For at least 25 years, approximately 20% of Medicare fee‐for‐service discharges have been followed by a hospital readmission within 30 days.[1, 2] Section 3025 of the Patient Protection and Affordable Care Act (ACA)[3] created escalating penalties for hospitals with higher than expected 30‐day readmission rates, and the Congressional Budget Office estimated this will reduce Medicare spending by over $7 billion between 2010 and 2019.[4]

Hospitals and physicians have begun developing strategies to identify which Medicare beneficiaries are most likely to be readmitted and use this information to design programs to reduce their readmission rate. Initially, penalties will be based on readmission rates after an index discharge with heart failure, myocardial infarction, and pneumonia.[5] Recently, the Centers for Medicare and Medicaid Services (CMS) released the Inpatient Prospective Payment System FY2014 proposed rule, which proposes to add 2 new readmission penalties beginning in FY2015: readmissions for hip/knee arthroplasty and chronic obstructive pulmonary disease.[6] Other countries are already penalizing hospitals with high readmission rates; for example, Germany is penalizing all readmissions that occur within a 30‐day period following admission.[7] In this brief report, we examine the characteristics of Medicare beneficiaries most likely to be readmitted within 30 days. We focus on readmission rates for all discharge conditions and all patient readmission rates, because we believe the language in the ACA ultimately points to an all‐inclusive approach.

METHODS

We used a nationally random 5% sample of all Medicare beneficiaries for the period between January 1, 2008 and September 30, 2008. To be included, beneficiaries must have both Part A and B coverage and live within the United States. Medicare Advantage patients were excluded because Medicare Advantage plans do not report the data in the same way as fee for service. We calculated the readmission rate as the number of admissions that were preceded by an at‐risk discharge within 30 days divided by the total number of at‐risk discharges. This definition included admissions to and discharges from sole community providers, Medicare‐dependent small rural hospitals, and critical access hospitals. We counted as at risk all live discharges from short‐term acute care hospitals that were not discharged against medical advice, discharged to a rehabilitation unit within an acute care hospital, or readmitted on day 0 (due to inconsistency with use of transfer coding). We only included discharges and readmissions to acute care hospitals and excluded hospitalizations in long‐term care facilities, rehabilitation facilities, skilled nursing homes, and other non‐acute care hospital facilities from being an index hospitalization. However, if the beneficiary was discharged to 1 of these facilities and then readmitted to an acute care hospital, the readmission was counted.

Each discharge was recorded as an independent event and we reset the readmission clock for a fresh 30‐day count each time the beneficiary was discharged. We examined the admission and readmission rate to determine if the rates varied by age, gender, reason for entitlement, racial characteristics, region of the country, number of chronic conditions, and whether the beneficiary is also enrolled in Medicaid (dual eligibles). We calculated the mean readmission rate for each diagnosis‐related group (DRG) and then used the probability of having a readmission for each DRG to calculate a case mix adjustment for each hospital. To calculate the chronic illness burden, we used a previously developed methodology for counting the number of chronic disease categories reported for the patient in the preceding year (2007).[8, 9] The classification system is maintained by the Agency for Health Care Research and Quality. We then used logistic regression to calculate the odds ratio of a discharge being readmitted based on these factors. We preformed statistical analysis using SAS version 9.1.3 (SAS Institute Inc., Cary, NC).

RESULTS

There were 434,999 hospital discharges that occurred in the first 9 months of 2008 in the 5% sample. There were 20.6% of Medicare beneficiaries hospitalized, and the overall readmission rate was 19.5%. Table 1 shows the odds ratios and 95% confidence intervals for the probability that a Medicare beneficiary will be readmitted within 30 days for variables including: age, sex, race, dual‐eligibility status, number of comorbid conditions, geographic region, and reason for entitlement. Of note, beneficiaries with 10 or more chronic conditions were more than 6 times more likely, and beneficiaries with 5 to 9 chronic conditions were more than 2.5 times more likely, to be readmitted than beneficiaries with 1 to 4 chronic conditions.

DISCUSSION

The most interesting finding is that beneficiaries with 10 or more chronic conditions were more than 6 times more likely to be readmitted than beneficiaries with 1 to 4 chronic conditions. Beneficiaries with 10 or more chronic conditions represent only 8.9% of all Medicare beneficiaries (31.0% of all hospitalizations), but they were responsible for 50.2% of all readmissions. The 31.8% of beneficiaries with 5 to 9 chronic conditions (55.5% of all hospitalizations) had the second highest odds ratio (2.5) and were responsible for 45% of all readmissions. The 59.3% of beneficiaries with <5 comorbidities (13.6% of all hospitalizations) were associated with only 4.7% of all readmissions. This strongly suggests that hospitals focus their attention on beneficiaries with 10 or more comorbidities. These results were despite correction for DRG diagnosis in the model.

We recognize that the number of chronic conditions is a crude measure of health status because it weighs hundreds of different clinical conditions equally; however, it seems a good proxy for 3 closely allied concepts: (1) the overall burden of chronic illness carried by the patient, (2) the patient's level of engagement with the healthcare system (including number of unique providers), and (3) the number of conditions being treated. By providing a 1‐year window of a patient's health status, it is a more complete picture than any single hospital claim submission or indices based solely on hospital discharge data.

The other variables are less predictive of 30‐day readmissions. Beneficiaries over 85 years old are only 14% more likely, whereas disabled Medicare beneficiaries <44 years old are 63% more likely to be readmitted than beneficiaries between 65 and 74 years old. Men are 20% more likely to be readmitted than women. Black race and dual‐eligibility slightly increase rates of readmission. Beneficiaries located in the West have the lowest readmission rates. In comparison to those who are aged, those with end‐stage renal disease (ESRD) have a higher rate of readmission, and those with a disability have a lower rate of readmission. In considering the age and reason for entitlement findings, one would assume that ESRD was the driver of higher readmission rates in the younger Medicare population.

CMS will need to analyze which hospitals have higher than expected readmission rates, and this will require risk adjustment at each hospital. In addition to the number of chronic conditions and other variables shown in Table 1, other factors CMS might want to include when it starts doing readmissions for all discharges is the discharge diagnosis (because our results suggest there are significant differences in the probability of a readmission across DRGs). In addition, CMS will need to consider how to capture additional data not currently in the claims data, such as social factors like homelessness.

We recognize significant limitations to these findings. First, this analysis uses only information that is available from Medicare claims and administrative data. Claims give almost no information on how well the hospital planned the discharge, instructed the patient and family, or engaged follow‐up providers. Also, claims data tell us virtually nothing about a patient's health literacy or social situation. Second, the analysis relies on claims data, but this has little clinical detail. Third, these data are limited to persons enrolled in fee‐for‐service Medicare. Fourth, we included all readmissions, including some readmissions (such as chemotherapy and staged percutaneous coronary interventions) that were part of a planned treatment protocol.[10] Fifth, we were unable to distinguish same‐day readmissions versus transfers, and therefore excluded all same‐day readmissions from measurement.

As hospitals and physicians begin to plan for the regulations that will penalize hospitals with high readmission rates, they will need to strongly consider targeting beneficiaries with more than 10 chronic conditions.

For at least 25 years, approximately 20% of Medicare fee‐for‐service discharges have been followed by a hospital readmission within 30 days.[1, 2] Section 3025 of the Patient Protection and Affordable Care Act (ACA)[3] created escalating penalties for hospitals with higher than expected 30‐day readmission rates, and the Congressional Budget Office estimated this will reduce Medicare spending by over $7 billion between 2010 and 2019.[4]

Hospitals and physicians have begun developing strategies to identify which Medicare beneficiaries are most likely to be readmitted and use this information to design programs to reduce their readmission rate. Initially, penalties will be based on readmission rates after an index discharge with heart failure, myocardial infarction, and pneumonia.[5] Recently, the Centers for Medicare and Medicaid Services (CMS) released the Inpatient Prospective Payment System FY2014 proposed rule, which proposes to add 2 new readmission penalties beginning in FY2015: readmissions for hip/knee arthroplasty and chronic obstructive pulmonary disease.[6] Other countries are already penalizing hospitals with high readmission rates; for example, Germany is penalizing all readmissions that occur within a 30‐day period following admission.[7] In this brief report, we examine the characteristics of Medicare beneficiaries most likely to be readmitted within 30 days. We focus on readmission rates for all discharge conditions and all patient readmission rates, because we believe the language in the ACA ultimately points to an all‐inclusive approach.

METHODS

We used a nationally random 5% sample of all Medicare beneficiaries for the period between January 1, 2008 and September 30, 2008. To be included, beneficiaries must have both Part A and B coverage and live within the United States. Medicare Advantage patients were excluded because Medicare Advantage plans do not report the data in the same way as fee for service. We calculated the readmission rate as the number of admissions that were preceded by an at‐risk discharge within 30 days divided by the total number of at‐risk discharges. This definition included admissions to and discharges from sole community providers, Medicare‐dependent small rural hospitals, and critical access hospitals. We counted as at risk all live discharges from short‐term acute care hospitals that were not discharged against medical advice, discharged to a rehabilitation unit within an acute care hospital, or readmitted on day 0 (due to inconsistency with use of transfer coding). We only included discharges and readmissions to acute care hospitals and excluded hospitalizations in long‐term care facilities, rehabilitation facilities, skilled nursing homes, and other non‐acute care hospital facilities from being an index hospitalization. However, if the beneficiary was discharged to 1 of these facilities and then readmitted to an acute care hospital, the readmission was counted.

Each discharge was recorded as an independent event and we reset the readmission clock for a fresh 30‐day count each time the beneficiary was discharged. We examined the admission and readmission rate to determine if the rates varied by age, gender, reason for entitlement, racial characteristics, region of the country, number of chronic conditions, and whether the beneficiary is also enrolled in Medicaid (dual eligibles). We calculated the mean readmission rate for each diagnosis‐related group (DRG) and then used the probability of having a readmission for each DRG to calculate a case mix adjustment for each hospital. To calculate the chronic illness burden, we used a previously developed methodology for counting the number of chronic disease categories reported for the patient in the preceding year (2007).[8, 9] The classification system is maintained by the Agency for Health Care Research and Quality. We then used logistic regression to calculate the odds ratio of a discharge being readmitted based on these factors. We preformed statistical analysis using SAS version 9.1.3 (SAS Institute Inc., Cary, NC).

RESULTS

There were 434,999 hospital discharges that occurred in the first 9 months of 2008 in the 5% sample. There were 20.6% of Medicare beneficiaries hospitalized, and the overall readmission rate was 19.5%. Table 1 shows the odds ratios and 95% confidence intervals for the probability that a Medicare beneficiary will be readmitted within 30 days for variables including: age, sex, race, dual‐eligibility status, number of comorbid conditions, geographic region, and reason for entitlement. Of note, beneficiaries with 10 or more chronic conditions were more than 6 times more likely, and beneficiaries with 5 to 9 chronic conditions were more than 2.5 times more likely, to be readmitted than beneficiaries with 1 to 4 chronic conditions.

DISCUSSION

The most interesting finding is that beneficiaries with 10 or more chronic conditions were more than 6 times more likely to be readmitted than beneficiaries with 1 to 4 chronic conditions. Beneficiaries with 10 or more chronic conditions represent only 8.9% of all Medicare beneficiaries (31.0% of all hospitalizations), but they were responsible for 50.2% of all readmissions. The 31.8% of beneficiaries with 5 to 9 chronic conditions (55.5% of all hospitalizations) had the second highest odds ratio (2.5) and were responsible for 45% of all readmissions. The 59.3% of beneficiaries with <5 comorbidities (13.6% of all hospitalizations) were associated with only 4.7% of all readmissions. This strongly suggests that hospitals focus their attention on beneficiaries with 10 or more comorbidities. These results were despite correction for DRG diagnosis in the model.

We recognize that the number of chronic conditions is a crude measure of health status because it weighs hundreds of different clinical conditions equally; however, it seems a good proxy for 3 closely allied concepts: (1) the overall burden of chronic illness carried by the patient, (2) the patient's level of engagement with the healthcare system (including number of unique providers), and (3) the number of conditions being treated. By providing a 1‐year window of a patient's health status, it is a more complete picture than any single hospital claim submission or indices based solely on hospital discharge data.

The other variables are less predictive of 30‐day readmissions. Beneficiaries over 85 years old are only 14% more likely, whereas disabled Medicare beneficiaries <44 years old are 63% more likely to be readmitted than beneficiaries between 65 and 74 years old. Men are 20% more likely to be readmitted than women. Black race and dual‐eligibility slightly increase rates of readmission. Beneficiaries located in the West have the lowest readmission rates. In comparison to those who are aged, those with end‐stage renal disease (ESRD) have a higher rate of readmission, and those with a disability have a lower rate of readmission. In considering the age and reason for entitlement findings, one would assume that ESRD was the driver of higher readmission rates in the younger Medicare population.

CMS will need to analyze which hospitals have higher than expected readmission rates, and this will require risk adjustment at each hospital. In addition to the number of chronic conditions and other variables shown in Table 1, other factors CMS might want to include when it starts doing readmissions for all discharges is the discharge diagnosis (because our results suggest there are significant differences in the probability of a readmission across DRGs). In addition, CMS will need to consider how to capture additional data not currently in the claims data, such as social factors like homelessness.

We recognize significant limitations to these findings. First, this analysis uses only information that is available from Medicare claims and administrative data. Claims give almost no information on how well the hospital planned the discharge, instructed the patient and family, or engaged follow‐up providers. Also, claims data tell us virtually nothing about a patient's health literacy or social situation. Second, the analysis relies on claims data, but this has little clinical detail. Third, these data are limited to persons enrolled in fee‐for‐service Medicare. Fourth, we included all readmissions, including some readmissions (such as chemotherapy and staged percutaneous coronary interventions) that were part of a planned treatment protocol.[10] Fifth, we were unable to distinguish same‐day readmissions versus transfers, and therefore excluded all same‐day readmissions from measurement.

As hospitals and physicians begin to plan for the regulations that will penalize hospitals with high readmission rates, they will need to strongly consider targeting beneficiaries with more than 10 chronic conditions.

For at least 25 years, approximately 20% of Medicare fee‐for‐service discharges have been followed by a hospital readmission within 30 days.[1, 2] Section 3025 of the Patient Protection and Affordable Care Act (ACA)[3] created escalating penalties for hospitals with higher than expected 30‐day readmission rates, and the Congressional Budget Office estimated this will reduce Medicare spending by over $7 billion between 2010 and 2019.[4]

Hospitals and physicians have begun developing strategies to identify which Medicare beneficiaries are most likely to be readmitted and use this information to design programs to reduce their readmission rate. Initially, penalties will be based on readmission rates after an index discharge with heart failure, myocardial infarction, and pneumonia.[5] Recently, the Centers for Medicare and Medicaid Services (CMS) released the Inpatient Prospective Payment System FY2014 proposed rule, which proposes to add 2 new readmission penalties beginning in FY2015: readmissions for hip/knee arthroplasty and chronic obstructive pulmonary disease.[6] Other countries are already penalizing hospitals with high readmission rates; for example, Germany is penalizing all readmissions that occur within a 30‐day period following admission.[7] In this brief report, we examine the characteristics of Medicare beneficiaries most likely to be readmitted within 30 days. We focus on readmission rates for all discharge conditions and all patient readmission rates, because we believe the language in the ACA ultimately points to an all‐inclusive approach.

METHODS

We used a nationally random 5% sample of all Medicare beneficiaries for the period between January 1, 2008 and September 30, 2008. To be included, beneficiaries must have both Part A and B coverage and live within the United States. Medicare Advantage patients were excluded because Medicare Advantage plans do not report the data in the same way as fee for service. We calculated the readmission rate as the number of admissions that were preceded by an at‐risk discharge within 30 days divided by the total number of at‐risk discharges. This definition included admissions to and discharges from sole community providers, Medicare‐dependent small rural hospitals, and critical access hospitals. We counted as at risk all live discharges from short‐term acute care hospitals that were not discharged against medical advice, discharged to a rehabilitation unit within an acute care hospital, or readmitted on day 0 (due to inconsistency with use of transfer coding). We only included discharges and readmissions to acute care hospitals and excluded hospitalizations in long‐term care facilities, rehabilitation facilities, skilled nursing homes, and other non‐acute care hospital facilities from being an index hospitalization. However, if the beneficiary was discharged to 1 of these facilities and then readmitted to an acute care hospital, the readmission was counted.

Each discharge was recorded as an independent event and we reset the readmission clock for a fresh 30‐day count each time the beneficiary was discharged. We examined the admission and readmission rate to determine if the rates varied by age, gender, reason for entitlement, racial characteristics, region of the country, number of chronic conditions, and whether the beneficiary is also enrolled in Medicaid (dual eligibles). We calculated the mean readmission rate for each diagnosis‐related group (DRG) and then used the probability of having a readmission for each DRG to calculate a case mix adjustment for each hospital. To calculate the chronic illness burden, we used a previously developed methodology for counting the number of chronic disease categories reported for the patient in the preceding year (2007).[8, 9] The classification system is maintained by the Agency for Health Care Research and Quality. We then used logistic regression to calculate the odds ratio of a discharge being readmitted based on these factors. We preformed statistical analysis using SAS version 9.1.3 (SAS Institute Inc., Cary, NC).

RESULTS

There were 434,999 hospital discharges that occurred in the first 9 months of 2008 in the 5% sample. There were 20.6% of Medicare beneficiaries hospitalized, and the overall readmission rate was 19.5%. Table 1 shows the odds ratios and 95% confidence intervals for the probability that a Medicare beneficiary will be readmitted within 30 days for variables including: age, sex, race, dual‐eligibility status, number of comorbid conditions, geographic region, and reason for entitlement. Of note, beneficiaries with 10 or more chronic conditions were more than 6 times more likely, and beneficiaries with 5 to 9 chronic conditions were more than 2.5 times more likely, to be readmitted than beneficiaries with 1 to 4 chronic conditions.

DISCUSSION

The most interesting finding is that beneficiaries with 10 or more chronic conditions were more than 6 times more likely to be readmitted than beneficiaries with 1 to 4 chronic conditions. Beneficiaries with 10 or more chronic conditions represent only 8.9% of all Medicare beneficiaries (31.0% of all hospitalizations), but they were responsible for 50.2% of all readmissions. The 31.8% of beneficiaries with 5 to 9 chronic conditions (55.5% of all hospitalizations) had the second highest odds ratio (2.5) and were responsible for 45% of all readmissions. The 59.3% of beneficiaries with <5 comorbidities (13.6% of all hospitalizations) were associated with only 4.7% of all readmissions. This strongly suggests that hospitals focus their attention on beneficiaries with 10 or more comorbidities. These results were despite correction for DRG diagnosis in the model.

We recognize that the number of chronic conditions is a crude measure of health status because it weighs hundreds of different clinical conditions equally; however, it seems a good proxy for 3 closely allied concepts: (1) the overall burden of chronic illness carried by the patient, (2) the patient's level of engagement with the healthcare system (including number of unique providers), and (3) the number of conditions being treated. By providing a 1‐year window of a patient's health status, it is a more complete picture than any single hospital claim submission or indices based solely on hospital discharge data.

The other variables are less predictive of 30‐day readmissions. Beneficiaries over 85 years old are only 14% more likely, whereas disabled Medicare beneficiaries <44 years old are 63% more likely to be readmitted than beneficiaries between 65 and 74 years old. Men are 20% more likely to be readmitted than women. Black race and dual‐eligibility slightly increase rates of readmission. Beneficiaries located in the West have the lowest readmission rates. In comparison to those who are aged, those with end‐stage renal disease (ESRD) have a higher rate of readmission, and those with a disability have a lower rate of readmission. In considering the age and reason for entitlement findings, one would assume that ESRD was the driver of higher readmission rates in the younger Medicare population.

CMS will need to analyze which hospitals have higher than expected readmission rates, and this will require risk adjustment at each hospital. In addition to the number of chronic conditions and other variables shown in Table 1, other factors CMS might want to include when it starts doing readmissions for all discharges is the discharge diagnosis (because our results suggest there are significant differences in the probability of a readmission across DRGs). In addition, CMS will need to consider how to capture additional data not currently in the claims data, such as social factors like homelessness.

We recognize significant limitations to these findings. First, this analysis uses only information that is available from Medicare claims and administrative data. Claims give almost no information on how well the hospital planned the discharge, instructed the patient and family, or engaged follow‐up providers. Also, claims data tell us virtually nothing about a patient's health literacy or social situation. Second, the analysis relies on claims data, but this has little clinical detail. Third, these data are limited to persons enrolled in fee‐for‐service Medicare. Fourth, we included all readmissions, including some readmissions (such as chemotherapy and staged percutaneous coronary interventions) that were part of a planned treatment protocol.[10] Fifth, we were unable to distinguish same‐day readmissions versus transfers, and therefore excluded all same‐day readmissions from measurement.

As hospitals and physicians begin to plan for the regulations that will penalize hospitals with high readmission rates, they will need to strongly consider targeting beneficiaries with more than 10 chronic conditions.

In their seminal report Crossing the Quality Chasm, the Institute of Medicine outlined patient‐centered care as 1 of its 6 aims to improve the healthcare delivery system.[1] Patients who are more involved in their diagnosis and treatment plan are more likely to feel respected, be satisfied with their healthcare experience, and ultimately have better outcomes.[2, 3] In a study of hospitalized patients, only 42% were able to state their diagnosis at the time of discharge, suggesting that hospital providers could communicate better with patients about their hospital care.[4] Additionally, only 28% of hospitalized patients were able to list their medications, and only 37% were able to state the purpose of their medications. Although hospitals have taken great strides to improve the quality of patient care, publicly reported patient care surveys, such as the Hospital Consumer Assessment of Hospitals and Health Systems (HCAHPS), suggest that physician communication with patients could be further improved.[1, 5] Furthermore, a recent report by the Institute of Medicine stresses the need to get patients and families involved in their care.[6] Thus, hospital‐based providers should seek to enhance the quality of their communication with patients.

With greater emphasis placed on patient‐ and family‐centered care at many health systems, simple and easy‐to‐implement strategies to improve communication with patients need to be developed and tested.[7, 8] Patients who actively participate in their healthcare by asking questions of their doctor are able to control the focus of their interaction and adjust the amount of information provided.[9] Simply asking questions can have a critical impact, as 1 study found that the frequency with which patients asked questions was significantly related to the amount of information received about general and specific medical matters.[10] The notepad is a common tool for reminders and personal interactions that is used in everyday life, but has not been formalized in the hospital. We introduced Dear Doctor (DD) notes, a bedside notepad designed to prompt patient questions, with the goal of facilitating patient communication with their hospitalist physicians (Figure 1). As hospitalists provide direct and indirect care to a growing number of hospitalized patients, they are likely to be asked questions and opinions about the patients' diagnoses and plans. Furthermore, hospitalists are poised to lead institutional quality, safety, efficiency, and service improvement efforts in the inpatient setting. Becoming familiar with communication‐enhancing tools, such as the DD notes, may help hospitalists in their improvement team roles.

Figure 1

METHODS

RESULTS

Of the 440 patients surveyed in the intervention group (1 general medicine and 1 cardiology unit), 343 (78%) received the notepads in their rooms and 207 (47%) used them (Figure 2). Not every patient in the intervention group received DD notepads due to inconsistent placement of DD notepads upon every room turnover. Of the patients admitted to the control group (1 general medicine and 1 cardiology unit), 224 were surveyed. Fifty‐four percent of the 440 patients in the intervention group reported that they took notes related to their hospital care, compared to only 22% of the 224 patients in the control group (P < 0.001). Of the patients who took notes within the intervention group (n = 207), 91% of them utilized the DD notepads.

Figure 2

Patients in the intervention group who received and used the DD notes (n = 207) compared to patients in the control group (n = 224) were more likely to report that their questions were answered by their physicians (4.63 vs 4.45, P < 0.001). In an intention‐to‐treat analysis of all 440 patients in the intervention group, the overall satisfaction with physician communication was not significantly different between the intervention and control groups as measured on a 5‐point Likert scale (4.55 vs 4.55, P = 0.89). However, 89% of the patients in the intervention group who used the notepads felt that DD notepads either moderately or significantly improved their communication with their providers (Figure 3).

Figure 3

When the 207 patients who received DD notepads were asked how they used this tool, 99% of these patients used DD to write down questions, 82% to keep track of tests and procedures, and 54% indicated that their family and friends also used the notepads during the hospital stay (Table 1). Among these patients who utilized the DD notepads, 93% reported that they would use them again in the future.

Of the 97 patients in the intervention group who did not receive a DD notepad, we asked if they would use the DD notepad if they were made aware of such a tool. Of these patients, 77% agreed that they would use DD notes if they were made available in the future, 100% of them said that they would use DD to write down questions, 97% indicated that they would write notes about tests and procedures, and 88% of them believed that their families and friends would use DD notes.

DISCUSSION

As hospitals place greater emphasis and value on patient‐centered care as part of their clinical mission, it is important to develop tools to help facilitate the doctor‐patient relationship. We found that patients who were provided the Dear Doctor notepad were more satisfied that their doctors answered their questions and felt this tool enhanced their ability to communicate with their physicians. Employing the use of a familiar tool such as the notepad to remind patients about specific issues in their interactions with their providers can be a powerful intervention. Our study demonstrated that the DD notepad was widely accepted by patients, and that almost all of them would use this tool if it were made available to them in the future.

Other tools and methods to enhance the quality of communication between patients and their healthcare providers have included using whiteboards in the patients' rooms to relay the care plan to the patients, implementing bedside rounds by the healthcare team, and multidisciplinary huddling to coordinate information to the patient.[12, 13] Studies of these communication tools have shown potential to improve teamwork, interaction, and patient care. All of these have their own merit and value, and our DD notepad should be considered an adjunct to existing methods to enhance the patient care experience. A bedside tool that is familiar in form to most patients also needs to have the feature of easy access and use. Once this barrier has been removed for the patient and their family members, tools such as the DD notepad can impact the patient‐centeredness by fostering increased and better quality dialogue between the patients, their family members, and healthcare providers.

The DD notepad represents a means of communication that may have the potential to empower patients. It is possible that through question prompts, the DD notepad stimulates the patient to be an active partner with his or her healthcare team. This may enable patients to have some sense of control and accountability of their care in a setting where they would otherwise feel overwhelmed or powerless. The 3 general categories to help patients write down their questions included diagnosis, treatment plan, and medications. In the inpatient setting, where patient‐care activities can be fast paced, and patients are unable to recall some details when speaking to the healthcare team, these notes may remind the patient to write their thoughts down so that they may be remembered for a future time. In situations where patients may not know which questions to ask, the question prompts may be particularly helpful. We did not assess whether our particular question prompts were the key elements that resulted in their perceived value, or whether simply placing a blank notepad at the bedside would also have been successful. However, the specific questions were suggested by the focus groups. Enhanced communication, focusing on the patients' understanding of their condition, and the need to pursue certain diagnostic or therapeutic interventions, may help patients to be better prepared for the next course of plan. These topics of reasons for hospitalization, treatment plan, and medication changes are also important for patients to be active participants in their care, in particular as they transition from 1 site of care to the next, and their healthcare will be delivered by different providers.

There are several limitations to our study. First, this intervention was performed at a single hospital site with only 2 clinical services (general medicine, cardiology) represented in the study groups. Although we do not have any causal reasons to believe this tool would be looked upon differently by patients on other clinical services, it is possible that patients on a different clinical unit or service may view this tool as less or more useful. Second, as the patients were not randomized to intervention, but rather based on the units to which they were admitted, it is possible that other variables, such as the experience of the unit staff, the patient's condition, and housestaff‐based service versus hospitalist‐based service may have played a role in how the patients perceived the use of DD notes. Third, patients were only surveyed if they were able to verbally communicate in English. These notes may not be as useful in hospital settings to populations with language or literacy barriers. Fourth, the logistical implementation of DD notes limited our ability to deliver the DD notepads in every patient's rooms, where only 78% of the intervention group received the DD notepads. This may be the reason that we did not find that overall satisfaction with physician communication differed between intervention and control groups. Nonetheless, we performed an intention‐to‐treat analysis to minimize any biases in our analysis. Last, although our survey of patients asked about their satisfaction in using the DD note pads, we did not compare these results with those of Press‐Ganey or HCAHPS scores of patients on the intervention group versus the control group. Additionally, lack of data about type, quality, and quantity of questions asked by a control group to see if the notepads actually improved quality of questions asked is a limitation; however, we believe our outcomes of interest were most specifically evaluated through our survey questions.

DD notes show that the majority of patients who use this tool feel a modest to significant improvement in communication with their providers. Although the quality of medical care is undoubtedly the first priority, the patients' view of their care, which includes communication, is arguably just as important. An often‐forgotten goal of hospitals and clinics is to provide service excellence along with high‐quality care. Thus, it is imperative for hospitals and their care providers to not only focus on the quality and safety of the clinical care, but also be mindful of the patient's entire experience throughout their hospital stay. Many of the categories of questions asked in the HCAHPS address the patient's experience and perspectives of hospital care. Furthermore, the role of the HCAHPS survey in the Value‐Based Purchasing rules may enhance the importance of these notepads. As the results of HCAHPS are becoming more transparent and available to the public, the impact of such results will have a greater significance to the future of the hospital's clinical mission.

CONCLUSION

DD notepads are a simple, low‐cost, patient‐centered tool that can be an effective reminder for patients to ask their healthcare providers questions related to their hospital care. Utilizing a common tool such as the notepad, redesigned for the healthcare setting, can serve to help healthcare providers interact with their patients. Patient satisfaction may be higher in patients who use the DD notepad.

In their seminal report Crossing the Quality Chasm, the Institute of Medicine outlined patient‐centered care as 1 of its 6 aims to improve the healthcare delivery system.[1] Patients who are more involved in their diagnosis and treatment plan are more likely to feel respected, be satisfied with their healthcare experience, and ultimately have better outcomes.[2, 3] In a study of hospitalized patients, only 42% were able to state their diagnosis at the time of discharge, suggesting that hospital providers could communicate better with patients about their hospital care.[4] Additionally, only 28% of hospitalized patients were able to list their medications, and only 37% were able to state the purpose of their medications. Although hospitals have taken great strides to improve the quality of patient care, publicly reported patient care surveys, such as the Hospital Consumer Assessment of Hospitals and Health Systems (HCAHPS), suggest that physician communication with patients could be further improved.[1, 5] Furthermore, a recent report by the Institute of Medicine stresses the need to get patients and families involved in their care.[6] Thus, hospital‐based providers should seek to enhance the quality of their communication with patients.

With greater emphasis placed on patient‐ and family‐centered care at many health systems, simple and easy‐to‐implement strategies to improve communication with patients need to be developed and tested.[7, 8] Patients who actively participate in their healthcare by asking questions of their doctor are able to control the focus of their interaction and adjust the amount of information provided.[9] Simply asking questions can have a critical impact, as 1 study found that the frequency with which patients asked questions was significantly related to the amount of information received about general and specific medical matters.[10] The notepad is a common tool for reminders and personal interactions that is used in everyday life, but has not been formalized in the hospital. We introduced Dear Doctor (DD) notes, a bedside notepad designed to prompt patient questions, with the goal of facilitating patient communication with their hospitalist physicians (Figure 1). As hospitalists provide direct and indirect care to a growing number of hospitalized patients, they are likely to be asked questions and opinions about the patients' diagnoses and plans. Furthermore, hospitalists are poised to lead institutional quality, safety, efficiency, and service improvement efforts in the inpatient setting. Becoming familiar with communication‐enhancing tools, such as the DD notes, may help hospitalists in their improvement team roles.

Figure 1

METHODS

RESULTS

Of the 440 patients surveyed in the intervention group (1 general medicine and 1 cardiology unit), 343 (78%) received the notepads in their rooms and 207 (47%) used them (Figure 2). Not every patient in the intervention group received DD notepads due to inconsistent placement of DD notepads upon every room turnover. Of the patients admitted to the control group (1 general medicine and 1 cardiology unit), 224 were surveyed. Fifty‐four percent of the 440 patients in the intervention group reported that they took notes related to their hospital care, compared to only 22% of the 224 patients in the control group (P < 0.001). Of the patients who took notes within the intervention group (n = 207), 91% of them utilized the DD notepads.

Figure 2

Patients in the intervention group who received and used the DD notes (n = 207) compared to patients in the control group (n = 224) were more likely to report that their questions were answered by their physicians (4.63 vs 4.45, P < 0.001). In an intention‐to‐treat analysis of all 440 patients in the intervention group, the overall satisfaction with physician communication was not significantly different between the intervention and control groups as measured on a 5‐point Likert scale (4.55 vs 4.55, P = 0.89). However, 89% of the patients in the intervention group who used the notepads felt that DD notepads either moderately or significantly improved their communication with their providers (Figure 3).

Figure 3

When the 207 patients who received DD notepads were asked how they used this tool, 99% of these patients used DD to write down questions, 82% to keep track of tests and procedures, and 54% indicated that their family and friends also used the notepads during the hospital stay (Table 1). Among these patients who utilized the DD notepads, 93% reported that they would use them again in the future.

Of the 97 patients in the intervention group who did not receive a DD notepad, we asked if they would use the DD notepad if they were made aware of such a tool. Of these patients, 77% agreed that they would use DD notes if they were made available in the future, 100% of them said that they would use DD to write down questions, 97% indicated that they would write notes about tests and procedures, and 88% of them believed that their families and friends would use DD notes.

DISCUSSION

As hospitals place greater emphasis and value on patient‐centered care as part of their clinical mission, it is important to develop tools to help facilitate the doctor‐patient relationship. We found that patients who were provided the Dear Doctor notepad were more satisfied that their doctors answered their questions and felt this tool enhanced their ability to communicate with their physicians. Employing the use of a familiar tool such as the notepad to remind patients about specific issues in their interactions with their providers can be a powerful intervention. Our study demonstrated that the DD notepad was widely accepted by patients, and that almost all of them would use this tool if it were made available to them in the future.

Other tools and methods to enhance the quality of communication between patients and their healthcare providers have included using whiteboards in the patients' rooms to relay the care plan to the patients, implementing bedside rounds by the healthcare team, and multidisciplinary huddling to coordinate information to the patient.[12, 13] Studies of these communication tools have shown potential to improve teamwork, interaction, and patient care. All of these have their own merit and value, and our DD notepad should be considered an adjunct to existing methods to enhance the patient care experience. A bedside tool that is familiar in form to most patients also needs to have the feature of easy access and use. Once this barrier has been removed for the patient and their family members, tools such as the DD notepad can impact the patient‐centeredness by fostering increased and better quality dialogue between the patients, their family members, and healthcare providers.

The DD notepad represents a means of communication that may have the potential to empower patients. It is possible that through question prompts, the DD notepad stimulates the patient to be an active partner with his or her healthcare team. This may enable patients to have some sense of control and accountability of their care in a setting where they would otherwise feel overwhelmed or powerless. The 3 general categories to help patients write down their questions included diagnosis, treatment plan, and medications. In the inpatient setting, where patient‐care activities can be fast paced, and patients are unable to recall some details when speaking to the healthcare team, these notes may remind the patient to write their thoughts down so that they may be remembered for a future time. In situations where patients may not know which questions to ask, the question prompts may be particularly helpful. We did not assess whether our particular question prompts were the key elements that resulted in their perceived value, or whether simply placing a blank notepad at the bedside would also have been successful. However, the specific questions were suggested by the focus groups. Enhanced communication, focusing on the patients' understanding of their condition, and the need to pursue certain diagnostic or therapeutic interventions, may help patients to be better prepared for the next course of plan. These topics of reasons for hospitalization, treatment plan, and medication changes are also important for patients to be active participants in their care, in particular as they transition from 1 site of care to the next, and their healthcare will be delivered by different providers.

There are several limitations to our study. First, this intervention was performed at a single hospital site with only 2 clinical services (general medicine, cardiology) represented in the study groups. Although we do not have any causal reasons to believe this tool would be looked upon differently by patients on other clinical services, it is possible that patients on a different clinical unit or service may view this tool as less or more useful. Second, as the patients were not randomized to intervention, but rather based on the units to which they were admitted, it is possible that other variables, such as the experience of the unit staff, the patient's condition, and housestaff‐based service versus hospitalist‐based service may have played a role in how the patients perceived the use of DD notes. Third, patients were only surveyed if they were able to verbally communicate in English. These notes may not be as useful in hospital settings to populations with language or literacy barriers. Fourth, the logistical implementation of DD notes limited our ability to deliver the DD notepads in every patient's rooms, where only 78% of the intervention group received the DD notepads. This may be the reason that we did not find that overall satisfaction with physician communication differed between intervention and control groups. Nonetheless, we performed an intention‐to‐treat analysis to minimize any biases in our analysis. Last, although our survey of patients asked about their satisfaction in using the DD note pads, we did not compare these results with those of Press‐Ganey or HCAHPS scores of patients on the intervention group versus the control group. Additionally, lack of data about type, quality, and quantity of questions asked by a control group to see if the notepads actually improved quality of questions asked is a limitation; however, we believe our outcomes of interest were most specifically evaluated through our survey questions.

DD notes show that the majority of patients who use this tool feel a modest to significant improvement in communication with their providers. Although the quality of medical care is undoubtedly the first priority, the patients' view of their care, which includes communication, is arguably just as important. An often‐forgotten goal of hospitals and clinics is to provide service excellence along with high‐quality care. Thus, it is imperative for hospitals and their care providers to not only focus on the quality and safety of the clinical care, but also be mindful of the patient's entire experience throughout their hospital stay. Many of the categories of questions asked in the HCAHPS address the patient's experience and perspectives of hospital care. Furthermore, the role of the HCAHPS survey in the Value‐Based Purchasing rules may enhance the importance of these notepads. As the results of HCAHPS are becoming more transparent and available to the public, the impact of such results will have a greater significance to the future of the hospital's clinical mission.

CONCLUSION

DD notepads are a simple, low‐cost, patient‐centered tool that can be an effective reminder for patients to ask their healthcare providers questions related to their hospital care. Utilizing a common tool such as the notepad, redesigned for the healthcare setting, can serve to help healthcare providers interact with their patients. Patient satisfaction may be higher in patients who use the DD notepad.

In their seminal report Crossing the Quality Chasm, the Institute of Medicine outlined patient‐centered care as 1 of its 6 aims to improve the healthcare delivery system.[1] Patients who are more involved in their diagnosis and treatment plan are more likely to feel respected, be satisfied with their healthcare experience, and ultimately have better outcomes.[2, 3] In a study of hospitalized patients, only 42% were able to state their diagnosis at the time of discharge, suggesting that hospital providers could communicate better with patients about their hospital care.[4] Additionally, only 28% of hospitalized patients were able to list their medications, and only 37% were able to state the purpose of their medications. Although hospitals have taken great strides to improve the quality of patient care, publicly reported patient care surveys, such as the Hospital Consumer Assessment of Hospitals and Health Systems (HCAHPS), suggest that physician communication with patients could be further improved.[1, 5] Furthermore, a recent report by the Institute of Medicine stresses the need to get patients and families involved in their care.[6] Thus, hospital‐based providers should seek to enhance the quality of their communication with patients.

With greater emphasis placed on patient‐ and family‐centered care at many health systems, simple and easy‐to‐implement strategies to improve communication with patients need to be developed and tested.[7, 8] Patients who actively participate in their healthcare by asking questions of their doctor are able to control the focus of their interaction and adjust the amount of information provided.[9] Simply asking questions can have a critical impact, as 1 study found that the frequency with which patients asked questions was significantly related to the amount of information received about general and specific medical matters.[10] The notepad is a common tool for reminders and personal interactions that is used in everyday life, but has not been formalized in the hospital. We introduced Dear Doctor (DD) notes, a bedside notepad designed to prompt patient questions, with the goal of facilitating patient communication with their hospitalist physicians (Figure 1). As hospitalists provide direct and indirect care to a growing number of hospitalized patients, they are likely to be asked questions and opinions about the patients' diagnoses and plans. Furthermore, hospitalists are poised to lead institutional quality, safety, efficiency, and service improvement efforts in the inpatient setting. Becoming familiar with communication‐enhancing tools, such as the DD notes, may help hospitalists in their improvement team roles.

Figure 1

METHODS

RESULTS

Of the 440 patients surveyed in the intervention group (1 general medicine and 1 cardiology unit), 343 (78%) received the notepads in their rooms and 207 (47%) used them (Figure 2). Not every patient in the intervention group received DD notepads due to inconsistent placement of DD notepads upon every room turnover. Of the patients admitted to the control group (1 general medicine and 1 cardiology unit), 224 were surveyed. Fifty‐four percent of the 440 patients in the intervention group reported that they took notes related to their hospital care, compared to only 22% of the 224 patients in the control group (P < 0.001). Of the patients who took notes within the intervention group (n = 207), 91% of them utilized the DD notepads.

Figure 2

Patients in the intervention group who received and used the DD notes (n = 207) compared to patients in the control group (n = 224) were more likely to report that their questions were answered by their physicians (4.63 vs 4.45, P < 0.001). In an intention‐to‐treat analysis of all 440 patients in the intervention group, the overall satisfaction with physician communication was not significantly different between the intervention and control groups as measured on a 5‐point Likert scale (4.55 vs 4.55, P = 0.89). However, 89% of the patients in the intervention group who used the notepads felt that DD notepads either moderately or significantly improved their communication with their providers (Figure 3).

Figure 3

When the 207 patients who received DD notepads were asked how they used this tool, 99% of these patients used DD to write down questions, 82% to keep track of tests and procedures, and 54% indicated that their family and friends also used the notepads during the hospital stay (Table 1). Among these patients who utilized the DD notepads, 93% reported that they would use them again in the future.

Of the 97 patients in the intervention group who did not receive a DD notepad, we asked if they would use the DD notepad if they were made aware of such a tool. Of these patients, 77% agreed that they would use DD notes if they were made available in the future, 100% of them said that they would use DD to write down questions, 97% indicated that they would write notes about tests and procedures, and 88% of them believed that their families and friends would use DD notes.

DISCUSSION

As hospitals place greater emphasis and value on patient‐centered care as part of their clinical mission, it is important to develop tools to help facilitate the doctor‐patient relationship. We found that patients who were provided the Dear Doctor notepad were more satisfied that their doctors answered their questions and felt this tool enhanced their ability to communicate with their physicians. Employing the use of a familiar tool such as the notepad to remind patients about specific issues in their interactions with their providers can be a powerful intervention. Our study demonstrated that the DD notepad was widely accepted by patients, and that almost all of them would use this tool if it were made available to them in the future.

Other tools and methods to enhance the quality of communication between patients and their healthcare providers have included using whiteboards in the patients' rooms to relay the care plan to the patients, implementing bedside rounds by the healthcare team, and multidisciplinary huddling to coordinate information to the patient.[12, 13] Studies of these communication tools have shown potential to improve teamwork, interaction, and patient care. All of these have their own merit and value, and our DD notepad should be considered an adjunct to existing methods to enhance the patient care experience. A bedside tool that is familiar in form to most patients also needs to have the feature of easy access and use. Once this barrier has been removed for the patient and their family members, tools such as the DD notepad can impact the patient‐centeredness by fostering increased and better quality dialogue between the patients, their family members, and healthcare providers.

The DD notepad represents a means of communication that may have the potential to empower patients. It is possible that through question prompts, the DD notepad stimulates the patient to be an active partner with his or her healthcare team. This may enable patients to have some sense of control and accountability of their care in a setting where they would otherwise feel overwhelmed or powerless. The 3 general categories to help patients write down their questions included diagnosis, treatment plan, and medications. In the inpatient setting, where patient‐care activities can be fast paced, and patients are unable to recall some details when speaking to the healthcare team, these notes may remind the patient to write their thoughts down so that they may be remembered for a future time. In situations where patients may not know which questions to ask, the question prompts may be particularly helpful. We did not assess whether our particular question prompts were the key elements that resulted in their perceived value, or whether simply placing a blank notepad at the bedside would also have been successful. However, the specific questions were suggested by the focus groups. Enhanced communication, focusing on the patients' understanding of their condition, and the need to pursue certain diagnostic or therapeutic interventions, may help patients to be better prepared for the next course of plan. These topics of reasons for hospitalization, treatment plan, and medication changes are also important for patients to be active participants in their care, in particular as they transition from 1 site of care to the next, and their healthcare will be delivered by different providers.

There are several limitations to our study. First, this intervention was performed at a single hospital site with only 2 clinical services (general medicine, cardiology) represented in the study groups. Although we do not have any causal reasons to believe this tool would be looked upon differently by patients on other clinical services, it is possible that patients on a different clinical unit or service may view this tool as less or more useful. Second, as the patients were not randomized to intervention, but rather based on the units to which they were admitted, it is possible that other variables, such as the experience of the unit staff, the patient's condition, and housestaff‐based service versus hospitalist‐based service may have played a role in how the patients perceived the use of DD notes. Third, patients were only surveyed if they were able to verbally communicate in English. These notes may not be as useful in hospital settings to populations with language or literacy barriers. Fourth, the logistical implementation of DD notes limited our ability to deliver the DD notepads in every patient's rooms, where only 78% of the intervention group received the DD notepads. This may be the reason that we did not find that overall satisfaction with physician communication differed between intervention and control groups. Nonetheless, we performed an intention‐to‐treat analysis to minimize any biases in our analysis. Last, although our survey of patients asked about their satisfaction in using the DD note pads, we did not compare these results with those of Press‐Ganey or HCAHPS scores of patients on the intervention group versus the control group. Additionally, lack of data about type, quality, and quantity of questions asked by a control group to see if the notepads actually improved quality of questions asked is a limitation; however, we believe our outcomes of interest were most specifically evaluated through our survey questions.

DD notes show that the majority of patients who use this tool feel a modest to significant improvement in communication with their providers. Although the quality of medical care is undoubtedly the first priority, the patients' view of their care, which includes communication, is arguably just as important. An often‐forgotten goal of hospitals and clinics is to provide service excellence along with high‐quality care. Thus, it is imperative for hospitals and their care providers to not only focus on the quality and safety of the clinical care, but also be mindful of the patient's entire experience throughout their hospital stay. Many of the categories of questions asked in the HCAHPS address the patient's experience and perspectives of hospital care. Furthermore, the role of the HCAHPS survey in the Value‐Based Purchasing rules may enhance the importance of these notepads. As the results of HCAHPS are becoming more transparent and available to the public, the impact of such results will have a greater significance to the future of the hospital's clinical mission.

CONCLUSION

DD notepads are a simple, low‐cost, patient‐centered tool that can be an effective reminder for patients to ask their healthcare providers questions related to their hospital care. Utilizing a common tool such as the notepad, redesigned for the healthcare setting, can serve to help healthcare providers interact with their patients. Patient satisfaction may be higher in patients who use the DD notepad.

Patients hospitalized for acute medical illness have more than a 10‐fold increased risk for venous thromboembolism (VTE),[1] with an undeniably dramatic, negative impact on the lives of those afflicted, including fatal pulmonary embolism (PE), which most commonly affects patients on the medical service.[2, 3, 4] Yet estimates for the overall rate of VTE in this population are relatively low, raising questions about which subsets of medical patients warrant the risk and cost of prophylaxis.

Recently, the American College of Physicians published guidelines (ACP‐1)[5] and a supporting review[6] addressing VTE prophylaxis in nonsurgical inpatients, followed by publication of the American College of Chest Physicians (ACCP) 9th Edition of the Chest Guidelines on Antithrombotic Therapy and Prevention of Thrombosis (AT9),[7] which divides VTE prevention into 3 articles,[8, 9, 10] including 1 on nonsurgical patients.[8] Both ACP‐1 and AT9 differ significantly from the 2008 ACCP guidelines (AT8),[11] but took different approaches to methodology, risk assessment, and several other aspects of thromboprophylaxis (Table 1). This narrative review summarizes and compares these recommendations and the methods used to arrive at them, with a final section focusing on implications for improvement teams designing order sets and system changes to address VTE prophylaxis.

WHY ARE THE NEW GUIDELINES DIFFERENT?

Major randomized controlled trials (RCTs)[12, 13, 14] of thromboprophylaxis used routine deep vein thrombosis (DVT) surveillance and included both symptomatic (S‐VTE) and asymptomatic VTE (A‐VTE) end points. These studies consistently demonstrated 44% to 63% reductions in VTE without increases in major bleeding.[11] Because of the strong relationship between A‐VTE and S‐VTE outcomes, and a paucity of studies using only S‐VTE outcomes, AT8 judged that A‐VTE outcomes were valid to include, whereas the new guidelines reject the use of asymptomatic VTE end points.[5, 8, 15] To minimize financial and intellectual conflicts of interest, AT9 also used methodologists rather than VTE experts as topic editors, excluded conflicted experts from voting on recommendations, and attempted to estimate patient values and preferences.[15] As a result, AT9 makes fewer strong recommendations (182 1A recommendations in 2008, but only 29 in 2012), replacing them with weak suggestions.

WHAT DO THE NEW GUIDELINES RECOMMEND?

AT8 recommended anticoagulant prophylaxis for acutely ill medical inpatients with known risk factors, but did not recommend routine thromboprophylaxis. However, because of well‐known problems with underprophylaxis,[16, 17, 18, 19] particularly in medical patients, the low risk of bleeding, and difficulties with explicitly defining low‐risk patients, many discounted the need for VTE risk stratification.

Both new guidelines recommend prophylaxis for many nonsurgical patients, but discourage routine thromboprophylaxis for nonsurgical inpatients. AT9 specifically recommends against any thromboprophylaxis for low‐risk medical inpatients, implying that many nonsurgical, non‐critical care patients belong in this category, citing lower estimates of benefit, lower estimates of VTE risk, and potential bleeding risks.

The guidelines[5, 8] agree that, when indicated and absent contraindications, anticoagulant prophylaxis is preferred over mechanical prophylaxis, and agree there is insufficient evidence to recommend 1 anticoagulant over another.

For patients at risk of both VTE and bleeding, ACP‐1 states that intermittent pneumatic compression (IPC) devices are a reasonable option, given the evidence showing benefit in surgical patients. However, ACP‐1 recommends against graduated compression stockings (GCS) in nonsurgical patients based on a meta‐analysis dominated by the CLOTS‐1 (Clots in Legs Or sTockings after Stroke) trial, which found that thigh‐high GCS increased the risk of skin breakdown without reducing VTE[20] in immobilized stroke patients. AT9 does not recommend against GCS for patients facing bleeding and VTE risk. AT9 notes the hazards of generalizing results from stroke patients, and also considers the somewhat contradictory results from the CLOTS‐2 trial in stroke patients, which found a lower rate of VTE with thigh‐high GCS than with knee‐high GCS.[21] AT9 designates a recommendation of 2C for either IPC devices or thigh‐high GCS for those at VTE risk when anticoagulants are contraindicated.

Combination mechanical‐pharmacologic prophylaxis has proven superior in some surgical populations, and many hospitals use combined prophylaxis in high‐risk medical patients. However, combination prophylaxis has not been studied in this population. ACP‐1 does not comment on the practice; AT9 does not recommend for or against it. Institutions that use combination prophylaxis should be aware that although it may seem logical to extrapolate estimates of benefit seen in selected surgical patients, this is not a recommended practice.

RCTs for thromboprophylaxis in nonsurgical inpatients provided prophylaxis for 6 to 21 days. Neither ACP‐1 or AT9 recommend routinely extending prophylaxis beyond the hospital stay, citing an RCT[22] in which the benefit of extended duration low molecular weight heparin was limited to selected subsets of patients and offset by bleeding complications. AT9 suggests prophylaxis for 6 to 21 days, until full mobility is restored, or until dischargewhichever comes first.[8] However, we know of no study that establishes a mobility level at which prophylaxis can be safely discontinued, especially in inpatients with multiple risk factors.

ESTIMATING RISK AND BENEFIT OF PROPHYLAXIS AND LIMITATIONS OF METHODS

Calculating risk/benefit ratios for thromboprophylaxis requires estimates of baseline VTE and bleeding risks, and estimates of the impact of prophylaxis on those baseline risks. Methods to estimate the impact of prophylaxis on S‐VTE from studies relying on A‐VTE all have limitations, as acknowledged by the AT9 introduction.[15]

The ACP‐1 review found the only significant effect of prophylaxis on medical inpatients was a modest reduction in PE and a modest increase in total bleeding events, without effects on major bleeding, DVT, or mortality.[6] The authors summarized the findings as indicative of little or no net benefit for the medical population as a whole. The ACP‐1 review derives estimates of S‐VTE risk, bleeding, and mortality from control (baseline) and interventional arms of RCTs that used routine VTE screening, and included A‐VTE end points. The baseline risk of VTE could potentially be overestimated, because the populations in the trials are not representative of the entire medical population.

On the other hand, pooling trials with screening‐detected VTE to estimate S‐VTE outcomes is a questionable practice that may falsely lower estimates of VTE prophylaxis benefit. Screening‐detected VTE may be treated or declared a study end point before it becomes symptomatic. MEDENOX (Medical Patients With Enoxaparin) is an illustrative example.[12] The 263 placebo recipients suffered 37 A‐VTEs and 4 S‐VTEs. The 272 enoxaparin recipients suffered 17 A‐VTEs and 3 S‐VTEs. Patients at the highest risk of S‐VTE were counted as reaching an end point before they could develop symptoms; this happened more than twice as often in the placebo arm. This decreases both estimates of baseline VTE risk and the measured benefit of prophylaxis for S‐VTE. Screening could conceivably reduce measured effects on mortality as well, because patients begin VTE therapy earlier. Per ACP‐1, the estimated risk for DVT is lower than for PE, running counter to literature experience[8, 16] and raising issues of face validity. The ACP‐1 review accepts all original definitions of major bleeding, including a 2 g/dL drop in hemoglobin,[12] which commonly occurs without any bleeding or clinical consequence, and bleeding events were ascribed to heparins up to 120 days after randomization, long after they could have been responsible.

Previous meta‐analyses of thromboprophylaxis studies[23, 24] shared many of these same limitations, but did not ascribe bleeding complications to heparins for this extended duration, and had point estimates that suggested a larger impact from prophylaxis than ACP‐1. Dentali et al., for example, showed statistically significant impact on PE (relative risk [RR] 0.43), fatal PE (RR 0.38), and a nearly statistically significant large impact on DVT (RR 0.47, 95% confidence interval [CI]: 0.22‐1.00),[24] whereas ACP‐1 estimated a smaller significant impact on PE (RR 0.69), no significant difference in fatal PE, and a much smaller estimate of the impact on DVT (RR 0.78, 95% CI: 0.45‐1.35) (Table 2).

AT9 used a variety of methods to estimate each component of the risk/benefit equation. Critical care and non‐critical care estimates were generated independently, but because of limited data, the critical care estimates were highly imprecise. In non‐critical care patients, as in ACP‐1, treatment effects were estimated from RCTs that routinely screened for A‐VTE, and they adapted the Dentali et al. estimate of DVT risk reduction. The baseline risk for bleeding and mortality were derived from the control population of the same meta‐analysis.[24]

Using a novel approach, AT9 estimated baseline nonsurgical VTE risk from a prospective observational cohort study of 1180 medical inpatients divided into high‐ and low‐risk groups by a point‐scoring system.[25] Deriving risk estimates from an observational cohort has theoretical advantages. Many patients did not receive prophylaxis, allowing for unadjusted risk estimates; they represented a cross‐section of medical inpatients rather than a selected trial population, and risk estimates were not reduced by the culling of screen‐detected A‐VTE.

The Padua risk‐assessment model (RAM) (Table 3) defines high VTE risk as a cumulative score 4. There were 60.3% of patients at low risk and 39.7% at high risk using this threshold. Among unprophylaxed patients, VTE occurred in 11% of high‐risk patients versus 0.3% of low‐risk patients (hazard ratio 32.0, 95% CI: 4.1251.0).

PADUA: A CLOSER LOOK

In the Padua study, 60% of the population appeared to be at such low risk for VTE that prophylaxis would seem unnecessary, but closer scrutiny should raise concern about generalizing these results. Of the 711 low‐risk patients, <1% were immobile, only 6% had cancer, 6% were obese, and only 12% had any acute infection or inflammatory condition, yet their mean length of stay was 7.9 days. These characteristics do not apply to 60% of American inpatients. Furthermore, 964 of 2208 eligible patients (44%) were excluded because they required therapeutic anticoagulation.[25]

Correspondence with the authors revealed that the 2 PEs in patients with Padua scores 4 occurred among 192 patients with a risk score of 3 (Figure 1), a 1% (2/192) risk of PE. This is a very small sample, and the true risk of VTE for medical inpatients with a risk score of 3 may be lower or significantly higher. In the Padua population, a risk score of 3 equated to a VTE risk of 6.9%, whereas those with a score of 0 to 2 had no VTE. For those adapting the Padua model, careful consideration of using a cutoff of 3, versus 4, is warranted.

Figure 1

IMPLICATIONS FOR VTE PROTOCOL IMPLEMENTATION AND IMPROVEMENT TEAMS

AT9 and ACP‐1 sought to focus on S‐VTE, remove bias from recommendations, and highlight potential risks of unnecessary prophylaxis in low‐risk patients. They have largely succeeded in these important goals. However, the complexity of the new guidelines and lack of consensus about VTE risk assessment pose significant challenges to improvement teams tasked with implementing the guidelines in real‐world settings.

CHOOSING A VTE RAM

The fundamental question is: How can hospitals assess VTE risk, assure adequate prophylaxis for patients who need it, while minimizing excess prophylaxis, in a practical, efficient way?

BOTTOM LINE IN CHOOSING A VTE RAM

Many medical inpatients are at high risk for VTE, but others are not at sufficient risk to warrant prophylaxis. VTE risk assessment should be embedded in admission, transfer, and perioperative order sets and may need a hard stop to insure completion. There is a trend to favor individualized point‐based models over models that place patients in groups of risk, but evidence is insufficient to recommend 1 type of RAM over another, and more complex point‐based models often require extensive local customization and algorithmic clinical decision support to effectively implement them. Centers without advanced capability may find the bucket models more effective. We urge improvement teams to trial their RAM with common patient case scenarios, and to make a choice based on an effort‐benefit analysis, feedback from their clinicians, and the level of customization in clinical decision support available to them.

OTHER IMPLEMENTATION STRATEGIES

VTE and bleeding risk change during hospitalization. We have used ongoing daily surveillance and measurement of patients on no prophylaxis to prompt concurrent intervention (ie, measure‐vention) to increase prophylaxis for patients at risk.[28] Improvement teams should focus not only on increasing prophylaxis for those at risk, but should also use measure‐vention, checklists, or other techniques to identify low‐risk (eg, ambulating) patients for cessation of overly aggressive prophylaxis. Efforts to improve early progressive ambulation, limit central venous catheters to those who truly need them, and improve adherence to mechanical prophylaxis can also reduce VTE, as well as benefitting patient populations in other ways.

We recognize there are several approaches to close the implementation gap in delivering thromboprophylaxis judiciously but reliably, and encourage research and publication of varied strategies. Last, we hope efforts to limit unnecessary prophylaxis and challenges inherent in implementing new and complex guidelines do not increase the morbidity and mortality of hospital‐acquired VTE, by derailing the delivery of prophylaxis to those in whom the benefits outweigh the risks.

Patients hospitalized for acute medical illness have more than a 10‐fold increased risk for venous thromboembolism (VTE),[1] with an undeniably dramatic, negative impact on the lives of those afflicted, including fatal pulmonary embolism (PE), which most commonly affects patients on the medical service.[2, 3, 4] Yet estimates for the overall rate of VTE in this population are relatively low, raising questions about which subsets of medical patients warrant the risk and cost of prophylaxis.

Recently, the American College of Physicians published guidelines (ACP‐1)[5] and a supporting review[6] addressing VTE prophylaxis in nonsurgical inpatients, followed by publication of the American College of Chest Physicians (ACCP) 9th Edition of the Chest Guidelines on Antithrombotic Therapy and Prevention of Thrombosis (AT9),[7] which divides VTE prevention into 3 articles,[8, 9, 10] including 1 on nonsurgical patients.[8] Both ACP‐1 and AT9 differ significantly from the 2008 ACCP guidelines (AT8),[11] but took different approaches to methodology, risk assessment, and several other aspects of thromboprophylaxis (Table 1). This narrative review summarizes and compares these recommendations and the methods used to arrive at them, with a final section focusing on implications for improvement teams designing order sets and system changes to address VTE prophylaxis.

WHY ARE THE NEW GUIDELINES DIFFERENT?

Major randomized controlled trials (RCTs)[12, 13, 14] of thromboprophylaxis used routine deep vein thrombosis (DVT) surveillance and included both symptomatic (S‐VTE) and asymptomatic VTE (A‐VTE) end points. These studies consistently demonstrated 44% to 63% reductions in VTE without increases in major bleeding.[11] Because of the strong relationship between A‐VTE and S‐VTE outcomes, and a paucity of studies using only S‐VTE outcomes, AT8 judged that A‐VTE outcomes were valid to include, whereas the new guidelines reject the use of asymptomatic VTE end points.[5, 8, 15] To minimize financial and intellectual conflicts of interest, AT9 also used methodologists rather than VTE experts as topic editors, excluded conflicted experts from voting on recommendations, and attempted to estimate patient values and preferences.[15] As a result, AT9 makes fewer strong recommendations (182 1A recommendations in 2008, but only 29 in 2012), replacing them with weak suggestions.

WHAT DO THE NEW GUIDELINES RECOMMEND?

AT8 recommended anticoagulant prophylaxis for acutely ill medical inpatients with known risk factors, but did not recommend routine thromboprophylaxis. However, because of well‐known problems with underprophylaxis,[16, 17, 18, 19] particularly in medical patients, the low risk of bleeding, and difficulties with explicitly defining low‐risk patients, many discounted the need for VTE risk stratification.

Both new guidelines recommend prophylaxis for many nonsurgical patients, but discourage routine thromboprophylaxis for nonsurgical inpatients. AT9 specifically recommends against any thromboprophylaxis for low‐risk medical inpatients, implying that many nonsurgical, non‐critical care patients belong in this category, citing lower estimates of benefit, lower estimates of VTE risk, and potential bleeding risks.

The guidelines[5, 8] agree that, when indicated and absent contraindications, anticoagulant prophylaxis is preferred over mechanical prophylaxis, and agree there is insufficient evidence to recommend 1 anticoagulant over another.

For patients at risk of both VTE and bleeding, ACP‐1 states that intermittent pneumatic compression (IPC) devices are a reasonable option, given the evidence showing benefit in surgical patients. However, ACP‐1 recommends against graduated compression stockings (GCS) in nonsurgical patients based on a meta‐analysis dominated by the CLOTS‐1 (Clots in Legs Or sTockings after Stroke) trial, which found that thigh‐high GCS increased the risk of skin breakdown without reducing VTE[20] in immobilized stroke patients. AT9 does not recommend against GCS for patients facing bleeding and VTE risk. AT9 notes the hazards of generalizing results from stroke patients, and also considers the somewhat contradictory results from the CLOTS‐2 trial in stroke patients, which found a lower rate of VTE with thigh‐high GCS than with knee‐high GCS.[21] AT9 designates a recommendation of 2C for either IPC devices or thigh‐high GCS for those at VTE risk when anticoagulants are contraindicated.

Combination mechanical‐pharmacologic prophylaxis has proven superior in some surgical populations, and many hospitals use combined prophylaxis in high‐risk medical patients. However, combination prophylaxis has not been studied in this population. ACP‐1 does not comment on the practice; AT9 does not recommend for or against it. Institutions that use combination prophylaxis should be aware that although it may seem logical to extrapolate estimates of benefit seen in selected surgical patients, this is not a recommended practice.

RCTs for thromboprophylaxis in nonsurgical inpatients provided prophylaxis for 6 to 21 days. Neither ACP‐1 or AT9 recommend routinely extending prophylaxis beyond the hospital stay, citing an RCT[22] in which the benefit of extended duration low molecular weight heparin was limited to selected subsets of patients and offset by bleeding complications. AT9 suggests prophylaxis for 6 to 21 days, until full mobility is restored, or until dischargewhichever comes first.[8] However, we know of no study that establishes a mobility level at which prophylaxis can be safely discontinued, especially in inpatients with multiple risk factors.

ESTIMATING RISK AND BENEFIT OF PROPHYLAXIS AND LIMITATIONS OF METHODS

Calculating risk/benefit ratios for thromboprophylaxis requires estimates of baseline VTE and bleeding risks, and estimates of the impact of prophylaxis on those baseline risks. Methods to estimate the impact of prophylaxis on S‐VTE from studies relying on A‐VTE all have limitations, as acknowledged by the AT9 introduction.[15]

The ACP‐1 review found the only significant effect of prophylaxis on medical inpatients was a modest reduction in PE and a modest increase in total bleeding events, without effects on major bleeding, DVT, or mortality.[6] The authors summarized the findings as indicative of little or no net benefit for the medical population as a whole. The ACP‐1 review derives estimates of S‐VTE risk, bleeding, and mortality from control (baseline) and interventional arms of RCTs that used routine VTE screening, and included A‐VTE end points. The baseline risk of VTE could potentially be overestimated, because the populations in the trials are not representative of the entire medical population.

On the other hand, pooling trials with screening‐detected VTE to estimate S‐VTE outcomes is a questionable practice that may falsely lower estimates of VTE prophylaxis benefit. Screening‐detected VTE may be treated or declared a study end point before it becomes symptomatic. MEDENOX (Medical Patients With Enoxaparin) is an illustrative example.[12] The 263 placebo recipients suffered 37 A‐VTEs and 4 S‐VTEs. The 272 enoxaparin recipients suffered 17 A‐VTEs and 3 S‐VTEs. Patients at the highest risk of S‐VTE were counted as reaching an end point before they could develop symptoms; this happened more than twice as often in the placebo arm. This decreases both estimates of baseline VTE risk and the measured benefit of prophylaxis for S‐VTE. Screening could conceivably reduce measured effects on mortality as well, because patients begin VTE therapy earlier. Per ACP‐1, the estimated risk for DVT is lower than for PE, running counter to literature experience[8, 16] and raising issues of face validity. The ACP‐1 review accepts all original definitions of major bleeding, including a 2 g/dL drop in hemoglobin,[12] which commonly occurs without any bleeding or clinical consequence, and bleeding events were ascribed to heparins up to 120 days after randomization, long after they could have been responsible.

Previous meta‐analyses of thromboprophylaxis studies[23, 24] shared many of these same limitations, but did not ascribe bleeding complications to heparins for this extended duration, and had point estimates that suggested a larger impact from prophylaxis than ACP‐1. Dentali et al., for example, showed statistically significant impact on PE (relative risk [RR] 0.43), fatal PE (RR 0.38), and a nearly statistically significant large impact on DVT (RR 0.47, 95% confidence interval [CI]: 0.22‐1.00),[24] whereas ACP‐1 estimated a smaller significant impact on PE (RR 0.69), no significant difference in fatal PE, and a much smaller estimate of the impact on DVT (RR 0.78, 95% CI: 0.45‐1.35) (Table 2).

AT9 used a variety of methods to estimate each component of the risk/benefit equation. Critical care and non‐critical care estimates were generated independently, but because of limited data, the critical care estimates were highly imprecise. In non‐critical care patients, as in ACP‐1, treatment effects were estimated from RCTs that routinely screened for A‐VTE, and they adapted the Dentali et al. estimate of DVT risk reduction. The baseline risk for bleeding and mortality were derived from the control population of the same meta‐analysis.[24]

Using a novel approach, AT9 estimated baseline nonsurgical VTE risk from a prospective observational cohort study of 1180 medical inpatients divided into high‐ and low‐risk groups by a point‐scoring system.[25] Deriving risk estimates from an observational cohort has theoretical advantages. Many patients did not receive prophylaxis, allowing for unadjusted risk estimates; they represented a cross‐section of medical inpatients rather than a selected trial population, and risk estimates were not reduced by the culling of screen‐detected A‐VTE.

The Padua risk‐assessment model (RAM) (Table 3) defines high VTE risk as a cumulative score 4. There were 60.3% of patients at low risk and 39.7% at high risk using this threshold. Among unprophylaxed patients, VTE occurred in 11% of high‐risk patients versus 0.3% of low‐risk patients (hazard ratio 32.0, 95% CI: 4.1251.0).

PADUA: A CLOSER LOOK

In the Padua study, 60% of the population appeared to be at such low risk for VTE that prophylaxis would seem unnecessary, but closer scrutiny should raise concern about generalizing these results. Of the 711 low‐risk patients, <1% were immobile, only 6% had cancer, 6% were obese, and only 12% had any acute infection or inflammatory condition, yet their mean length of stay was 7.9 days. These characteristics do not apply to 60% of American inpatients. Furthermore, 964 of 2208 eligible patients (44%) were excluded because they required therapeutic anticoagulation.[25]

Correspondence with the authors revealed that the 2 PEs in patients with Padua scores 4 occurred among 192 patients with a risk score of 3 (Figure 1), a 1% (2/192) risk of PE. This is a very small sample, and the true risk of VTE for medical inpatients with a risk score of 3 may be lower or significantly higher. In the Padua population, a risk score of 3 equated to a VTE risk of 6.9%, whereas those with a score of 0 to 2 had no VTE. For those adapting the Padua model, careful consideration of using a cutoff of 3, versus 4, is warranted.

Figure 1

IMPLICATIONS FOR VTE PROTOCOL IMPLEMENTATION AND IMPROVEMENT TEAMS

AT9 and ACP‐1 sought to focus on S‐VTE, remove bias from recommendations, and highlight potential risks of unnecessary prophylaxis in low‐risk patients. They have largely succeeded in these important goals. However, the complexity of the new guidelines and lack of consensus about VTE risk assessment pose significant challenges to improvement teams tasked with implementing the guidelines in real‐world settings.

CHOOSING A VTE RAM

The fundamental question is: How can hospitals assess VTE risk, assure adequate prophylaxis for patients who need it, while minimizing excess prophylaxis, in a practical, efficient way?

BOTTOM LINE IN CHOOSING A VTE RAM

Many medical inpatients are at high risk for VTE, but others are not at sufficient risk to warrant prophylaxis. VTE risk assessment should be embedded in admission, transfer, and perioperative order sets and may need a hard stop to insure completion. There is a trend to favor individualized point‐based models over models that place patients in groups of risk, but evidence is insufficient to recommend 1 type of RAM over another, and more complex point‐based models often require extensive local customization and algorithmic clinical decision support to effectively implement them. Centers without advanced capability may find the bucket models more effective. We urge improvement teams to trial their RAM with common patient case scenarios, and to make a choice based on an effort‐benefit analysis, feedback from their clinicians, and the level of customization in clinical decision support available to them.

OTHER IMPLEMENTATION STRATEGIES

VTE and bleeding risk change during hospitalization. We have used ongoing daily surveillance and measurement of patients on no prophylaxis to prompt concurrent intervention (ie, measure‐vention) to increase prophylaxis for patients at risk.[28] Improvement teams should focus not only on increasing prophylaxis for those at risk, but should also use measure‐vention, checklists, or other techniques to identify low‐risk (eg, ambulating) patients for cessation of overly aggressive prophylaxis. Efforts to improve early progressive ambulation, limit central venous catheters to those who truly need them, and improve adherence to mechanical prophylaxis can also reduce VTE, as well as benefitting patient populations in other ways.

We recognize there are several approaches to close the implementation gap in delivering thromboprophylaxis judiciously but reliably, and encourage research and publication of varied strategies. Last, we hope efforts to limit unnecessary prophylaxis and challenges inherent in implementing new and complex guidelines do not increase the morbidity and mortality of hospital‐acquired VTE, by derailing the delivery of prophylaxis to those in whom the benefits outweigh the risks.

Patients hospitalized for acute medical illness have more than a 10‐fold increased risk for venous thromboembolism (VTE),[1] with an undeniably dramatic, negative impact on the lives of those afflicted, including fatal pulmonary embolism (PE), which most commonly affects patients on the medical service.[2, 3, 4] Yet estimates for the overall rate of VTE in this population are relatively low, raising questions about which subsets of medical patients warrant the risk and cost of prophylaxis.

Recently, the American College of Physicians published guidelines (ACP‐1)[5] and a supporting review[6] addressing VTE prophylaxis in nonsurgical inpatients, followed by publication of the American College of Chest Physicians (ACCP) 9th Edition of the Chest Guidelines on Antithrombotic Therapy and Prevention of Thrombosis (AT9),[7] which divides VTE prevention into 3 articles,[8, 9, 10] including 1 on nonsurgical patients.[8] Both ACP‐1 and AT9 differ significantly from the 2008 ACCP guidelines (AT8),[11] but took different approaches to methodology, risk assessment, and several other aspects of thromboprophylaxis (Table 1). This narrative review summarizes and compares these recommendations and the methods used to arrive at them, with a final section focusing on implications for improvement teams designing order sets and system changes to address VTE prophylaxis.

WHY ARE THE NEW GUIDELINES DIFFERENT?

Major randomized controlled trials (RCTs)[12, 13, 14] of thromboprophylaxis used routine deep vein thrombosis (DVT) surveillance and included both symptomatic (S‐VTE) and asymptomatic VTE (A‐VTE) end points. These studies consistently demonstrated 44% to 63% reductions in VTE without increases in major bleeding.[11] Because of the strong relationship between A‐VTE and S‐VTE outcomes, and a paucity of studies using only S‐VTE outcomes, AT8 judged that A‐VTE outcomes were valid to include, whereas the new guidelines reject the use of asymptomatic VTE end points.[5, 8, 15] To minimize financial and intellectual conflicts of interest, AT9 also used methodologists rather than VTE experts as topic editors, excluded conflicted experts from voting on recommendations, and attempted to estimate patient values and preferences.[15] As a result, AT9 makes fewer strong recommendations (182 1A recommendations in 2008, but only 29 in 2012), replacing them with weak suggestions.

WHAT DO THE NEW GUIDELINES RECOMMEND?

AT8 recommended anticoagulant prophylaxis for acutely ill medical inpatients with known risk factors, but did not recommend routine thromboprophylaxis. However, because of well‐known problems with underprophylaxis,[16, 17, 18, 19] particularly in medical patients, the low risk of bleeding, and difficulties with explicitly defining low‐risk patients, many discounted the need for VTE risk stratification.

Both new guidelines recommend prophylaxis for many nonsurgical patients, but discourage routine thromboprophylaxis for nonsurgical inpatients. AT9 specifically recommends against any thromboprophylaxis for low‐risk medical inpatients, implying that many nonsurgical, non‐critical care patients belong in this category, citing lower estimates of benefit, lower estimates of VTE risk, and potential bleeding risks.

The guidelines[5, 8] agree that, when indicated and absent contraindications, anticoagulant prophylaxis is preferred over mechanical prophylaxis, and agree there is insufficient evidence to recommend 1 anticoagulant over another.

For patients at risk of both VTE and bleeding, ACP‐1 states that intermittent pneumatic compression (IPC) devices are a reasonable option, given the evidence showing benefit in surgical patients. However, ACP‐1 recommends against graduated compression stockings (GCS) in nonsurgical patients based on a meta‐analysis dominated by the CLOTS‐1 (Clots in Legs Or sTockings after Stroke) trial, which found that thigh‐high GCS increased the risk of skin breakdown without reducing VTE[20] in immobilized stroke patients. AT9 does not recommend against GCS for patients facing bleeding and VTE risk. AT9 notes the hazards of generalizing results from stroke patients, and also considers the somewhat contradictory results from the CLOTS‐2 trial in stroke patients, which found a lower rate of VTE with thigh‐high GCS than with knee‐high GCS.[21] AT9 designates a recommendation of 2C for either IPC devices or thigh‐high GCS for those at VTE risk when anticoagulants are contraindicated.

Combination mechanical‐pharmacologic prophylaxis has proven superior in some surgical populations, and many hospitals use combined prophylaxis in high‐risk medical patients. However, combination prophylaxis has not been studied in this population. ACP‐1 does not comment on the practice; AT9 does not recommend for or against it. Institutions that use combination prophylaxis should be aware that although it may seem logical to extrapolate estimates of benefit seen in selected surgical patients, this is not a recommended practice.

RCTs for thromboprophylaxis in nonsurgical inpatients provided prophylaxis for 6 to 21 days. Neither ACP‐1 or AT9 recommend routinely extending prophylaxis beyond the hospital stay, citing an RCT[22] in which the benefit of extended duration low molecular weight heparin was limited to selected subsets of patients and offset by bleeding complications. AT9 suggests prophylaxis for 6 to 21 days, until full mobility is restored, or until dischargewhichever comes first.[8] However, we know of no study that establishes a mobility level at which prophylaxis can be safely discontinued, especially in inpatients with multiple risk factors.

ESTIMATING RISK AND BENEFIT OF PROPHYLAXIS AND LIMITATIONS OF METHODS

Calculating risk/benefit ratios for thromboprophylaxis requires estimates of baseline VTE and bleeding risks, and estimates of the impact of prophylaxis on those baseline risks. Methods to estimate the impact of prophylaxis on S‐VTE from studies relying on A‐VTE all have limitations, as acknowledged by the AT9 introduction.[15]

The ACP‐1 review found the only significant effect of prophylaxis on medical inpatients was a modest reduction in PE and a modest increase in total bleeding events, without effects on major bleeding, DVT, or mortality.[6] The authors summarized the findings as indicative of little or no net benefit for the medical population as a whole. The ACP‐1 review derives estimates of S‐VTE risk, bleeding, and mortality from control (baseline) and interventional arms of RCTs that used routine VTE screening, and included A‐VTE end points. The baseline risk of VTE could potentially be overestimated, because the populations in the trials are not representative of the entire medical population.

On the other hand, pooling trials with screening‐detected VTE to estimate S‐VTE outcomes is a questionable practice that may falsely lower estimates of VTE prophylaxis benefit. Screening‐detected VTE may be treated or declared a study end point before it becomes symptomatic. MEDENOX (Medical Patients With Enoxaparin) is an illustrative example.[12] The 263 placebo recipients suffered 37 A‐VTEs and 4 S‐VTEs. The 272 enoxaparin recipients suffered 17 A‐VTEs and 3 S‐VTEs. Patients at the highest risk of S‐VTE were counted as reaching an end point before they could develop symptoms; this happened more than twice as often in the placebo arm. This decreases both estimates of baseline VTE risk and the measured benefit of prophylaxis for S‐VTE. Screening could conceivably reduce measured effects on mortality as well, because patients begin VTE therapy earlier. Per ACP‐1, the estimated risk for DVT is lower than for PE, running counter to literature experience[8, 16] and raising issues of face validity. The ACP‐1 review accepts all original definitions of major bleeding, including a 2 g/dL drop in hemoglobin,[12] which commonly occurs without any bleeding or clinical consequence, and bleeding events were ascribed to heparins up to 120 days after randomization, long after they could have been responsible.

Previous meta‐analyses of thromboprophylaxis studies[23, 24] shared many of these same limitations, but did not ascribe bleeding complications to heparins for this extended duration, and had point estimates that suggested a larger impact from prophylaxis than ACP‐1. Dentali et al., for example, showed statistically significant impact on PE (relative risk [RR] 0.43), fatal PE (RR 0.38), and a nearly statistically significant large impact on DVT (RR 0.47, 95% confidence interval [CI]: 0.22‐1.00),[24] whereas ACP‐1 estimated a smaller significant impact on PE (RR 0.69), no significant difference in fatal PE, and a much smaller estimate of the impact on DVT (RR 0.78, 95% CI: 0.45‐1.35) (Table 2).

AT9 used a variety of methods to estimate each component of the risk/benefit equation. Critical care and non‐critical care estimates were generated independently, but because of limited data, the critical care estimates were highly imprecise. In non‐critical care patients, as in ACP‐1, treatment effects were estimated from RCTs that routinely screened for A‐VTE, and they adapted the Dentali et al. estimate of DVT risk reduction. The baseline risk for bleeding and mortality were derived from the control population of the same meta‐analysis.[24]

Using a novel approach, AT9 estimated baseline nonsurgical VTE risk from a prospective observational cohort study of 1180 medical inpatients divided into high‐ and low‐risk groups by a point‐scoring system.[25] Deriving risk estimates from an observational cohort has theoretical advantages. Many patients did not receive prophylaxis, allowing for unadjusted risk estimates; they represented a cross‐section of medical inpatients rather than a selected trial population, and risk estimates were not reduced by the culling of screen‐detected A‐VTE.

The Padua risk‐assessment model (RAM) (Table 3) defines high VTE risk as a cumulative score 4. There were 60.3% of patients at low risk and 39.7% at high risk using this threshold. Among unprophylaxed patients, VTE occurred in 11% of high‐risk patients versus 0.3% of low‐risk patients (hazard ratio 32.0, 95% CI: 4.1251.0).

PADUA: A CLOSER LOOK

In the Padua study, 60% of the population appeared to be at such low risk for VTE that prophylaxis would seem unnecessary, but closer scrutiny should raise concern about generalizing these results. Of the 711 low‐risk patients, <1% were immobile, only 6% had cancer, 6% were obese, and only 12% had any acute infection or inflammatory condition, yet their mean length of stay was 7.9 days. These characteristics do not apply to 60% of American inpatients. Furthermore, 964 of 2208 eligible patients (44%) were excluded because they required therapeutic anticoagulation.[25]

Correspondence with the authors revealed that the 2 PEs in patients with Padua scores 4 occurred among 192 patients with a risk score of 3 (Figure 1), a 1% (2/192) risk of PE. This is a very small sample, and the true risk of VTE for medical inpatients with a risk score of 3 may be lower or significantly higher. In the Padua population, a risk score of 3 equated to a VTE risk of 6.9%, whereas those with a score of 0 to 2 had no VTE. For those adapting the Padua model, careful consideration of using a cutoff of 3, versus 4, is warranted.

Figure 1

IMPLICATIONS FOR VTE PROTOCOL IMPLEMENTATION AND IMPROVEMENT TEAMS

AT9 and ACP‐1 sought to focus on S‐VTE, remove bias from recommendations, and highlight potential risks of unnecessary prophylaxis in low‐risk patients. They have largely succeeded in these important goals. However, the complexity of the new guidelines and lack of consensus about VTE risk assessment pose significant challenges to improvement teams tasked with implementing the guidelines in real‐world settings.

CHOOSING A VTE RAM

The fundamental question is: How can hospitals assess VTE risk, assure adequate prophylaxis for patients who need it, while minimizing excess prophylaxis, in a practical, efficient way?

BOTTOM LINE IN CHOOSING A VTE RAM

Many medical inpatients are at high risk for VTE, but others are not at sufficient risk to warrant prophylaxis. VTE risk assessment should be embedded in admission, transfer, and perioperative order sets and may need a hard stop to insure completion. There is a trend to favor individualized point‐based models over models that place patients in groups of risk, but evidence is insufficient to recommend 1 type of RAM over another, and more complex point‐based models often require extensive local customization and algorithmic clinical decision support to effectively implement them. Centers without advanced capability may find the bucket models more effective. We urge improvement teams to trial their RAM with common patient case scenarios, and to make a choice based on an effort‐benefit analysis, feedback from their clinicians, and the level of customization in clinical decision support available to them.

OTHER IMPLEMENTATION STRATEGIES

VTE and bleeding risk change during hospitalization. We have used ongoing daily surveillance and measurement of patients on no prophylaxis to prompt concurrent intervention (ie, measure‐vention) to increase prophylaxis for patients at risk.[28] Improvement teams should focus not only on increasing prophylaxis for those at risk, but should also use measure‐vention, checklists, or other techniques to identify low‐risk (eg, ambulating) patients for cessation of overly aggressive prophylaxis. Efforts to improve early progressive ambulation, limit central venous catheters to those who truly need them, and improve adherence to mechanical prophylaxis can also reduce VTE, as well as benefitting patient populations in other ways.

We recognize there are several approaches to close the implementation gap in delivering thromboprophylaxis judiciously but reliably, and encourage research and publication of varied strategies. Last, we hope efforts to limit unnecessary prophylaxis and challenges inherent in implementing new and complex guidelines do not increase the morbidity and mortality of hospital‐acquired VTE, by derailing the delivery of prophylaxis to those in whom the benefits outweigh the risks.