al. use a representative sample of US hospitals to explore the opinions of hospital quality leaders regarding the SEP-1 measure. First, the qualitative methods used by Barbash et al. warrant some explanation. Much of biomedical research is characterized by hypothesis-driven, deductive reasoning: theories are tested using observations. In contrast, the methods of Barbash et al. use inductive reasoning: observations are used to develop theories within a systematic approach called “grounded theory” that explores common themes emerging from structured interviews.²³ Inductive reasoning can later inform deductive reasoning, feeding theories into testable hypotheses. However, qualitative, inductive research is not meant to test hypotheses and is not subject to typical notions of “power and sample size” often expected of quantitative statistical analyses. Qualitative studies reach sufficient sample size when no further themes emerge, a situation called “thematic saturation”; the sample size here of 29 participants rests comfortably in the range of participants commonly needed for thematic saturation.²³

Barbash et al. identified common themes in opinions of quality leaders regarding SEP-1. Namely, the complexity of SEP-1 necessitated a major resource investment into sepsis care and data collection. The major infrastructure investments needed to comply with SEP-1 also bred frustration regarding lack of perceived fairness around the “all or none” nature of the measure and raised multiple additional challenges including lack of clinician buy-in and resistance to protocolized care. Prior qualitative studies evaluating hospital quality leaders’ opinions on performance measures identified similar concerns about lack of “fairness,”²⁴ but the implementation of SEP-1 has raised additional concern regarding the large burdens of instituting major infrastructure changes to monitor processes of care required to report on this measure. Despite the major challenges of responding to SEP-1, quality leaders expressed optimism that increased attention to sepsis would ultimately lead to better patient outcomes.

How might future sepsis quality measures achieve the adequate balance between focusing attention on improving care processes for high-impact diseases, without imposing additional burdens on the healthcare system? Lessons from Barbash et al. help us move forward. First, rather than taxing hospitals with administratively complex process measures, initial attempts at quality measures should start simply. Policy makers should consider moving forward into new areas of quality measurement in 2 ways: (1) pursue 1 or 2 processes with strong etiological links to important patient outcomes (eg, timely antibiotics in septic shock),^25-28 and/or (2) use risk-adjusted outcomes and allow individual hospitals to adopt processes that improve local patient outcomes. Evidence suggests that the introduction of a quality measure may result in improved outcomes regardless of adoption of specific target processes,²⁹ although results are mixed.^30,31 In either case, complex “all or none” measures based upon weak evidence run a high risk of inciting clinician resentment and paradoxically perpetuating poor quality by increasing healthcare costs (decreased efficiency) without gains in safety, effectiveness, timeliness, or equity.³² It has been estimated that hospitals spend on average $2 million to implement SEP-1,³³ with unclear return on the investment. The experience of SEP-1 is a reminder that, as evidence evolves, quality measures must adapt lest they become irrelevant. However, it is also a reminder that quality measures should not sit precariously on the edge of evidence. Withdrawal of process-based measures due to a changing evidence landscape breeds mistrust and impairs future attempts to improve quality.

Sepsis quality measures face additional challenges. If recent experience with interpretation of sepsis definitions can serve as a guide, variable uptake of newer sepsis definitions between/across hospitals will impair the ability to risk-adjust outcome measures and increase bias in identifying outlier hospitals.³⁴ In addition, recent studies have already raised skepticism regarding the effectiveness of individual SEP-1 bundle components, confirming suspicions that the 30 cc/kg fluid bolus is not a magic quality target. Rather, the effectiveness of prior sepsis bundles has likely been driven by improved time to antibiotics, a process unstudied in sepsis trials, but driven by increased attention to the importance of early sepsis recognition and timely management.²⁸ Timeliness of antibiotics can act as an effect modifier for more complex sepsis therapies, with quicker time to antibiotics associated with reversal of previously described effectiveness of activated protein C,³⁵ and EGDT.²⁸

Sepsis has a legacy in which improving simple processes (ie, time to antibiotics) obviates the need for more complex interventions (eg, activated protein C, EGDT). To the extent that CMS remains committed to using process-based measures of quality, those focused on sepsis are likely to be most effective when pared down to the simplest and strongest evidence base—improved recognition³⁶ and timely antibiotics (for patients with infection-induced organ dysfunction and shock). Taking the time to start simply may best serve our current patients and preserve stakeholder buy-in for quality initiatives likely to benefit our future patients.

Disclosure

Dr. Lindenauer reports that he received support from the Centers for Medicare and Medicaid Services to develop and maintain hospital outcome measures for pneumonia and COPD. Dr. Lindenauer is supported by grant K24HL132008 from the National Heart, Lung, and Blood Institute. Dr. Walkey was supported by grants K01-HL116768 and R01-HL139751 from the National Heart, Lung, and Blood Institute.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

Cardiac biomarker testing, along with a thorough patient history, physical exam, and an electrocardiogram, is required for the diagnosis of patients with suspected acute coronary syndrome (ACS). For nearly 3 decades, 2 cardiac biomarkers, troponin (I or T) and creatine kinase-MB fraction (CK-MB), have been ordered together to evaluate ACS patients out of concern that utilizing a single biomarker might be less diagnostically accurate than using 2 biomarkers. However, subsequent studies have shown that troponin is far more sensitive and specific for myocardial injury than CK-MB.^1,2 Troponin testing offers important prognostic information irrespective of whether the CK-MB is normal or abnormal.^3,4 In 2015, the American Society of Clinical Pathology released a Choosing Wisely^® recommendation against ordering CK-MB (or myoglobin) for the diagnosis of acute myocardial infarction (AMI).⁵ This reflects an emerging consensus that CK-MB testing represents low-value care while troponin testing alone is the appropriate diagnostic strategy for ACS patients.

Remarkably, we know very little about patterns of cardiac biomarker utilization in clinical practice. In this issue of the Journal of Hospital Medicine, Prochaska et al.⁶ provide a valuable snapshot of troponin and CK-MB utilization at 91 U.S. academic medical centers (AMCs) for 18 months prior to and following the release of the 2015 Choosing Wisely^® recommendation. From a retrospective review of 106,954 inpatient discharges with a principal diagnosis of AMI, they report a 29.2% rate of troponin-only testing in 2013 with a gradual increase over 3 years to 53.5% in 2016. Interestingly, the study’s baseline troponin-only utilization rate is consistent with a 2013 College of American Pathologists survey, which estimated that 23% of U.S. clinical laboratories no longer process CK-MB (and therefore run troponins alone).⁷

Did the 2015 Choosing Wisely^® recommendation have an impact on providers choosing cardiac biomarkers wisely? The authors answer this question in a novel way by stratifying hospitals into performance tertiles for each study quarter and then further classifying them into groups that were consistently high, middle, and low performers throughout the study period. Using an interrupted time series design, they identify 26 hospitals who improved their troponin-only testing performance tertile during the study period and examine their average quarterly rate of change. As illustrated in Figure 3, they report a sharp increase in the rate of change of troponin-only testing shortly after the release of the 2015 Choosing Wisely^® recommendation. The authors reasonably conclude that the Choosing Wisely^® campaign “appeared to facilitate accelerated adoption of troponin-only testing” among these hospitals.

However, we should interpret these results with caution. The authors highlight several limitations, including the absence of causality common in observational studies and insufficient time to follow-up to capture the full (or transient) impact of the intervention. There are factors external to the Choosing Wisely^® campaign that may have influenced cardiac biomarker testing patterns observed. Examples include variation in hospital leadership, financial drivers, and local culture that promote high-value care. We also note that (1) there are several published interventions to improve troponin-only ordering that predate the Choosing Wisely^® campaign^8,9; (2) a prominent cardiology guideline endorsed the use of troponin as a preferred cardiac biomarker in 2012¹⁰; and (3) a widely cited opinion by prominent researchers called for the elimination of CK-MB from clinical practice in 2008.¹¹ These publications suggest there was already an awareness of and efforts underway to improve cardiac enzyme testing contributing to the results described by Prochaska et al.

Limitations notwithstanding, we commend Prochaska et al. for conducting the first-known description of patient-level trend rates of troponin and CK-MB testing. Finally, it is worth noting that where there is accomplishment, there is also opportunity. At the end of the study period, nearly 50% of institutions had yet to adopt a troponin-only strategy. While there has been an overall trend towards improvement, this number remains high. We may conjecture as to possible explanations: Providers may be unconvinced that a single troponin is sufficient in the diagnosis of ACS (ie, lack of knowledge or debate over the interpretation of available science), stakeholders may be slow to de-adopt practices using appropriate systems levers (eg, laboratories delisting CK-MB processing), and incentives may be lacking to motivate AMCs. The results of this study should be used as a burning platform to those who wish to “test wisely” in cardiac biomarker use.

Disclosure

The authors report no conflicts of interest or financial disclosures.

The question posed in the 1-Minute Consult by Zambrano and Burguera¹ in this issue of Cleveland Clinic Journal of Medicine forces us to evaluate the current management of one of our nation’s most costly and devastating health problems. On the front lines of this battle are primary care providers who face the challenge of delivering effective obesity counseling in a limited time frame.

See related article

Zambrano and Burguera highlight the 2011 Centers for Medicare and Medicaid Services reimbursement program for obesity counseling using intensive behavioral therapy.² The program supports and provides incentives in the form of time and reimbursement to primary care providers to discuss obesity with patients. But fewer than 1% of Medicare beneficiaries use the program.

While doctors often cite lack of time as a barrier to effectively counseling patients on weight, no clear evidence suggests that more time beyond the usual “5 minutes” of counseling is effective. The real issue is how a patient is counseled, not how long.

Physicians commonly resort to the simple message of “eat less and move more,” and tell patients that they “should” lose weight (as if patients with obesity don’t already know they should lose weight), which clearly is not helpful. Recently, a patient told me her primary care physician came into the examination room and told her that she needs to lose 15 to 20 pounds. “We can do it,” he said, clapped his hands, and left. This message is no more effective than telling a person with depression to “cheer up.”

WEIGHT BIAS

Zambrano and Burguera succinctly outline a targeted approach to reimbursable obesity counseling. But another obstacle to effective counseling that needs to be addressed is weight bias. Weight bias refers to negative attitudes and beliefs toward people with obesity and is common among healthcare professionals. Doctors too often believe people with obesity are lazy, eat too much, and lack the willpower to maintain a healthy diet. As a result, doctors may spend less time, have less discussion, and fail to consider effective treatment options for patients with obesity.

Weight loss is difficult for the patient and for the physician. Many still believe that people with obesity can ameliorate their condition simply by eating less. Rather than label the lack of weight loss or weight regain as a failure of the patient with obesity, we should consider this a poor response to the treatment. When chemotherapy is not effective or when someone requires insulin for their diabetes, do we blame the patient? There is a double standard for obesity, and it highlights a lack of understanding of obesity and weight bias. These historic beliefs are at odds with growing evidence indicating the pathogenesis of obesity involves a far more complex process, consisting of genetic, developmental, and environmental factors.³

LANGUAGE MATTERS

Obesity is not a lifestyle choice but rather a dysfunction of a highly regulated system. We need to help patients navigate the process of trying to lose weight in a nonjudgmental way, understanding that language matters. We should pay attention to our comments, recognizing that pejorative words (eg, morbid, fat) may contribute to patient shame and impair the effectiveness of behavioral change counseling. We need to self-identify negative assumptions and stereotypes and empathize with our patients. Learning about our own implicit bias through an online test (eg, Project Implicit⁴) and using “person-first” language (eg, “patient with obesity” instead of “obese patient”) are simple steps we can take to support our patients.⁵

REALISTIC EXPECTATIONS, EFFECTIVE OPTIONS

Setting expectations is crucial in the shared decision-making process. We need to be optimistic that a 5% to 10% loss of body weight can significantly improve many chronic diseases, but realistic that not everyone will respond the same way. Establishing 3- to 6-month end points is an appropriate way to gauge treatment response and pursue different treatment options in those who do not respond.

Antiobesity drugs may be effective combined with lifestyle interventions and may be considered in patients who have not responded to behavioral modification. Once thought to be a barbaric operation that should be reserved as a last resort, bariatric surgery remains the most effective treatment for obesity, resulting in a 20% to 35% body weight loss after 1 year. And a recent study showed sustained weight loss and effective remission and prevention of type 2 diabetes.⁶

To believe that all forms of obesity are the same and thus should have one treatment option is narrow-minded. We do not treat all cancers the same, nor do we treat all diabetes the same. Obesity is no different.

Effective obesity counseling in the limited time frame of an office visit is essential, but we also need to change the way we approach patients with obesity. We should pay attention to how we treat our patients with excess weight and empathize with their condition as we do with every other patient. We should be willing to treat obesity as the disease that it is and look beyond the scale. In the end, 20 minutes may not solve the problem, but it can begin the process.

The question posed in the 1-Minute Consult by Zambrano and Burguera¹ in this issue of Cleveland Clinic Journal of Medicine forces us to evaluate the current management of one of our nation’s most costly and devastating health problems. On the front lines of this battle are primary care providers who face the challenge of delivering effective obesity counseling in a limited time frame.

See related article

Zambrano and Burguera highlight the 2011 Centers for Medicare and Medicaid Services reimbursement program for obesity counseling using intensive behavioral therapy.² The program supports and provides incentives in the form of time and reimbursement to primary care providers to discuss obesity with patients. But fewer than 1% of Medicare beneficiaries use the program.

While doctors often cite lack of time as a barrier to effectively counseling patients on weight, no clear evidence suggests that more time beyond the usual “5 minutes” of counseling is effective. The real issue is how a patient is counseled, not how long.

Physicians commonly resort to the simple message of “eat less and move more,” and tell patients that they “should” lose weight (as if patients with obesity don’t already know they should lose weight), which clearly is not helpful. Recently, a patient told me her primary care physician came into the examination room and told her that she needs to lose 15 to 20 pounds. “We can do it,” he said, clapped his hands, and left. This message is no more effective than telling a person with depression to “cheer up.”

WEIGHT BIAS

Zambrano and Burguera succinctly outline a targeted approach to reimbursable obesity counseling. But another obstacle to effective counseling that needs to be addressed is weight bias. Weight bias refers to negative attitudes and beliefs toward people with obesity and is common among healthcare professionals. Doctors too often believe people with obesity are lazy, eat too much, and lack the willpower to maintain a healthy diet. As a result, doctors may spend less time, have less discussion, and fail to consider effective treatment options for patients with obesity.

Weight loss is difficult for the patient and for the physician. Many still believe that people with obesity can ameliorate their condition simply by eating less. Rather than label the lack of weight loss or weight regain as a failure of the patient with obesity, we should consider this a poor response to the treatment. When chemotherapy is not effective or when someone requires insulin for their diabetes, do we blame the patient? There is a double standard for obesity, and it highlights a lack of understanding of obesity and weight bias. These historic beliefs are at odds with growing evidence indicating the pathogenesis of obesity involves a far more complex process, consisting of genetic, developmental, and environmental factors.³

LANGUAGE MATTERS

Obesity is not a lifestyle choice but rather a dysfunction of a highly regulated system. We need to help patients navigate the process of trying to lose weight in a nonjudgmental way, understanding that language matters. We should pay attention to our comments, recognizing that pejorative words (eg, morbid, fat) may contribute to patient shame and impair the effectiveness of behavioral change counseling. We need to self-identify negative assumptions and stereotypes and empathize with our patients. Learning about our own implicit bias through an online test (eg, Project Implicit⁴) and using “person-first” language (eg, “patient with obesity” instead of “obese patient”) are simple steps we can take to support our patients.⁵

REALISTIC EXPECTATIONS, EFFECTIVE OPTIONS

Setting expectations is crucial in the shared decision-making process. We need to be optimistic that a 5% to 10% loss of body weight can significantly improve many chronic diseases, but realistic that not everyone will respond the same way. Establishing 3- to 6-month end points is an appropriate way to gauge treatment response and pursue different treatment options in those who do not respond.

Antiobesity drugs may be effective combined with lifestyle interventions and may be considered in patients who have not responded to behavioral modification. Once thought to be a barbaric operation that should be reserved as a last resort, bariatric surgery remains the most effective treatment for obesity, resulting in a 20% to 35% body weight loss after 1 year. And a recent study showed sustained weight loss and effective remission and prevention of type 2 diabetes.⁶

To believe that all forms of obesity are the same and thus should have one treatment option is narrow-minded. We do not treat all cancers the same, nor do we treat all diabetes the same. Obesity is no different.

Effective obesity counseling in the limited time frame of an office visit is essential, but we also need to change the way we approach patients with obesity. We should pay attention to how we treat our patients with excess weight and empathize with their condition as we do with every other patient. We should be willing to treat obesity as the disease that it is and look beyond the scale. In the end, 20 minutes may not solve the problem, but it can begin the process.

The question posed in the 1-Minute Consult by Zambrano and Burguera¹ in this issue of Cleveland Clinic Journal of Medicine forces us to evaluate the current management of one of our nation’s most costly and devastating health problems. On the front lines of this battle are primary care providers who face the challenge of delivering effective obesity counseling in a limited time frame.

See related article

Zambrano and Burguera highlight the 2011 Centers for Medicare and Medicaid Services reimbursement program for obesity counseling using intensive behavioral therapy.² The program supports and provides incentives in the form of time and reimbursement to primary care providers to discuss obesity with patients. But fewer than 1% of Medicare beneficiaries use the program.

While doctors often cite lack of time as a barrier to effectively counseling patients on weight, no clear evidence suggests that more time beyond the usual “5 minutes” of counseling is effective. The real issue is how a patient is counseled, not how long.

Physicians commonly resort to the simple message of “eat less and move more,” and tell patients that they “should” lose weight (as if patients with obesity don’t already know they should lose weight), which clearly is not helpful. Recently, a patient told me her primary care physician came into the examination room and told her that she needs to lose 15 to 20 pounds. “We can do it,” he said, clapped his hands, and left. This message is no more effective than telling a person with depression to “cheer up.”

WEIGHT BIAS

Zambrano and Burguera succinctly outline a targeted approach to reimbursable obesity counseling. But another obstacle to effective counseling that needs to be addressed is weight bias. Weight bias refers to negative attitudes and beliefs toward people with obesity and is common among healthcare professionals. Doctors too often believe people with obesity are lazy, eat too much, and lack the willpower to maintain a healthy diet. As a result, doctors may spend less time, have less discussion, and fail to consider effective treatment options for patients with obesity.

Weight loss is difficult for the patient and for the physician. Many still believe that people with obesity can ameliorate their condition simply by eating less. Rather than label the lack of weight loss or weight regain as a failure of the patient with obesity, we should consider this a poor response to the treatment. When chemotherapy is not effective or when someone requires insulin for their diabetes, do we blame the patient? There is a double standard for obesity, and it highlights a lack of understanding of obesity and weight bias. These historic beliefs are at odds with growing evidence indicating the pathogenesis of obesity involves a far more complex process, consisting of genetic, developmental, and environmental factors.³

LANGUAGE MATTERS

Obesity is not a lifestyle choice but rather a dysfunction of a highly regulated system. We need to help patients navigate the process of trying to lose weight in a nonjudgmental way, understanding that language matters. We should pay attention to our comments, recognizing that pejorative words (eg, morbid, fat) may contribute to patient shame and impair the effectiveness of behavioral change counseling. We need to self-identify negative assumptions and stereotypes and empathize with our patients. Learning about our own implicit bias through an online test (eg, Project Implicit⁴) and using “person-first” language (eg, “patient with obesity” instead of “obese patient”) are simple steps we can take to support our patients.⁵

REALISTIC EXPECTATIONS, EFFECTIVE OPTIONS

Setting expectations is crucial in the shared decision-making process. We need to be optimistic that a 5% to 10% loss of body weight can significantly improve many chronic diseases, but realistic that not everyone will respond the same way. Establishing 3- to 6-month end points is an appropriate way to gauge treatment response and pursue different treatment options in those who do not respond.

Antiobesity drugs may be effective combined with lifestyle interventions and may be considered in patients who have not responded to behavioral modification. Once thought to be a barbaric operation that should be reserved as a last resort, bariatric surgery remains the most effective treatment for obesity, resulting in a 20% to 35% body weight loss after 1 year. And a recent study showed sustained weight loss and effective remission and prevention of type 2 diabetes.⁶

To believe that all forms of obesity are the same and thus should have one treatment option is narrow-minded. We do not treat all cancers the same, nor do we treat all diabetes the same. Obesity is no different.

Effective obesity counseling in the limited time frame of an office visit is essential, but we also need to change the way we approach patients with obesity. We should pay attention to how we treat our patients with excess weight and empathize with their condition as we do with every other patient. We should be willing to treat obesity as the disease that it is and look beyond the scale. In the end, 20 minutes may not solve the problem, but it can begin the process.

Quality improvement is a key component of hospital medicine. The naïve assumption implicit in many quality improvement efforts is that physicians are highly trained scientists who, when shown a better way with a new practice guideline, will logically change their practice accordingly. In real life, mere education often doesn’t change behavior. This human quirk is an endless surprise to some physicians but is just standard fare for those with a Master’s of Business Administration.

This has especially been true when the change involves eliminating ineffective practices when there are no economic incentives to replace them with a new drug or test. For instance, the prescription of inappropriate antibiotics for adults with bronchitis1 remained unchanged despite 40 years of scientific evidence that the practice is ineffective, although there is clear evidence that it leads to dangerous antibiotic resistance, and regardless of 15 years of educational efforts by the government.

A common paradigm for progress is Everett Rogers’ theory on the diffusion of innovation.2 There are innovators and early adopters for any new idea and also laggards. When the innovation involves clinical decision making, research shows that human thought processes are not necessarily linear or logical.3 Changing prescribing habits is difficult. Various methodologies can be used to nudge4 people to modify their behavior. I recommend that all hospitalists who perform quality improvement read the 3 books cited in this paragraph. (Better yet, read an executive summary of each of the books. The original books are long and repetitive.)

The Value in Pediatrics (VIP) bronchiolitis collaborative created a virtual peer group to share experiences, benchmark process measures, and collectively problem solve issues in order to provide evidence-based care for infants with bronchiolitis. Their efforts were successful and published in January 2016.5 The multicenter project markedly reduced use, at their home institutions, of unnecessary and ineffective treatments. Those bootstrap efforts in hospital medicine compare favorably with the gigantic 4-year study6 published a month later, which documents similar efforts of a Primary Care Practice Research Network project to reduce inappropriate prescribing of antibiotics for simple upper respiratory infections in the outpatient world. There are many parallels between those 2 projects. Both yield insight into management methods that can reduce overtreatment.

The next logical question that a skeptical hospital Chief Executive Officer would ask is, “Will these improved behaviors continue once the research projects are over?” All doctors are familiar with backsliding when it comes to alcoholism, smoking, and dieting. Bad habits often return.

The first sentence of the discussion section in the article by Shadman et al.7 says it all. “To our knowledge, this is the first report of sustained improvements in care achieved through a multiinstitutional quality improvement collaborative of community and academic hospitals focused on bronchiolitis care.” The history of medicine has many examples where a multicenter study has led to the adoption of new treatments or new diagnostic tests. The typical progress of medicine has been the replacement of less effective treatments with better ones. But it is rare and difficult to eliminate, without substitution, ineffective treatments once they are in widespread use. This is the challenge facing the Choosing Wisely™ approach. Established habits of overtesting, overdiagnosis and overtreatment are refractory to correction, other than by replacing retirees with a new generation of physicians.

The confirmation that the previously announced improvements are being sustained will encourage other hospital groups to adopt some of the management methodology of the VIP bronchiolitis collaborative. The collaborative aimed to change medical practice but didn’t identify which of the many management techniques it employed led to behaviors being sustainably changed. The aforementioned much larger (and far more expensive) outpatient project by Meeker et al.⁶ was designed to tease out which of 3 management methodologies promoted the most change. I anticipate those authors will publish their sustainability data in the near future.

The Shadman et al.⁷ article is limited by weak statistical measures. The P values for the sustainability in the bottom row of Table 1 probe whether any backsliding was statistically different from 0. Because there are no corresponding power calculations, I don’t find those helpful. Given that only 9 centers continued to submit data, the lack of statistical significance may reflect wide error bars rather than small changes in clinical behavior. However, by comparing the confidence intervals for the process measures during the sustainability period to the means at baseline, one can deduce that clinically significant changes were achieved and that clinically significant backsliding did not occur over the following year.

Another limitation is that the 9 hospitals involved were still collecting and submitting data. As a result, the Hawthorne Effect (people behave differently when they know they are being observed) is still very active and may temporarily be preventing regression in behavior.

The study authors admit the limitation that there may be selection bias in the groups that chose to work the extra year. The authors do a reasonable job trying to find evidence of that selection bias and don’t find it. However, all participants in the original study were self selected and dedicated to a cause, so extrapolating these results to less motivated physician groups may be suspect. Despite those limitations, the evidence for sustainability in eliminating overtreatment is encouraging for anyone involved in Choosing Wisely™endeavors.

Disclosure

The author reports no conflicts of interest.

Quality improvement is a key component of hospital medicine. The naïve assumption implicit in many quality improvement efforts is that physicians are highly trained scientists who, when shown a better way with a new practice guideline, will logically change their practice accordingly. In real life, mere education often doesn’t change behavior. This human quirk is an endless surprise to some physicians but is just standard fare for those with a Master’s of Business Administration.

This has especially been true when the change involves eliminating ineffective practices when there are no economic incentives to replace them with a new drug or test. For instance, the prescription of inappropriate antibiotics for adults with bronchitis1 remained unchanged despite 40 years of scientific evidence that the practice is ineffective, although there is clear evidence that it leads to dangerous antibiotic resistance, and regardless of 15 years of educational efforts by the government.

A common paradigm for progress is Everett Rogers’ theory on the diffusion of innovation.2 There are innovators and early adopters for any new idea and also laggards. When the innovation involves clinical decision making, research shows that human thought processes are not necessarily linear or logical.3 Changing prescribing habits is difficult. Various methodologies can be used to nudge4 people to modify their behavior. I recommend that all hospitalists who perform quality improvement read the 3 books cited in this paragraph. (Better yet, read an executive summary of each of the books. The original books are long and repetitive.)

The Value in Pediatrics (VIP) bronchiolitis collaborative created a virtual peer group to share experiences, benchmark process measures, and collectively problem solve issues in order to provide evidence-based care for infants with bronchiolitis. Their efforts were successful and published in January 2016.5 The multicenter project markedly reduced use, at their home institutions, of unnecessary and ineffective treatments. Those bootstrap efforts in hospital medicine compare favorably with the gigantic 4-year study6 published a month later, which documents similar efforts of a Primary Care Practice Research Network project to reduce inappropriate prescribing of antibiotics for simple upper respiratory infections in the outpatient world. There are many parallels between those 2 projects. Both yield insight into management methods that can reduce overtreatment.

The next logical question that a skeptical hospital Chief Executive Officer would ask is, “Will these improved behaviors continue once the research projects are over?” All doctors are familiar with backsliding when it comes to alcoholism, smoking, and dieting. Bad habits often return.

The first sentence of the discussion section in the article by Shadman et al.7 says it all. “To our knowledge, this is the first report of sustained improvements in care achieved through a multiinstitutional quality improvement collaborative of community and academic hospitals focused on bronchiolitis care.” The history of medicine has many examples where a multicenter study has led to the adoption of new treatments or new diagnostic tests. The typical progress of medicine has been the replacement of less effective treatments with better ones. But it is rare and difficult to eliminate, without substitution, ineffective treatments once they are in widespread use. This is the challenge facing the Choosing Wisely™ approach. Established habits of overtesting, overdiagnosis and overtreatment are refractory to correction, other than by replacing retirees with a new generation of physicians.

The confirmation that the previously announced improvements are being sustained will encourage other hospital groups to adopt some of the management methodology of the VIP bronchiolitis collaborative. The collaborative aimed to change medical practice but didn’t identify which of the many management techniques it employed led to behaviors being sustainably changed. The aforementioned much larger (and far more expensive) outpatient project by Meeker et al.⁶ was designed to tease out which of 3 management methodologies promoted the most change. I anticipate those authors will publish their sustainability data in the near future.

The Shadman et al.⁷ article is limited by weak statistical measures. The P values for the sustainability in the bottom row of Table 1 probe whether any backsliding was statistically different from 0. Because there are no corresponding power calculations, I don’t find those helpful. Given that only 9 centers continued to submit data, the lack of statistical significance may reflect wide error bars rather than small changes in clinical behavior. However, by comparing the confidence intervals for the process measures during the sustainability period to the means at baseline, one can deduce that clinically significant changes were achieved and that clinically significant backsliding did not occur over the following year.

Another limitation is that the 9 hospitals involved were still collecting and submitting data. As a result, the Hawthorne Effect (people behave differently when they know they are being observed) is still very active and may temporarily be preventing regression in behavior.

The study authors admit the limitation that there may be selection bias in the groups that chose to work the extra year. The authors do a reasonable job trying to find evidence of that selection bias and don’t find it. However, all participants in the original study were self selected and dedicated to a cause, so extrapolating these results to less motivated physician groups may be suspect. Despite those limitations, the evidence for sustainability in eliminating overtreatment is encouraging for anyone involved in Choosing Wisely™endeavors.

Disclosure

The author reports no conflicts of interest.

Quality improvement is a key component of hospital medicine. The naïve assumption implicit in many quality improvement efforts is that physicians are highly trained scientists who, when shown a better way with a new practice guideline, will logically change their practice accordingly. In real life, mere education often doesn’t change behavior. This human quirk is an endless surprise to some physicians but is just standard fare for those with a Master’s of Business Administration.

This has especially been true when the change involves eliminating ineffective practices when there are no economic incentives to replace them with a new drug or test. For instance, the prescription of inappropriate antibiotics for adults with bronchitis1 remained unchanged despite 40 years of scientific evidence that the practice is ineffective, although there is clear evidence that it leads to dangerous antibiotic resistance, and regardless of 15 years of educational efforts by the government.

A common paradigm for progress is Everett Rogers’ theory on the diffusion of innovation.2 There are innovators and early adopters for any new idea and also laggards. When the innovation involves clinical decision making, research shows that human thought processes are not necessarily linear or logical.3 Changing prescribing habits is difficult. Various methodologies can be used to nudge4 people to modify their behavior. I recommend that all hospitalists who perform quality improvement read the 3 books cited in this paragraph. (Better yet, read an executive summary of each of the books. The original books are long and repetitive.)

The Value in Pediatrics (VIP) bronchiolitis collaborative created a virtual peer group to share experiences, benchmark process measures, and collectively problem solve issues in order to provide evidence-based care for infants with bronchiolitis. Their efforts were successful and published in January 2016.5 The multicenter project markedly reduced use, at their home institutions, of unnecessary and ineffective treatments. Those bootstrap efforts in hospital medicine compare favorably with the gigantic 4-year study6 published a month later, which documents similar efforts of a Primary Care Practice Research Network project to reduce inappropriate prescribing of antibiotics for simple upper respiratory infections in the outpatient world. There are many parallels between those 2 projects. Both yield insight into management methods that can reduce overtreatment.

The next logical question that a skeptical hospital Chief Executive Officer would ask is, “Will these improved behaviors continue once the research projects are over?” All doctors are familiar with backsliding when it comes to alcoholism, smoking, and dieting. Bad habits often return.

The first sentence of the discussion section in the article by Shadman et al.7 says it all. “To our knowledge, this is the first report of sustained improvements in care achieved through a multiinstitutional quality improvement collaborative of community and academic hospitals focused on bronchiolitis care.” The history of medicine has many examples where a multicenter study has led to the adoption of new treatments or new diagnostic tests. The typical progress of medicine has been the replacement of less effective treatments with better ones. But it is rare and difficult to eliminate, without substitution, ineffective treatments once they are in widespread use. This is the challenge facing the Choosing Wisely™ approach. Established habits of overtesting, overdiagnosis and overtreatment are refractory to correction, other than by replacing retirees with a new generation of physicians.

The confirmation that the previously announced improvements are being sustained will encourage other hospital groups to adopt some of the management methodology of the VIP bronchiolitis collaborative. The collaborative aimed to change medical practice but didn’t identify which of the many management techniques it employed led to behaviors being sustainably changed. The aforementioned much larger (and far more expensive) outpatient project by Meeker et al.⁶ was designed to tease out which of 3 management methodologies promoted the most change. I anticipate those authors will publish their sustainability data in the near future.

The Shadman et al.⁷ article is limited by weak statistical measures. The P values for the sustainability in the bottom row of Table 1 probe whether any backsliding was statistically different from 0. Because there are no corresponding power calculations, I don’t find those helpful. Given that only 9 centers continued to submit data, the lack of statistical significance may reflect wide error bars rather than small changes in clinical behavior. However, by comparing the confidence intervals for the process measures during the sustainability period to the means at baseline, one can deduce that clinically significant changes were achieved and that clinically significant backsliding did not occur over the following year.

Another limitation is that the 9 hospitals involved were still collecting and submitting data. As a result, the Hawthorne Effect (people behave differently when they know they are being observed) is still very active and may temporarily be preventing regression in behavior.

The study authors admit the limitation that there may be selection bias in the groups that chose to work the extra year. The authors do a reasonable job trying to find evidence of that selection bias and don’t find it. However, all participants in the original study were self selected and dedicated to a cause, so extrapolating these results to less motivated physician groups may be suspect. Despite those limitations, the evidence for sustainability in eliminating overtreatment is encouraging for anyone involved in Choosing Wisely™endeavors.

Disclosure

The author reports no conflicts of interest.

Health literacy (HL) is the ability of individuals to obtain, process, and understand health information in a way that enables them to make health decisions.¹ Approximately one-third of adults in the United States are considered to have inadequate HL,² and its prevalence is even higher among hospitalized patients.³ Low HL has been associated with higher rates of hospital readmission⁴ and higher mortality.^5,6 Inadequate HL has been identified as a barrier to communication and is associated with poorer outcomes for communication-sensitive behaviors, such as adherence to medications, chronic disease self-efficacy and self-management,^7-10 and understanding hospital discharge instructions.^11,12 It has been largely understood that the association between HL and hospital outcomes has been mediated by these communication challenges.

In this issue of the journal, Boyle et al.¹³ demonstrate that inadequate HL is not only a communication barrier but also an indicator of other social support needs during a transition from the hospital. In particular, the authors found that hospitalized patients with inadequate HL had needs in more social support domains than those with adequate HL. After multivariable adjustment for sociodemographic factors that likely impact social support, such as age and marital status, inadequate HL remained associated specifically with insufficient caregiver support and transportation barriers. These findings suggest that, along with the more direct comprehension barriers previously associated with inadequate HL, the identified social support needs may mediate prior established associations between inadequate HL and poor health outcomes.

The authors concluded that screening for HL along with transitional care needs will allow hospitals to ensure a quality care transition. Indeed, screening for these gaps is the first step in identifying important postdischarge social needs and will be necessary in order to track improvements for at-risk populations. However, screening alone will not likely change outcomes; for this, we will need effective interventions.

In fact, it remains an open question how best to intervene to improve care transitions for patients with social needs and low HL. The recent focus of HL interventions in the literature has been on “universal precautions,” such as the teach-back technique, to ensure patient comprehension of information, and writing patient informational materials at a low literacy level.¹⁴This approach to make all materials and communication accessible to all patients, rather than to tailor HL interventions, has become more prevalent in efforts to address the adverse communication and resultant health impacts of inadequate HL.^15-17

Meanwhile, the focus of care transition interventions has been on transition coaching or case management in the hospital, medication reconciliation prior to discharge, and postdischarge telephone calls from pharmacists or nurses, often utilizing the HL “universal precautions.”^18-20 While these approaches have been impactful to improve discharge preparedness and decrease readmission rates,²¹ they may not adequately address individual social support and social service needs when the patient leaves the hospital.

Recently, the National Academy of Medicine published the Accountable Health Community Screening Tool, designed to screen for the following 5 areas of unmet social need that are known to be impactful for health: housing stability, food insecurity, transportation needs, utility needs, and interpersonal violence.²² This screener is being used as part of the Center for Medicare & Medicaid Services’ Accountable Health Communities Model and is being tested by the Center for Medicare and Medicaid Innovation (CMMI). The goal of the CMMI evaluation is to test whether systematically identifying social service needs and closing the gap between clinical care and community services for patients with the highest levels of need will improve health outcomes.

Screening for HL and social determinants in the hospital will not, in and of itself, improve the quality of care transitions or prevent subsequent readmissions, morbidity, or mortality. However, measurement is the first step toward identifying individuals with the greatest need and can help direct hospitals’ utilization of limited resources, such as transition managers. The CMMI Accountable Health Communities Model evaluation will provide hospital and healthcare systems with best practices for building clinical–social services networks and connecting at-risk patients with high levels of need to appropriate services in the community.

No longer can a patient’s hospital care end with writing prescriptions and scheduling follow-up appointments. For some, using teach-back and low literacy-appropriate discharge materials will be enough; others will require a postdischarge telephone call to review medications and symptoms and ensure follow-up. But for those highest-risk patients, connection to a network of ongoing community social support will be necessary to guide their transition back to health in the community.

Disclosure 

The author reports no conflicts of interest.

Health literacy (HL) is the ability of individuals to obtain, process, and understand health information in a way that enables them to make health decisions.¹ Approximately one-third of adults in the United States are considered to have inadequate HL,² and its prevalence is even higher among hospitalized patients.³ Low HL has been associated with higher rates of hospital readmission⁴ and higher mortality.^5,6 Inadequate HL has been identified as a barrier to communication and is associated with poorer outcomes for communication-sensitive behaviors, such as adherence to medications, chronic disease self-efficacy and self-management,^7-10 and understanding hospital discharge instructions.^11,12 It has been largely understood that the association between HL and hospital outcomes has been mediated by these communication challenges.

In this issue of the journal, Boyle et al.¹³ demonstrate that inadequate HL is not only a communication barrier but also an indicator of other social support needs during a transition from the hospital. In particular, the authors found that hospitalized patients with inadequate HL had needs in more social support domains than those with adequate HL. After multivariable adjustment for sociodemographic factors that likely impact social support, such as age and marital status, inadequate HL remained associated specifically with insufficient caregiver support and transportation barriers. These findings suggest that, along with the more direct comprehension barriers previously associated with inadequate HL, the identified social support needs may mediate prior established associations between inadequate HL and poor health outcomes.

The authors concluded that screening for HL along with transitional care needs will allow hospitals to ensure a quality care transition. Indeed, screening for these gaps is the first step in identifying important postdischarge social needs and will be necessary in order to track improvements for at-risk populations. However, screening alone will not likely change outcomes; for this, we will need effective interventions.

In fact, it remains an open question how best to intervene to improve care transitions for patients with social needs and low HL. The recent focus of HL interventions in the literature has been on “universal precautions,” such as the teach-back technique, to ensure patient comprehension of information, and writing patient informational materials at a low literacy level.¹⁴This approach to make all materials and communication accessible to all patients, rather than to tailor HL interventions, has become more prevalent in efforts to address the adverse communication and resultant health impacts of inadequate HL.^15-17

Meanwhile, the focus of care transition interventions has been on transition coaching or case management in the hospital, medication reconciliation prior to discharge, and postdischarge telephone calls from pharmacists or nurses, often utilizing the HL “universal precautions.”^18-20 While these approaches have been impactful to improve discharge preparedness and decrease readmission rates,²¹ they may not adequately address individual social support and social service needs when the patient leaves the hospital.

Recently, the National Academy of Medicine published the Accountable Health Community Screening Tool, designed to screen for the following 5 areas of unmet social need that are known to be impactful for health: housing stability, food insecurity, transportation needs, utility needs, and interpersonal violence.²² This screener is being used as part of the Center for Medicare & Medicaid Services’ Accountable Health Communities Model and is being tested by the Center for Medicare and Medicaid Innovation (CMMI). The goal of the CMMI evaluation is to test whether systematically identifying social service needs and closing the gap between clinical care and community services for patients with the highest levels of need will improve health outcomes.

Screening for HL and social determinants in the hospital will not, in and of itself, improve the quality of care transitions or prevent subsequent readmissions, morbidity, or mortality. However, measurement is the first step toward identifying individuals with the greatest need and can help direct hospitals’ utilization of limited resources, such as transition managers. The CMMI Accountable Health Communities Model evaluation will provide hospital and healthcare systems with best practices for building clinical–social services networks and connecting at-risk patients with high levels of need to appropriate services in the community.

No longer can a patient’s hospital care end with writing prescriptions and scheduling follow-up appointments. For some, using teach-back and low literacy-appropriate discharge materials will be enough; others will require a postdischarge telephone call to review medications and symptoms and ensure follow-up. But for those highest-risk patients, connection to a network of ongoing community social support will be necessary to guide their transition back to health in the community.

Disclosure 

The author reports no conflicts of interest.

Health literacy (HL) is the ability of individuals to obtain, process, and understand health information in a way that enables them to make health decisions.¹ Approximately one-third of adults in the United States are considered to have inadequate HL,² and its prevalence is even higher among hospitalized patients.³ Low HL has been associated with higher rates of hospital readmission⁴ and higher mortality.^5,6 Inadequate HL has been identified as a barrier to communication and is associated with poorer outcomes for communication-sensitive behaviors, such as adherence to medications, chronic disease self-efficacy and self-management,^7-10 and understanding hospital discharge instructions.^11,12 It has been largely understood that the association between HL and hospital outcomes has been mediated by these communication challenges.

In this issue of the journal, Boyle et al.¹³ demonstrate that inadequate HL is not only a communication barrier but also an indicator of other social support needs during a transition from the hospital. In particular, the authors found that hospitalized patients with inadequate HL had needs in more social support domains than those with adequate HL. After multivariable adjustment for sociodemographic factors that likely impact social support, such as age and marital status, inadequate HL remained associated specifically with insufficient caregiver support and transportation barriers. These findings suggest that, along with the more direct comprehension barriers previously associated with inadequate HL, the identified social support needs may mediate prior established associations between inadequate HL and poor health outcomes.

The authors concluded that screening for HL along with transitional care needs will allow hospitals to ensure a quality care transition. Indeed, screening for these gaps is the first step in identifying important postdischarge social needs and will be necessary in order to track improvements for at-risk populations. However, screening alone will not likely change outcomes; for this, we will need effective interventions.

In fact, it remains an open question how best to intervene to improve care transitions for patients with social needs and low HL. The recent focus of HL interventions in the literature has been on “universal precautions,” such as the teach-back technique, to ensure patient comprehension of information, and writing patient informational materials at a low literacy level.¹⁴This approach to make all materials and communication accessible to all patients, rather than to tailor HL interventions, has become more prevalent in efforts to address the adverse communication and resultant health impacts of inadequate HL.^15-17

Meanwhile, the focus of care transition interventions has been on transition coaching or case management in the hospital, medication reconciliation prior to discharge, and postdischarge telephone calls from pharmacists or nurses, often utilizing the HL “universal precautions.”^18-20 While these approaches have been impactful to improve discharge preparedness and decrease readmission rates,²¹ they may not adequately address individual social support and social service needs when the patient leaves the hospital.

Recently, the National Academy of Medicine published the Accountable Health Community Screening Tool, designed to screen for the following 5 areas of unmet social need that are known to be impactful for health: housing stability, food insecurity, transportation needs, utility needs, and interpersonal violence.²² This screener is being used as part of the Center for Medicare & Medicaid Services’ Accountable Health Communities Model and is being tested by the Center for Medicare and Medicaid Innovation (CMMI). The goal of the CMMI evaluation is to test whether systematically identifying social service needs and closing the gap between clinical care and community services for patients with the highest levels of need will improve health outcomes.

Screening for HL and social determinants in the hospital will not, in and of itself, improve the quality of care transitions or prevent subsequent readmissions, morbidity, or mortality. However, measurement is the first step toward identifying individuals with the greatest need and can help direct hospitals’ utilization of limited resources, such as transition managers. The CMMI Accountable Health Communities Model evaluation will provide hospital and healthcare systems with best practices for building clinical–social services networks and connecting at-risk patients with high levels of need to appropriate services in the community.

No longer can a patient’s hospital care end with writing prescriptions and scheduling follow-up appointments. For some, using teach-back and low literacy-appropriate discharge materials will be enough; others will require a postdischarge telephone call to review medications and symptoms and ensure follow-up. But for those highest-risk patients, connection to a network of ongoing community social support will be necessary to guide their transition back to health in the community.

Disclosure 

The author reports no conflicts of interest.

Patient satisfaction and the ability to effectively communicate with hospitalized patients has become a core tenet to providing high-quality healthcare. Over the past few decades, medicine has gradually moved away from many paternalistic practices, and the profession has sought to engage patients as true partners in their own care. It is in this setting that effective communication has risen to be a key factor in the patient and provider relationship. It has also become a closely monitored quality metric tied to financial incentives and penalties. Most importantly, it has been well documented that failures in communication are a frequent cause of adverse events that compromise the ability of healthcare providers to provide safe and effective care.¹ It is in this climate that healthcare systems have worked to implement solutions designed to engage patients and their families to improve their healthcare experience. These solutions vary from low to high tech and include patient whiteboards, provider face cards, and web-based patient portals. Despite the numerous innovative solutions being implemented by hospitalists, studies supporting their effectiveness are few. There continues to be limited evidence on the value of these practices and whether they positively impact the desired outcomes of patient satisfaction and engagement.

In this issue of the Journal of Hospital Medicine, Goyal et al.² performed a systematic review to evaluate whether the use of bedside visual tools for hospitalized medical patients impacts patient satisfaction, patient–provider communication, and provider identification and understanding of roles. The authors were able to identify 16 studies that evaluated the use of these tools, which included provider face cards and whiteboards. The majority of the studies reviewed showed a positive effect on provider identification, understanding providers’ role, and patient satisfaction. The authors found that of the tools evaluated, whiteboards and picture-based techniques were the most effective visually based interventions. However, the authors also highlighted the difficulty in identifying 1 optimal approach to the use of these tools as a result of variations in content, format, and outcome measurement.

Variation in the use of visual tools to improve communication and patient satisfaction limits the ability to identify and evaluate the most effective approaches to their use. Without a streamlined approach, these tools may not produce the desired effect of improving patient and provider communication, which is essential in providing high-quality inpatient care and ensuring patient satisfaction. It has been documented that many patients cannot even identify their providers in the hospital setting, which limits the ability of the patient to be fully engaged in decisions made about their care.³ In addition, substantial portions of hospitalized patients do not understand their plan of care.⁴ Patients’ understanding of their plan of care is essential for patients to provide informed consent for hospital treatments and better prepare them to assume their own care after discharge, with a full understanding of their diagnosis.⁵ It has become increasingly clear that healthcare providers must incorporate effective approaches in their daily workflow to address these findings.

Aside from patient satisfaction and engagement, the effect communications failures have on patient safety have been evaluated and recognized. From the National Academy of Medicine’s report emphasizing patient-centered care to the addition of patients’ active engagement in their care as a National Patient Safety Goal by The Joint Commission, the medical field has committed to a continued focus in this area.^5,6

The business case can also be made for identifying effective tools that improve patient satisfaction and patient–provider communication. Private and public health insurance providers have incentivized high performance in these areas and have now begun to levy penalties for underperformers. As patients’ level of satisfaction and engagement continue to be assessed via patient surveys, healthcare systems continue to search for effective practices to improve performance in patient-perceived provider communication. Patients’ reporting of their assessment of nurse and physician communication through questions such as “How often did nurses/doctors explain things in a way you could understand?” will continue to be a moving target requiring future studies of effective interventions

Are visual aids the effective tools that hospitals need to improve communication and patient satisfaction, or are they merely decorations? The whiteboard provides an excellent example of the effectiveness that can be seen with the use of these tools. Used to improve patient-provider communication in medicine, the whiteboard has become almost ubiquitous in patient hospital rooms.⁷ It is now an expected aspect of hospital design and has inspired the development of higher tech solutions, including patient tablets and media walls. It is known to enhance the interaction for both the provider and patient and facilitate the exchange of complicated medical information within an anxiety prone environment in a simple manner by using short phrases or drawings.⁶ Yet, there is a scarcity of strong evidence to support the most effective approach to the use of whiteboards in improving patient satisfaction and communication. Standardizing how the whiteboard is used during the patient interaction will allow for the effectiveness of this tool to be realized and evaluated and prevent it from becoming another ornamental fixture on our hospital walls.

The systematic review by Goyal et al.² is a necessary step in the evaluation of common communication tools for their effectiveness and ability to improve patient satisfaction. This exhaustive review of key studies in this area is an excellent addition to the current literature, which has a paucity of extensive evaluations of these approaches. It provides an important signal that visual tools are more than decorative and can be effective when a streamlined approach is utilized. It highlights the importance of identifying effective best practices for the use of these tools that can be studied empirically and subsequently disseminated for widespread use. Continued work is necessary to fill this void and to enable healthcare professionals to provide the highest level of safe, effective, and engaging care that our patients deserve.

Disclosure

The authors have no conflicts of interest.

Patient satisfaction and the ability to effectively communicate with hospitalized patients has become a core tenet to providing high-quality healthcare. Over the past few decades, medicine has gradually moved away from many paternalistic practices, and the profession has sought to engage patients as true partners in their own care. It is in this setting that effective communication has risen to be a key factor in the patient and provider relationship. It has also become a closely monitored quality metric tied to financial incentives and penalties. Most importantly, it has been well documented that failures in communication are a frequent cause of adverse events that compromise the ability of healthcare providers to provide safe and effective care.¹ It is in this climate that healthcare systems have worked to implement solutions designed to engage patients and their families to improve their healthcare experience. These solutions vary from low to high tech and include patient whiteboards, provider face cards, and web-based patient portals. Despite the numerous innovative solutions being implemented by hospitalists, studies supporting their effectiveness are few. There continues to be limited evidence on the value of these practices and whether they positively impact the desired outcomes of patient satisfaction and engagement.

In this issue of the Journal of Hospital Medicine, Goyal et al.² performed a systematic review to evaluate whether the use of bedside visual tools for hospitalized medical patients impacts patient satisfaction, patient–provider communication, and provider identification and understanding of roles. The authors were able to identify 16 studies that evaluated the use of these tools, which included provider face cards and whiteboards. The majority of the studies reviewed showed a positive effect on provider identification, understanding providers’ role, and patient satisfaction. The authors found that of the tools evaluated, whiteboards and picture-based techniques were the most effective visually based interventions. However, the authors also highlighted the difficulty in identifying 1 optimal approach to the use of these tools as a result of variations in content, format, and outcome measurement.

Variation in the use of visual tools to improve communication and patient satisfaction limits the ability to identify and evaluate the most effective approaches to their use. Without a streamlined approach, these tools may not produce the desired effect of improving patient and provider communication, which is essential in providing high-quality inpatient care and ensuring patient satisfaction. It has been documented that many patients cannot even identify their providers in the hospital setting, which limits the ability of the patient to be fully engaged in decisions made about their care.³ In addition, substantial portions of hospitalized patients do not understand their plan of care.⁴ Patients’ understanding of their plan of care is essential for patients to provide informed consent for hospital treatments and better prepare them to assume their own care after discharge, with a full understanding of their diagnosis.⁵ It has become increasingly clear that healthcare providers must incorporate effective approaches in their daily workflow to address these findings.

Aside from patient satisfaction and engagement, the effect communications failures have on patient safety have been evaluated and recognized. From the National Academy of Medicine’s report emphasizing patient-centered care to the addition of patients’ active engagement in their care as a National Patient Safety Goal by The Joint Commission, the medical field has committed to a continued focus in this area.^5,6

The business case can also be made for identifying effective tools that improve patient satisfaction and patient–provider communication. Private and public health insurance providers have incentivized high performance in these areas and have now begun to levy penalties for underperformers. As patients’ level of satisfaction and engagement continue to be assessed via patient surveys, healthcare systems continue to search for effective practices to improve performance in patient-perceived provider communication. Patients’ reporting of their assessment of nurse and physician communication through questions such as “How often did nurses/doctors explain things in a way you could understand?” will continue to be a moving target requiring future studies of effective interventions

Are visual aids the effective tools that hospitals need to improve communication and patient satisfaction, or are they merely decorations? The whiteboard provides an excellent example of the effectiveness that can be seen with the use of these tools. Used to improve patient-provider communication in medicine, the whiteboard has become almost ubiquitous in patient hospital rooms.⁷ It is now an expected aspect of hospital design and has inspired the development of higher tech solutions, including patient tablets and media walls. It is known to enhance the interaction for both the provider and patient and facilitate the exchange of complicated medical information within an anxiety prone environment in a simple manner by using short phrases or drawings.⁶ Yet, there is a scarcity of strong evidence to support the most effective approach to the use of whiteboards in improving patient satisfaction and communication. Standardizing how the whiteboard is used during the patient interaction will allow for the effectiveness of this tool to be realized and evaluated and prevent it from becoming another ornamental fixture on our hospital walls.

The systematic review by Goyal et al.² is a necessary step in the evaluation of common communication tools for their effectiveness and ability to improve patient satisfaction. This exhaustive review of key studies in this area is an excellent addition to the current literature, which has a paucity of extensive evaluations of these approaches. It provides an important signal that visual tools are more than decorative and can be effective when a streamlined approach is utilized. It highlights the importance of identifying effective best practices for the use of these tools that can be studied empirically and subsequently disseminated for widespread use. Continued work is necessary to fill this void and to enable healthcare professionals to provide the highest level of safe, effective, and engaging care that our patients deserve.

Disclosure

The authors have no conflicts of interest.

Patient satisfaction and the ability to effectively communicate with hospitalized patients has become a core tenet to providing high-quality healthcare. Over the past few decades, medicine has gradually moved away from many paternalistic practices, and the profession has sought to engage patients as true partners in their own care. It is in this setting that effective communication has risen to be a key factor in the patient and provider relationship. It has also become a closely monitored quality metric tied to financial incentives and penalties. Most importantly, it has been well documented that failures in communication are a frequent cause of adverse events that compromise the ability of healthcare providers to provide safe and effective care.¹ It is in this climate that healthcare systems have worked to implement solutions designed to engage patients and their families to improve their healthcare experience. These solutions vary from low to high tech and include patient whiteboards, provider face cards, and web-based patient portals. Despite the numerous innovative solutions being implemented by hospitalists, studies supporting their effectiveness are few. There continues to be limited evidence on the value of these practices and whether they positively impact the desired outcomes of patient satisfaction and engagement.

In this issue of the Journal of Hospital Medicine, Goyal et al.² performed a systematic review to evaluate whether the use of bedside visual tools for hospitalized medical patients impacts patient satisfaction, patient–provider communication, and provider identification and understanding of roles. The authors were able to identify 16 studies that evaluated the use of these tools, which included provider face cards and whiteboards. The majority of the studies reviewed showed a positive effect on provider identification, understanding providers’ role, and patient satisfaction. The authors found that of the tools evaluated, whiteboards and picture-based techniques were the most effective visually based interventions. However, the authors also highlighted the difficulty in identifying 1 optimal approach to the use of these tools as a result of variations in content, format, and outcome measurement.

Variation in the use of visual tools to improve communication and patient satisfaction limits the ability to identify and evaluate the most effective approaches to their use. Without a streamlined approach, these tools may not produce the desired effect of improving patient and provider communication, which is essential in providing high-quality inpatient care and ensuring patient satisfaction. It has been documented that many patients cannot even identify their providers in the hospital setting, which limits the ability of the patient to be fully engaged in decisions made about their care.³ In addition, substantial portions of hospitalized patients do not understand their plan of care.⁴ Patients’ understanding of their plan of care is essential for patients to provide informed consent for hospital treatments and better prepare them to assume their own care after discharge, with a full understanding of their diagnosis.⁵ It has become increasingly clear that healthcare providers must incorporate effective approaches in their daily workflow to address these findings.

Aside from patient satisfaction and engagement, the effect communications failures have on patient safety have been evaluated and recognized. From the National Academy of Medicine’s report emphasizing patient-centered care to the addition of patients’ active engagement in their care as a National Patient Safety Goal by The Joint Commission, the medical field has committed to a continued focus in this area.^5,6

The business case can also be made for identifying effective tools that improve patient satisfaction and patient–provider communication. Private and public health insurance providers have incentivized high performance in these areas and have now begun to levy penalties for underperformers. As patients’ level of satisfaction and engagement continue to be assessed via patient surveys, healthcare systems continue to search for effective practices to improve performance in patient-perceived provider communication. Patients’ reporting of their assessment of nurse and physician communication through questions such as “How often did nurses/doctors explain things in a way you could understand?” will continue to be a moving target requiring future studies of effective interventions

Are visual aids the effective tools that hospitals need to improve communication and patient satisfaction, or are they merely decorations? The whiteboard provides an excellent example of the effectiveness that can be seen with the use of these tools. Used to improve patient-provider communication in medicine, the whiteboard has become almost ubiquitous in patient hospital rooms.⁷ It is now an expected aspect of hospital design and has inspired the development of higher tech solutions, including patient tablets and media walls. It is known to enhance the interaction for both the provider and patient and facilitate the exchange of complicated medical information within an anxiety prone environment in a simple manner by using short phrases or drawings.⁶ Yet, there is a scarcity of strong evidence to support the most effective approach to the use of whiteboards in improving patient satisfaction and communication. Standardizing how the whiteboard is used during the patient interaction will allow for the effectiveness of this tool to be realized and evaluated and prevent it from becoming another ornamental fixture on our hospital walls.

The systematic review by Goyal et al.² is a necessary step in the evaluation of common communication tools for their effectiveness and ability to improve patient satisfaction. This exhaustive review of key studies in this area is an excellent addition to the current literature, which has a paucity of extensive evaluations of these approaches. It provides an important signal that visual tools are more than decorative and can be effective when a streamlined approach is utilized. It highlights the importance of identifying effective best practices for the use of these tools that can be studied empirically and subsequently disseminated for widespread use. Continued work is necessary to fill this void and to enable healthcare professionals to provide the highest level of safe, effective, and engaging care that our patients deserve.

Disclosure

The authors have no conflicts of interest.