Michael B. Streiff, MD

The Affordable Care Act explicitly outlines improving the value of healthcare by increasing quality and decreasing costs. It emphasizes value‐based purchasing, the transparency of performance metrics, and the use of payment incentives to reward quality.[1, 2] Venous thromboembolism (VTE) prophylaxis is one of these publicly reported performance measures. The National Quality Forum recommends that each patient be evaluated on hospital admission and during their hospitalization for VTE risk level and for appropriate thromboprophylaxis to be used, if required.[3] Similarly, the Joint Commission includes appropriate VTE prophylaxis in its Core Measures.[4] Patient experience and performance metrics, including VTE prophylaxis, constitute the hospital value‐based purchasing (VBP) component of healthcare reform.[5] For a hypothetical 327‐bed hospital, an estimated $1.7 million of a hospital's inpatient payments from Medicare will be at risk from VBP alone.[2]

VTE prophylaxis is a common target of quality improvement projects. Effective, safe, and cost‐effective measures to prevent VTE exist, including pharmacologic and mechanical prophylaxis.[6, 7] Despite these measures, compliance rates are often below 50%.[8] Different interventions have been pursued to ensure appropriate VTE prophylaxis, including computerized provider order entry (CPOE), electronic alerts, mandatory VTE risk assessment and prophylaxis, and provider education campaigns.[9] Recent studies show that CPOE systems with mandatory fields can increase VTE prophylaxis rates to above 80%, yet the goal of a high reliability health system is for 100% of patients to receive recommended therapy.[10, 11, 12, 13, 14, 15] Interventions to improve prophylaxis rates that have included multiple strategies, such as computerized order sets, feedback, and education, have been the most effective, increasing compliance to above 90%.[9, 11, 16] These systems can be enhanced with additional interventions such as providing individualized provider education and feedback, understanding of work flow, and ensuring patients receive the prescribed therapies.[12] For example, a physician dashboard could be employed to provide a snapshot and historical trend of key performance indicators using graphical displays and indicators.[17]

Dashboards and pay‐for‐performance programs have been increasingly used to increase the visibility of these metrics, provide feedback, visually display benchmarks and goals, and proactively monitor for achievements and setbacks.[18] Although these strategies are often addressed at departmental (or greater) levels, applying them at the level of the individual provider may assist hospitals in reducing preventable harm and achieving safety and quality goals, especially at higher benchmarks. With their expanding role, hospitalists provide a key opportunity to lead improvement efforts and to study the impact of dashboards and pay‐for performance at the provider level to achieve VTE prophylaxis performance targets. Hospitalists are often the front‐line provider for inpatients and deliver up to 70% of inpatient general medical services.[19] The objective of our study was to evaluate the impact of providing individual provider feedback and employing a pay‐for‐performance program on baseline performance of VTE prophylaxis among hospitalists. We hypothesized that performance feedback through the use of a dashboard would increase appropriate VTE prophylaxis, and this effect would be further augmented by incorporation of a pay‐for‐performance program.

METHODS

Hospitalist Dashboard

In 2010, hospitalist program leaders met with hospital administrators to create a hospitalist dashboard that would provide regularly updated summaries of performance measures for individual hospitalists. The final set of metrics identified included appropriate VTE prophylaxis, length of stay, patients discharged per day, discharges before 3 _pm, depth of coding, patient satisfaction, readmissions, communication with the primary care provider, and time to signature for discharge summaries (Figure 1A). The dashboard was introduced at a general hospitalist meeting during which its purpose, methodology, and accessibility were described; it was subsequently implemented in January 2011.

Figure 1

Benchmarks were established for each metric, standardized to establish a scale ranging from 1 through 9, and incorporated into the dashboard (Figure 1A). Higher scores (creating a larger geometric shape) were desirable. For the VTE prophylaxis measure, scores of 1 through 9 corresponded to <60%, 60% to 64.9%, 65% to 69.9%, 70% to 74.9%, 75% to 79.9%, 80% to 84.9%, 85% to 89.9%, 90% to 94.9%, and 95% American College of Chest Physicians (ACCP)‐compliant VTE prophylaxis, respectively.[12, 20] Each provider was able to access the aggregated dashboard (showing the group mean) and his/her individualized dashboard using an individualized login and password for the institutional portal. This portal is used during the provider's workflow, including medical record review and order entry. Both a polygonal summary graphic (Figure 1A) and trend (Figure 1B) view of the dashboard were available to the provider. A comparison of the individual provider to the hospitalist group average was displayed (Figure 1A). At monthly program meetings, the dashboard, group results, and trends were discussed.

Venous Thromboembolism Prophylaxis Compliance

Our study was performed in a tertiary academic medical center with an approximately 20‐member hospitalist group (the precise membership varied over time), whose responsibilities include, among other clinical duties, staffing a 17‐bed general medicine unit with telemetry. The scope of diagnoses and acuity of patients admitted to the hospitalist service is similar to the housestaff services. Some hospitalist faculty serve both as hospitalist and nonhospitalist general medicine service team attendings, but the comparison groups were staffed by hospitalists for <20% of the time. For admissions, all hospitalists use a standardized general medicine admission order set that is integrated into the CPOE system (Sunrise Clinical Manager; Allscripts, Chicago, IL) and completed for all admitted patients. A mandatory VTE risk screen, which includes an assessment of VTE risk factors and pharmacological prophylaxis contraindications, must be completed by the ordering physician as part of this order set (Figure 2A). The system then prompts the provider with a risk‐appropriate VTE prophylaxis recommendation that the provider may subsequently order, including mechanical prophylaxis (Figure 2B). Based on ACCP VTE prevention guidelines, risk‐appropriate prophylaxis was determined using an electronic algorithm that categorized patients into risk categories based on the presence of major VTE risk factors (Figure 2A).[12, 15, 20] If none of these were present, the provider selected No major risk factors known. Both an assessment of current use of anticoagulation and a clinically high risk of bleeding were also included (Figure 2A). If none of these were present, the provider selected No contraindications known. This algorithm is published in detail elsewhere and has been shown to not increase major bleeding episodes.[12, 15] The VTE risk assessment, but not the VTE order itself, was a mandatory field. This allowed the physician discretion to choose among various pharmacological agents and mechanical mechanisms based on patient and physician preferences.

Figure 2

Compliance of risk‐appropriate VTE prophylaxis was determined 24 hours after the admission order set was completed using an automated electronic query of the CPOE system. Low molecular‐weight heparin prescription was included in the compliance algorithm as acceptable prophylaxis. Prescription of pharmacological VTE prophylaxis when a contraindication was present was considered noncompliant. The metric was assigned to the attending physician who billed for the first inpatient encounter.

RESULTS

Venous Thromboembolism Prophylaxis Compliance

We analyzed 3144 inpatient admissions by 38 hospitalists from 2009 to 2012. The 5 most frequent coded diagnoses were heart failure, acute kidney failure, syncope, pneumonia, and chest pain. Patients had a median length of stay of 3 days [interquartile range: 26]. During the dashboard‐only period, on average, providers improved in compliance by 4% (95% confidence interval [CI]: 35; P<0.001). With the addition of the pay‐for‐performance program, providers improved by an additional 4% (95% CI: 35; P<0.001). Group compliance significantly improved from 86% (95% CI: 8588) during the BASE period of the CPOE‐based VTE order set to 90% (95% CI: 8893) during the DASH period (P=0.01) and 94% (95% CI: 9396) during the subsequent P4P program (P=0.01) (Figure 3). Both inappropriate prophylaxis and lack of prophylaxis, when indicated, resulted in a non‐compliance rating. During the 3 periods, inappropriate prophylaxis decreased from 7.9% to 6.2% to 2.6% during the BASE, DASH, and subsequent P4P periods, respectively. Similarly, lack of prophylaxis when indicated decreased from 6.1% to 3.2% to 3.1% during the BASE, DASH, and subsequent P4P periods, respectively.

Figure 3

The average compliance of the 4 non‐hospitalist general medicine service teams was initially higher than that of the hospitalist service during the CPOE‐based VTE order set (90%) and DASH (92%) periods, but subsequently plateaued and was exceeded by the hospitalist service during the combined P4P (92%) period (Figure 3). However, there was no statistically significant difference between the general medicine service teams and hospitalist service during the DASH (P=0.15) and subsequent P4P (P=0.76) periods.

We also analyzed the rate of VTE prophylaxis compliance improvement (slope) with cut points at each time period transition (Figure 3). Risk‐appropriate VTE prophylaxis during the BASE period did not exhibit significant improvement as indicated by the slope (P=0.23) (Figure 3). In contrast, during the DASH period, VTE prophylaxis compliance significantly increased by 1.58% per month (95% CI: 0.41‐2.76; P=0.01). The addition of the P4P program, however, did not further significantly increase the rate of compliance (P=0.78).

A subgroup analysis restricted to the 19 providers present during all 3 periods was performed to assess for potential confounding from physician turnover. The percent compliance increased in a similar fashion: BASE period of CPOE‐based VTE order set, 85% (95% CI: 8386); DASH, 90% (95% CI: 8893); and P4P, 94% (95% CI: 9296).

DISCUSSION

A key component of healthcare reform has been value‐based purchasing, which emphasizes extrinsic motivation through the transparency of performance metrics and use of payment incentives to reward quality. Our study evaluates the impact of both extrinsic (payments) and intrinsic (professionalism and peer norms) motivation. It specifically attributed an individual performance metric, VTE prophylaxis, to an attending physician, provided both individualized and group feedback using an electronic dashboard, and incorporated a pay‐for‐performance program. Prescription of risk‐appropriate VTE prophylaxis significantly increased with the implementation of the dashboard and subsequent pay‐for performance program. The fastest rate of improvement occurred after the addition of the dashboard. Sensitivity analyses for provider turnover and comparisons to the general medicine services showed our results to be independent of a general trend of improvement, both at the provider and institutional levels.

Our prior studies demonstrated that order sets significantly improve performance, from a baseline compliance of risk‐appropriate VTE prophylaxis of 66% to 84%.[13, 15, 25] In the current study, compliance was relatively flat during the BASE period, which included these order sets. The greatest rate of continued improvement in compliance occurred during the DASH period, emphasizing both the importance of provider feedback and receptivity and adaptability in the prescribing behavior of hospitalists. Because the goal of a high‐reliability health system is for 100% of patients to receive recommended therapy, multiple approaches are necessary for success.

Nationally, benchmarks for performance measures continue to be raised, with the highest performers achieving above 95%.[26] Additional interventions, such as dashboards and pay‐for‐performance programs, supplement CPOE systems to achieve high reliability. In our study, the compliance rate during the baseline period, which included a CPOE‐based, clinical support‐enabled VTE order set, was 86%. Initially the compliance of the general medicine teams with residents exceeded that of the hospitalist attending teams, which may reflect a greater willingness of resident teams to comply with order sets and automated recommendations. This emphasizes the importance of continuous individual feedback and provider education at the attending physician level to enhance both guideline compliance and decrease provider care variation. Ultimately, with the addition of the dashboard and subsequent pay‐for‐performance program, compliance was increased to 90% and 94%, respectively. Although the major mechanism used by policymakers to improve quality of care is extrinsic motivation, this study demonstrates that intrinsic motivation through peer norms can enhance extrinsic efforts and may be more influential. Both of these programs, dashboards and pay‐for‐performance, may ultimately assist institutions in changing provider behavior and achieving these harder‐to‐achieve higher benchmarks.

We recognize that there are several limitations to our study. First, this is a single‐site program limited to an attending‐physician‐only service. There was strong data support and a defined CPOE algorithm for this initiative. Multi‐site studies will need to overcome the additional challenges of varying service structures and electronic medical record and provider order entry systems. Second, it is difficult to show actual changes in VTE events over time with appropriate prophylaxis. Although VTE prophylaxis is recommended for patients with VTE risk factors, there are conflicting findings about whether prophylaxis prevents VTE events in lower‐risk patients, and current studies suggest that most patients with VTE events are severely ill and develop VTE despite receiving prophylaxis.[27, 28, 29] Our study was underpowered to detect these potential differences in VTE rates, and although the algorithm has been shown to not increase bleeding rates, we did not measure bleeding rates during this study.[12, 15] Our institutional experience suggests that the majority of VTE events occur despite appropriate prophylaxis.[30] Also, VTE prophylaxis may be ordered, but intervening events, such as procedures and changes in risk status or patient refusal, may prevent patients from receiving appropriate prophylaxis.[31, 32] Similarly, hospitals with higher quality scores have higher VTE prophylaxis rates but worse risk‐adjusted VTE rates, which may result from increased surveillance for VTE, suggesting surveillance bias limits the usefulness of the VTE quality measure.[33, 34] Nevertheless, VTE prophylaxis remains a publicly reported Core Measure tied to financial incentives.[4, 5] Third, there may be an unmeasured factor specific to the hospitalist program, which could potentially account for an overall improvement in quality of care. Although the rate of increase in appropriate prophylaxis was not statistically significant during the baseline period, there did appear to be some improvement in prophylaxis toward the end of the period. However, there were no other VTE‐related provider feedback programs being simultaneously pursued during this study. VTE prophylaxis for the non‐hospitalist services showed a relatively stable, non‐increasing compliance rate for the general medical services. Although it was possible for successful residents to age into the hospitalist service, thereby improving rates of prophylaxis based on changes in group makeup, our subgroup analysis of the providers present throughout all phases of the study showed our results to be robust. Similarly, there may have been a cross‐contamination effect of hospitalist faculty who attended on both hospitalist and non‐hospitalist general medicine service teams. This, however, would attenuate any impact of the programs, and thus the effects may in fact be greater than reported. Fourth, establishment of both the dashboard and pay‐for‐performance program required significant institutional and program leadership and resources. To be successful, the dashboard must be in the provider's workflow, transparent, minimize reporter burden, use existing systems, and be actively fed back to providers, ideally those directly entering orders. Our greatest rate of improvement occurred during the feedback‐only phase of this study, emphasizing the importance of physician feedback, provider‐level accountability, and engagement. We suspect that the relatively modest pay‐for‐performance incentive served mainly as a means of engaging providers in self‐monitoring, rather than as a means to change behavior through true incentivization. Although we did not track individual physician views of the dashboard, we reinforced trends, deviations, and expectations at regularly scheduled meetings and provided feedback and patient‐level data to individual providers. Fifth, the design of the pay‐for‐performance program may have also influenced its effectiveness. These types of programs may be more effective when they provide frequent visible, small payments rather than one large payment, and when the payment is framed as a loss rather than a gain.[35] Finally, physician champions and consistent feedback through departmental meetings or visual displays may be required for program success. The initial resources to create the dashboard, continued maintenance and monitoring of performance, and payment of financial incentives all require institutional commitment. A partnership of physicians, program leaders, and institutional administrators is necessary for both initial and continued success.

To achieve performance goals and benchmarks, multiple strategies that combine extrinsic and intrinsic motivation are necessary. As shown by our study, the use of a dashboard and pay‐for‐performance can be tailored to an institution's goals, in line with national standards. The specific goal (risk‐appropriate VTE prophylaxis) and benchmarks (80%, 85%, 90%, 95%) can be individualized to a particular institution. For example, if readmission rates are above target, readmissions could be added as a dashboard metric. The specific benchmark would be determined by historical trends and administrative targets. Similarly, the overall financial incentives could be adjusted based on the financial resources available. Other process measures, such as influenza vaccination screening and administration, could also be targeted. For all of these objectives, continued provider feedback and engagement are critical for progressive success, especially to decrease variability in care at the attending physician level. Incorporating the value‐based purchasing philosophy from the Affordable Care Act, our study suggests that the combination of standardized order sets, real‐time dashboards, and physician‐level incentives may assist hospitals in achieving quality and safety benchmarks, especially at higher targets.

The Affordable Care Act explicitly outlines improving the value of healthcare by increasing quality and decreasing costs. It emphasizes value‐based purchasing, the transparency of performance metrics, and the use of payment incentives to reward quality.[1, 2] Venous thromboembolism (VTE) prophylaxis is one of these publicly reported performance measures. The National Quality Forum recommends that each patient be evaluated on hospital admission and during their hospitalization for VTE risk level and for appropriate thromboprophylaxis to be used, if required.[3] Similarly, the Joint Commission includes appropriate VTE prophylaxis in its Core Measures.[4] Patient experience and performance metrics, including VTE prophylaxis, constitute the hospital value‐based purchasing (VBP) component of healthcare reform.[5] For a hypothetical 327‐bed hospital, an estimated $1.7 million of a hospital's inpatient payments from Medicare will be at risk from VBP alone.[2]

VTE prophylaxis is a common target of quality improvement projects. Effective, safe, and cost‐effective measures to prevent VTE exist, including pharmacologic and mechanical prophylaxis.[6, 7] Despite these measures, compliance rates are often below 50%.[8] Different interventions have been pursued to ensure appropriate VTE prophylaxis, including computerized provider order entry (CPOE), electronic alerts, mandatory VTE risk assessment and prophylaxis, and provider education campaigns.[9] Recent studies show that CPOE systems with mandatory fields can increase VTE prophylaxis rates to above 80%, yet the goal of a high reliability health system is for 100% of patients to receive recommended therapy.[10, 11, 12, 13, 14, 15] Interventions to improve prophylaxis rates that have included multiple strategies, such as computerized order sets, feedback, and education, have been the most effective, increasing compliance to above 90%.[9, 11, 16] These systems can be enhanced with additional interventions such as providing individualized provider education and feedback, understanding of work flow, and ensuring patients receive the prescribed therapies.[12] For example, a physician dashboard could be employed to provide a snapshot and historical trend of key performance indicators using graphical displays and indicators.[17]

Dashboards and pay‐for‐performance programs have been increasingly used to increase the visibility of these metrics, provide feedback, visually display benchmarks and goals, and proactively monitor for achievements and setbacks.[18] Although these strategies are often addressed at departmental (or greater) levels, applying them at the level of the individual provider may assist hospitals in reducing preventable harm and achieving safety and quality goals, especially at higher benchmarks. With their expanding role, hospitalists provide a key opportunity to lead improvement efforts and to study the impact of dashboards and pay‐for performance at the provider level to achieve VTE prophylaxis performance targets. Hospitalists are often the front‐line provider for inpatients and deliver up to 70% of inpatient general medical services.[19] The objective of our study was to evaluate the impact of providing individual provider feedback and employing a pay‐for‐performance program on baseline performance of VTE prophylaxis among hospitalists. We hypothesized that performance feedback through the use of a dashboard would increase appropriate VTE prophylaxis, and this effect would be further augmented by incorporation of a pay‐for‐performance program.

METHODS

Hospitalist Dashboard

In 2010, hospitalist program leaders met with hospital administrators to create a hospitalist dashboard that would provide regularly updated summaries of performance measures for individual hospitalists. The final set of metrics identified included appropriate VTE prophylaxis, length of stay, patients discharged per day, discharges before 3 _pm, depth of coding, patient satisfaction, readmissions, communication with the primary care provider, and time to signature for discharge summaries (Figure 1A). The dashboard was introduced at a general hospitalist meeting during which its purpose, methodology, and accessibility were described; it was subsequently implemented in January 2011.

Figure 1

Benchmarks were established for each metric, standardized to establish a scale ranging from 1 through 9, and incorporated into the dashboard (Figure 1A). Higher scores (creating a larger geometric shape) were desirable. For the VTE prophylaxis measure, scores of 1 through 9 corresponded to <60%, 60% to 64.9%, 65% to 69.9%, 70% to 74.9%, 75% to 79.9%, 80% to 84.9%, 85% to 89.9%, 90% to 94.9%, and 95% American College of Chest Physicians (ACCP)‐compliant VTE prophylaxis, respectively.[12, 20] Each provider was able to access the aggregated dashboard (showing the group mean) and his/her individualized dashboard using an individualized login and password for the institutional portal. This portal is used during the provider's workflow, including medical record review and order entry. Both a polygonal summary graphic (Figure 1A) and trend (Figure 1B) view of the dashboard were available to the provider. A comparison of the individual provider to the hospitalist group average was displayed (Figure 1A). At monthly program meetings, the dashboard, group results, and trends were discussed.

Venous Thromboembolism Prophylaxis Compliance

Our study was performed in a tertiary academic medical center with an approximately 20‐member hospitalist group (the precise membership varied over time), whose responsibilities include, among other clinical duties, staffing a 17‐bed general medicine unit with telemetry. The scope of diagnoses and acuity of patients admitted to the hospitalist service is similar to the housestaff services. Some hospitalist faculty serve both as hospitalist and nonhospitalist general medicine service team attendings, but the comparison groups were staffed by hospitalists for <20% of the time. For admissions, all hospitalists use a standardized general medicine admission order set that is integrated into the CPOE system (Sunrise Clinical Manager; Allscripts, Chicago, IL) and completed for all admitted patients. A mandatory VTE risk screen, which includes an assessment of VTE risk factors and pharmacological prophylaxis contraindications, must be completed by the ordering physician as part of this order set (Figure 2A). The system then prompts the provider with a risk‐appropriate VTE prophylaxis recommendation that the provider may subsequently order, including mechanical prophylaxis (Figure 2B). Based on ACCP VTE prevention guidelines, risk‐appropriate prophylaxis was determined using an electronic algorithm that categorized patients into risk categories based on the presence of major VTE risk factors (Figure 2A).[12, 15, 20] If none of these were present, the provider selected No major risk factors known. Both an assessment of current use of anticoagulation and a clinically high risk of bleeding were also included (Figure 2A). If none of these were present, the provider selected No contraindications known. This algorithm is published in detail elsewhere and has been shown to not increase major bleeding episodes.[12, 15] The VTE risk assessment, but not the VTE order itself, was a mandatory field. This allowed the physician discretion to choose among various pharmacological agents and mechanical mechanisms based on patient and physician preferences.

Figure 2

Compliance of risk‐appropriate VTE prophylaxis was determined 24 hours after the admission order set was completed using an automated electronic query of the CPOE system. Low molecular‐weight heparin prescription was included in the compliance algorithm as acceptable prophylaxis. Prescription of pharmacological VTE prophylaxis when a contraindication was present was considered noncompliant. The metric was assigned to the attending physician who billed for the first inpatient encounter.

RESULTS

Venous Thromboembolism Prophylaxis Compliance

We analyzed 3144 inpatient admissions by 38 hospitalists from 2009 to 2012. The 5 most frequent coded diagnoses were heart failure, acute kidney failure, syncope, pneumonia, and chest pain. Patients had a median length of stay of 3 days [interquartile range: 26]. During the dashboard‐only period, on average, providers improved in compliance by 4% (95% confidence interval [CI]: 35; P<0.001). With the addition of the pay‐for‐performance program, providers improved by an additional 4% (95% CI: 35; P<0.001). Group compliance significantly improved from 86% (95% CI: 8588) during the BASE period of the CPOE‐based VTE order set to 90% (95% CI: 8893) during the DASH period (P=0.01) and 94% (95% CI: 9396) during the subsequent P4P program (P=0.01) (Figure 3). Both inappropriate prophylaxis and lack of prophylaxis, when indicated, resulted in a non‐compliance rating. During the 3 periods, inappropriate prophylaxis decreased from 7.9% to 6.2% to 2.6% during the BASE, DASH, and subsequent P4P periods, respectively. Similarly, lack of prophylaxis when indicated decreased from 6.1% to 3.2% to 3.1% during the BASE, DASH, and subsequent P4P periods, respectively.

Figure 3

The average compliance of the 4 non‐hospitalist general medicine service teams was initially higher than that of the hospitalist service during the CPOE‐based VTE order set (90%) and DASH (92%) periods, but subsequently plateaued and was exceeded by the hospitalist service during the combined P4P (92%) period (Figure 3). However, there was no statistically significant difference between the general medicine service teams and hospitalist service during the DASH (P=0.15) and subsequent P4P (P=0.76) periods.

We also analyzed the rate of VTE prophylaxis compliance improvement (slope) with cut points at each time period transition (Figure 3). Risk‐appropriate VTE prophylaxis during the BASE period did not exhibit significant improvement as indicated by the slope (P=0.23) (Figure 3). In contrast, during the DASH period, VTE prophylaxis compliance significantly increased by 1.58% per month (95% CI: 0.41‐2.76; P=0.01). The addition of the P4P program, however, did not further significantly increase the rate of compliance (P=0.78).

A subgroup analysis restricted to the 19 providers present during all 3 periods was performed to assess for potential confounding from physician turnover. The percent compliance increased in a similar fashion: BASE period of CPOE‐based VTE order set, 85% (95% CI: 8386); DASH, 90% (95% CI: 8893); and P4P, 94% (95% CI: 9296).

DISCUSSION

A key component of healthcare reform has been value‐based purchasing, which emphasizes extrinsic motivation through the transparency of performance metrics and use of payment incentives to reward quality. Our study evaluates the impact of both extrinsic (payments) and intrinsic (professionalism and peer norms) motivation. It specifically attributed an individual performance metric, VTE prophylaxis, to an attending physician, provided both individualized and group feedback using an electronic dashboard, and incorporated a pay‐for‐performance program. Prescription of risk‐appropriate VTE prophylaxis significantly increased with the implementation of the dashboard and subsequent pay‐for performance program. The fastest rate of improvement occurred after the addition of the dashboard. Sensitivity analyses for provider turnover and comparisons to the general medicine services showed our results to be independent of a general trend of improvement, both at the provider and institutional levels.

Our prior studies demonstrated that order sets significantly improve performance, from a baseline compliance of risk‐appropriate VTE prophylaxis of 66% to 84%.[13, 15, 25] In the current study, compliance was relatively flat during the BASE period, which included these order sets. The greatest rate of continued improvement in compliance occurred during the DASH period, emphasizing both the importance of provider feedback and receptivity and adaptability in the prescribing behavior of hospitalists. Because the goal of a high‐reliability health system is for 100% of patients to receive recommended therapy, multiple approaches are necessary for success.

Nationally, benchmarks for performance measures continue to be raised, with the highest performers achieving above 95%.[26] Additional interventions, such as dashboards and pay‐for‐performance programs, supplement CPOE systems to achieve high reliability. In our study, the compliance rate during the baseline period, which included a CPOE‐based, clinical support‐enabled VTE order set, was 86%. Initially the compliance of the general medicine teams with residents exceeded that of the hospitalist attending teams, which may reflect a greater willingness of resident teams to comply with order sets and automated recommendations. This emphasizes the importance of continuous individual feedback and provider education at the attending physician level to enhance both guideline compliance and decrease provider care variation. Ultimately, with the addition of the dashboard and subsequent pay‐for‐performance program, compliance was increased to 90% and 94%, respectively. Although the major mechanism used by policymakers to improve quality of care is extrinsic motivation, this study demonstrates that intrinsic motivation through peer norms can enhance extrinsic efforts and may be more influential. Both of these programs, dashboards and pay‐for‐performance, may ultimately assist institutions in changing provider behavior and achieving these harder‐to‐achieve higher benchmarks.

We recognize that there are several limitations to our study. First, this is a single‐site program limited to an attending‐physician‐only service. There was strong data support and a defined CPOE algorithm for this initiative. Multi‐site studies will need to overcome the additional challenges of varying service structures and electronic medical record and provider order entry systems. Second, it is difficult to show actual changes in VTE events over time with appropriate prophylaxis. Although VTE prophylaxis is recommended for patients with VTE risk factors, there are conflicting findings about whether prophylaxis prevents VTE events in lower‐risk patients, and current studies suggest that most patients with VTE events are severely ill and develop VTE despite receiving prophylaxis.[27, 28, 29] Our study was underpowered to detect these potential differences in VTE rates, and although the algorithm has been shown to not increase bleeding rates, we did not measure bleeding rates during this study.[12, 15] Our institutional experience suggests that the majority of VTE events occur despite appropriate prophylaxis.[30] Also, VTE prophylaxis may be ordered, but intervening events, such as procedures and changes in risk status or patient refusal, may prevent patients from receiving appropriate prophylaxis.[31, 32] Similarly, hospitals with higher quality scores have higher VTE prophylaxis rates but worse risk‐adjusted VTE rates, which may result from increased surveillance for VTE, suggesting surveillance bias limits the usefulness of the VTE quality measure.[33, 34] Nevertheless, VTE prophylaxis remains a publicly reported Core Measure tied to financial incentives.[4, 5] Third, there may be an unmeasured factor specific to the hospitalist program, which could potentially account for an overall improvement in quality of care. Although the rate of increase in appropriate prophylaxis was not statistically significant during the baseline period, there did appear to be some improvement in prophylaxis toward the end of the period. However, there were no other VTE‐related provider feedback programs being simultaneously pursued during this study. VTE prophylaxis for the non‐hospitalist services showed a relatively stable, non‐increasing compliance rate for the general medical services. Although it was possible for successful residents to age into the hospitalist service, thereby improving rates of prophylaxis based on changes in group makeup, our subgroup analysis of the providers present throughout all phases of the study showed our results to be robust. Similarly, there may have been a cross‐contamination effect of hospitalist faculty who attended on both hospitalist and non‐hospitalist general medicine service teams. This, however, would attenuate any impact of the programs, and thus the effects may in fact be greater than reported. Fourth, establishment of both the dashboard and pay‐for‐performance program required significant institutional and program leadership and resources. To be successful, the dashboard must be in the provider's workflow, transparent, minimize reporter burden, use existing systems, and be actively fed back to providers, ideally those directly entering orders. Our greatest rate of improvement occurred during the feedback‐only phase of this study, emphasizing the importance of physician feedback, provider‐level accountability, and engagement. We suspect that the relatively modest pay‐for‐performance incentive served mainly as a means of engaging providers in self‐monitoring, rather than as a means to change behavior through true incentivization. Although we did not track individual physician views of the dashboard, we reinforced trends, deviations, and expectations at regularly scheduled meetings and provided feedback and patient‐level data to individual providers. Fifth, the design of the pay‐for‐performance program may have also influenced its effectiveness. These types of programs may be more effective when they provide frequent visible, small payments rather than one large payment, and when the payment is framed as a loss rather than a gain.[35] Finally, physician champions and consistent feedback through departmental meetings or visual displays may be required for program success. The initial resources to create the dashboard, continued maintenance and monitoring of performance, and payment of financial incentives all require institutional commitment. A partnership of physicians, program leaders, and institutional administrators is necessary for both initial and continued success.

To achieve performance goals and benchmarks, multiple strategies that combine extrinsic and intrinsic motivation are necessary. As shown by our study, the use of a dashboard and pay‐for‐performance can be tailored to an institution's goals, in line with national standards. The specific goal (risk‐appropriate VTE prophylaxis) and benchmarks (80%, 85%, 90%, 95%) can be individualized to a particular institution. For example, if readmission rates are above target, readmissions could be added as a dashboard metric. The specific benchmark would be determined by historical trends and administrative targets. Similarly, the overall financial incentives could be adjusted based on the financial resources available. Other process measures, such as influenza vaccination screening and administration, could also be targeted. For all of these objectives, continued provider feedback and engagement are critical for progressive success, especially to decrease variability in care at the attending physician level. Incorporating the value‐based purchasing philosophy from the Affordable Care Act, our study suggests that the combination of standardized order sets, real‐time dashboards, and physician‐level incentives may assist hospitals in achieving quality and safety benchmarks, especially at higher targets.

The Affordable Care Act explicitly outlines improving the value of healthcare by increasing quality and decreasing costs. It emphasizes value‐based purchasing, the transparency of performance metrics, and the use of payment incentives to reward quality.[1, 2] Venous thromboembolism (VTE) prophylaxis is one of these publicly reported performance measures. The National Quality Forum recommends that each patient be evaluated on hospital admission and during their hospitalization for VTE risk level and for appropriate thromboprophylaxis to be used, if required.[3] Similarly, the Joint Commission includes appropriate VTE prophylaxis in its Core Measures.[4] Patient experience and performance metrics, including VTE prophylaxis, constitute the hospital value‐based purchasing (VBP) component of healthcare reform.[5] For a hypothetical 327‐bed hospital, an estimated $1.7 million of a hospital's inpatient payments from Medicare will be at risk from VBP alone.[2]

VTE prophylaxis is a common target of quality improvement projects. Effective, safe, and cost‐effective measures to prevent VTE exist, including pharmacologic and mechanical prophylaxis.[6, 7] Despite these measures, compliance rates are often below 50%.[8] Different interventions have been pursued to ensure appropriate VTE prophylaxis, including computerized provider order entry (CPOE), electronic alerts, mandatory VTE risk assessment and prophylaxis, and provider education campaigns.[9] Recent studies show that CPOE systems with mandatory fields can increase VTE prophylaxis rates to above 80%, yet the goal of a high reliability health system is for 100% of patients to receive recommended therapy.[10, 11, 12, 13, 14, 15] Interventions to improve prophylaxis rates that have included multiple strategies, such as computerized order sets, feedback, and education, have been the most effective, increasing compliance to above 90%.[9, 11, 16] These systems can be enhanced with additional interventions such as providing individualized provider education and feedback, understanding of work flow, and ensuring patients receive the prescribed therapies.[12] For example, a physician dashboard could be employed to provide a snapshot and historical trend of key performance indicators using graphical displays and indicators.[17]

Dashboards and pay‐for‐performance programs have been increasingly used to increase the visibility of these metrics, provide feedback, visually display benchmarks and goals, and proactively monitor for achievements and setbacks.[18] Although these strategies are often addressed at departmental (or greater) levels, applying them at the level of the individual provider may assist hospitals in reducing preventable harm and achieving safety and quality goals, especially at higher benchmarks. With their expanding role, hospitalists provide a key opportunity to lead improvement efforts and to study the impact of dashboards and pay‐for performance at the provider level to achieve VTE prophylaxis performance targets. Hospitalists are often the front‐line provider for inpatients and deliver up to 70% of inpatient general medical services.[19] The objective of our study was to evaluate the impact of providing individual provider feedback and employing a pay‐for‐performance program on baseline performance of VTE prophylaxis among hospitalists. We hypothesized that performance feedback through the use of a dashboard would increase appropriate VTE prophylaxis, and this effect would be further augmented by incorporation of a pay‐for‐performance program.

METHODS

Hospitalist Dashboard

In 2010, hospitalist program leaders met with hospital administrators to create a hospitalist dashboard that would provide regularly updated summaries of performance measures for individual hospitalists. The final set of metrics identified included appropriate VTE prophylaxis, length of stay, patients discharged per day, discharges before 3 _pm, depth of coding, patient satisfaction, readmissions, communication with the primary care provider, and time to signature for discharge summaries (Figure 1A). The dashboard was introduced at a general hospitalist meeting during which its purpose, methodology, and accessibility were described; it was subsequently implemented in January 2011.

Figure 1

Benchmarks were established for each metric, standardized to establish a scale ranging from 1 through 9, and incorporated into the dashboard (Figure 1A). Higher scores (creating a larger geometric shape) were desirable. For the VTE prophylaxis measure, scores of 1 through 9 corresponded to <60%, 60% to 64.9%, 65% to 69.9%, 70% to 74.9%, 75% to 79.9%, 80% to 84.9%, 85% to 89.9%, 90% to 94.9%, and 95% American College of Chest Physicians (ACCP)‐compliant VTE prophylaxis, respectively.[12, 20] Each provider was able to access the aggregated dashboard (showing the group mean) and his/her individualized dashboard using an individualized login and password for the institutional portal. This portal is used during the provider's workflow, including medical record review and order entry. Both a polygonal summary graphic (Figure 1A) and trend (Figure 1B) view of the dashboard were available to the provider. A comparison of the individual provider to the hospitalist group average was displayed (Figure 1A). At monthly program meetings, the dashboard, group results, and trends were discussed.

Venous Thromboembolism Prophylaxis Compliance

Our study was performed in a tertiary academic medical center with an approximately 20‐member hospitalist group (the precise membership varied over time), whose responsibilities include, among other clinical duties, staffing a 17‐bed general medicine unit with telemetry. The scope of diagnoses and acuity of patients admitted to the hospitalist service is similar to the housestaff services. Some hospitalist faculty serve both as hospitalist and nonhospitalist general medicine service team attendings, but the comparison groups were staffed by hospitalists for <20% of the time. For admissions, all hospitalists use a standardized general medicine admission order set that is integrated into the CPOE system (Sunrise Clinical Manager; Allscripts, Chicago, IL) and completed for all admitted patients. A mandatory VTE risk screen, which includes an assessment of VTE risk factors and pharmacological prophylaxis contraindications, must be completed by the ordering physician as part of this order set (Figure 2A). The system then prompts the provider with a risk‐appropriate VTE prophylaxis recommendation that the provider may subsequently order, including mechanical prophylaxis (Figure 2B). Based on ACCP VTE prevention guidelines, risk‐appropriate prophylaxis was determined using an electronic algorithm that categorized patients into risk categories based on the presence of major VTE risk factors (Figure 2A).[12, 15, 20] If none of these were present, the provider selected No major risk factors known. Both an assessment of current use of anticoagulation and a clinically high risk of bleeding were also included (Figure 2A). If none of these were present, the provider selected No contraindications known. This algorithm is published in detail elsewhere and has been shown to not increase major bleeding episodes.[12, 15] The VTE risk assessment, but not the VTE order itself, was a mandatory field. This allowed the physician discretion to choose among various pharmacological agents and mechanical mechanisms based on patient and physician preferences.

Figure 2

Compliance of risk‐appropriate VTE prophylaxis was determined 24 hours after the admission order set was completed using an automated electronic query of the CPOE system. Low molecular‐weight heparin prescription was included in the compliance algorithm as acceptable prophylaxis. Prescription of pharmacological VTE prophylaxis when a contraindication was present was considered noncompliant. The metric was assigned to the attending physician who billed for the first inpatient encounter.

RESULTS

Venous Thromboembolism Prophylaxis Compliance

We analyzed 3144 inpatient admissions by 38 hospitalists from 2009 to 2012. The 5 most frequent coded diagnoses were heart failure, acute kidney failure, syncope, pneumonia, and chest pain. Patients had a median length of stay of 3 days [interquartile range: 26]. During the dashboard‐only period, on average, providers improved in compliance by 4% (95% confidence interval [CI]: 35; P<0.001). With the addition of the pay‐for‐performance program, providers improved by an additional 4% (95% CI: 35; P<0.001). Group compliance significantly improved from 86% (95% CI: 8588) during the BASE period of the CPOE‐based VTE order set to 90% (95% CI: 8893) during the DASH period (P=0.01) and 94% (95% CI: 9396) during the subsequent P4P program (P=0.01) (Figure 3). Both inappropriate prophylaxis and lack of prophylaxis, when indicated, resulted in a non‐compliance rating. During the 3 periods, inappropriate prophylaxis decreased from 7.9% to 6.2% to 2.6% during the BASE, DASH, and subsequent P4P periods, respectively. Similarly, lack of prophylaxis when indicated decreased from 6.1% to 3.2% to 3.1% during the BASE, DASH, and subsequent P4P periods, respectively.

Figure 3

The average compliance of the 4 non‐hospitalist general medicine service teams was initially higher than that of the hospitalist service during the CPOE‐based VTE order set (90%) and DASH (92%) periods, but subsequently plateaued and was exceeded by the hospitalist service during the combined P4P (92%) period (Figure 3). However, there was no statistically significant difference between the general medicine service teams and hospitalist service during the DASH (P=0.15) and subsequent P4P (P=0.76) periods.

We also analyzed the rate of VTE prophylaxis compliance improvement (slope) with cut points at each time period transition (Figure 3). Risk‐appropriate VTE prophylaxis during the BASE period did not exhibit significant improvement as indicated by the slope (P=0.23) (Figure 3). In contrast, during the DASH period, VTE prophylaxis compliance significantly increased by 1.58% per month (95% CI: 0.41‐2.76; P=0.01). The addition of the P4P program, however, did not further significantly increase the rate of compliance (P=0.78).

A subgroup analysis restricted to the 19 providers present during all 3 periods was performed to assess for potential confounding from physician turnover. The percent compliance increased in a similar fashion: BASE period of CPOE‐based VTE order set, 85% (95% CI: 8386); DASH, 90% (95% CI: 8893); and P4P, 94% (95% CI: 9296).

DISCUSSION

A key component of healthcare reform has been value‐based purchasing, which emphasizes extrinsic motivation through the transparency of performance metrics and use of payment incentives to reward quality. Our study evaluates the impact of both extrinsic (payments) and intrinsic (professionalism and peer norms) motivation. It specifically attributed an individual performance metric, VTE prophylaxis, to an attending physician, provided both individualized and group feedback using an electronic dashboard, and incorporated a pay‐for‐performance program. Prescription of risk‐appropriate VTE prophylaxis significantly increased with the implementation of the dashboard and subsequent pay‐for performance program. The fastest rate of improvement occurred after the addition of the dashboard. Sensitivity analyses for provider turnover and comparisons to the general medicine services showed our results to be independent of a general trend of improvement, both at the provider and institutional levels.

Our prior studies demonstrated that order sets significantly improve performance, from a baseline compliance of risk‐appropriate VTE prophylaxis of 66% to 84%.[13, 15, 25] In the current study, compliance was relatively flat during the BASE period, which included these order sets. The greatest rate of continued improvement in compliance occurred during the DASH period, emphasizing both the importance of provider feedback and receptivity and adaptability in the prescribing behavior of hospitalists. Because the goal of a high‐reliability health system is for 100% of patients to receive recommended therapy, multiple approaches are necessary for success.

Nationally, benchmarks for performance measures continue to be raised, with the highest performers achieving above 95%.[26] Additional interventions, such as dashboards and pay‐for‐performance programs, supplement CPOE systems to achieve high reliability. In our study, the compliance rate during the baseline period, which included a CPOE‐based, clinical support‐enabled VTE order set, was 86%. Initially the compliance of the general medicine teams with residents exceeded that of the hospitalist attending teams, which may reflect a greater willingness of resident teams to comply with order sets and automated recommendations. This emphasizes the importance of continuous individual feedback and provider education at the attending physician level to enhance both guideline compliance and decrease provider care variation. Ultimately, with the addition of the dashboard and subsequent pay‐for‐performance program, compliance was increased to 90% and 94%, respectively. Although the major mechanism used by policymakers to improve quality of care is extrinsic motivation, this study demonstrates that intrinsic motivation through peer norms can enhance extrinsic efforts and may be more influential. Both of these programs, dashboards and pay‐for‐performance, may ultimately assist institutions in changing provider behavior and achieving these harder‐to‐achieve higher benchmarks.

We recognize that there are several limitations to our study. First, this is a single‐site program limited to an attending‐physician‐only service. There was strong data support and a defined CPOE algorithm for this initiative. Multi‐site studies will need to overcome the additional challenges of varying service structures and electronic medical record and provider order entry systems. Second, it is difficult to show actual changes in VTE events over time with appropriate prophylaxis. Although VTE prophylaxis is recommended for patients with VTE risk factors, there are conflicting findings about whether prophylaxis prevents VTE events in lower‐risk patients, and current studies suggest that most patients with VTE events are severely ill and develop VTE despite receiving prophylaxis.[27, 28, 29] Our study was underpowered to detect these potential differences in VTE rates, and although the algorithm has been shown to not increase bleeding rates, we did not measure bleeding rates during this study.[12, 15] Our institutional experience suggests that the majority of VTE events occur despite appropriate prophylaxis.[30] Also, VTE prophylaxis may be ordered, but intervening events, such as procedures and changes in risk status or patient refusal, may prevent patients from receiving appropriate prophylaxis.[31, 32] Similarly, hospitals with higher quality scores have higher VTE prophylaxis rates but worse risk‐adjusted VTE rates, which may result from increased surveillance for VTE, suggesting surveillance bias limits the usefulness of the VTE quality measure.[33, 34] Nevertheless, VTE prophylaxis remains a publicly reported Core Measure tied to financial incentives.[4, 5] Third, there may be an unmeasured factor specific to the hospitalist program, which could potentially account for an overall improvement in quality of care. Although the rate of increase in appropriate prophylaxis was not statistically significant during the baseline period, there did appear to be some improvement in prophylaxis toward the end of the period. However, there were no other VTE‐related provider feedback programs being simultaneously pursued during this study. VTE prophylaxis for the non‐hospitalist services showed a relatively stable, non‐increasing compliance rate for the general medical services. Although it was possible for successful residents to age into the hospitalist service, thereby improving rates of prophylaxis based on changes in group makeup, our subgroup analysis of the providers present throughout all phases of the study showed our results to be robust. Similarly, there may have been a cross‐contamination effect of hospitalist faculty who attended on both hospitalist and non‐hospitalist general medicine service teams. This, however, would attenuate any impact of the programs, and thus the effects may in fact be greater than reported. Fourth, establishment of both the dashboard and pay‐for‐performance program required significant institutional and program leadership and resources. To be successful, the dashboard must be in the provider's workflow, transparent, minimize reporter burden, use existing systems, and be actively fed back to providers, ideally those directly entering orders. Our greatest rate of improvement occurred during the feedback‐only phase of this study, emphasizing the importance of physician feedback, provider‐level accountability, and engagement. We suspect that the relatively modest pay‐for‐performance incentive served mainly as a means of engaging providers in self‐monitoring, rather than as a means to change behavior through true incentivization. Although we did not track individual physician views of the dashboard, we reinforced trends, deviations, and expectations at regularly scheduled meetings and provided feedback and patient‐level data to individual providers. Fifth, the design of the pay‐for‐performance program may have also influenced its effectiveness. These types of programs may be more effective when they provide frequent visible, small payments rather than one large payment, and when the payment is framed as a loss rather than a gain.[35] Finally, physician champions and consistent feedback through departmental meetings or visual displays may be required for program success. The initial resources to create the dashboard, continued maintenance and monitoring of performance, and payment of financial incentives all require institutional commitment. A partnership of physicians, program leaders, and institutional administrators is necessary for both initial and continued success.

To achieve performance goals and benchmarks, multiple strategies that combine extrinsic and intrinsic motivation are necessary. As shown by our study, the use of a dashboard and pay‐for‐performance can be tailored to an institution's goals, in line with national standards. The specific goal (risk‐appropriate VTE prophylaxis) and benchmarks (80%, 85%, 90%, 95%) can be individualized to a particular institution. For example, if readmission rates are above target, readmissions could be added as a dashboard metric. The specific benchmark would be determined by historical trends and administrative targets. Similarly, the overall financial incentives could be adjusted based on the financial resources available. Other process measures, such as influenza vaccination screening and administration, could also be targeted. For all of these objectives, continued provider feedback and engagement are critical for progressive success, especially to decrease variability in care at the attending physician level. Incorporating the value‐based purchasing philosophy from the Affordable Care Act, our study suggests that the combination of standardized order sets, real‐time dashboards, and physician‐level incentives may assist hospitals in achieving quality and safety benchmarks, especially at higher targets.

The 2012 American College of Chest Physicians (ACCP) guidelines on antithrombotic and thrombolytic therapy conducted a systematic review focusing on patient values and preferences regarding antithrombotic therapy, including thromboprophylaxis.[1] They found that patient values and preferences are highly variable and should be considered when developing future clinical practice guidelines. Notably, there were no studies evaluating patient preferences for venous thromboembolism (VTE) prophylaxis, which is prescribed for the vast majority of hospitalized patients.

Historically, interventions to prevent VTE have focused on increasing prescriptions of prophylaxis. At the Johns Hopkins Hospital, we implemented a mandatory clinical decision support tool in our computerized provider order entry system.[2] Following implementation of this tool, prescription of risk‐appropriate VTE prophylaxis dramatically increased for both medical and surgical patients.[3, 4, 5] These efforts were made with the implicit and incorrect assumption that prescribed medication doses will always be administered to patients, when in fact patient refusal is a leading cause of nonadministration. Studies of VTE prophylaxis administration have reported that 10% to 12% of doses are not administered to patients.[6] Alarmingly, it has been reported that among medically ill patients, between 10% and 30% of doses are not administered, with patient refusal as the most frequently documented reason.

The purpose of this study was to assess patient preferences regarding pharmacological VTE prophylaxis.

METHODS

RESULTS

DISCUSSION

Using a mixed‐methods approach, we report the first survey evaluating patient preferences regarding pharmacologic VTE prophylaxis. We found that a majority of patients preferred an oral route of administration. Nevertheless, a substantial number of patients favored a subcutaneous route of administration believing it to be associated with a faster onset of action. Of interest, patients favoring subcutaneous injections were significantly less likely to refuse doses of ordered VTE prophylaxis. Given that all patients were prescribed a subcutaneous form of VTE prophylaxis, matching patient preference to VTE prophylaxis prescription could potentially increase adherence and reduce patient refusal of ordered prophylaxis. Considering the large number of patients who preferred an oral route of administration, the availability of an oral formulation may potentially result in improved adherence to inpatient VTE prophylaxis.

Our findings have significant implications for healthcare providers, and for patient safety and quality‐improvement researchers. VTE prophylaxis is an important patient‐safety practice, particularly for medically ill patients, which is believed to be underprescribed.[7] Recent studies have demonstrated that a significant number of doses of VTE prophylaxis are not administered, primarily due to patient refusal.[6] Our data indicate that tailoring the route of prophylaxis administration to patient preference may represent a feasible strategy to improve VTE prophylaxis administration rates. Recently, several target‐specific oral anticoagulants (TSOACs) have been approved for a variety of clinical indications, and all have been investigated for VTE prophylaxis.[7, 8, 9, 10, 11, 12, 13, 14, 15] However, no agent is currently US Food & Drug Administration (FDA) approved for primary prevention of VTE, although apixaban and rivaroxaban are FDA approved for VTE prevention in joint replacement.[13, 14] Although in some instances these TSOACs were noted to demonstrate only equivalent efficacy to standard subcutaneous forms of VTE prophylaxis, our data suggest that perhaps in some patients, use of these agents may result in better outcomes due to improved adherence to therapy due to a preferred oral route of administration. We think this hypothesis warrants further investigation.

Our study also underscores the importance of considering patient preferences when caring for patients as emphasized by the 2012 ACCP guidelines.[1] Our results indicate that consideration of patient preferences may lead to better patient care and better outcomes. Interestingly, there were no differences in preference based on education level or the type of service to which the patient was admitted. Clarification of uninformed opinions regarding the rationale for preference may also lead to more informed decisions by patients.

This study has a number of limitations. We only included patients on the internal medicine and general surgical services. It is possible that patients on other specialty services may have different opinions regarding prophylaxis that were not captured in our sample. Similarly, our sample size was limited, and approximately 15% of potential subjects did not participate. We do believe that our population is reflective of our institution based upon our previously published evaluation of multiple hospital units and the inclusion of low‐ and high‐performing units on both the medical and surgical services. Nevertheless, we believe that much more investigation of patient perspectives on VTE prophylaxis needs to be done to inform decision making, including the impact of patient preferences on VTE‐related outcomes. Additionally, we did not evaluate potential predictors of preference including admission diagnosis and duration of hospital length of stay.

In conclusion, we conducted a mixed‐methods analysis of patient preferences regarding pharmacologic VTE prophylaxis. Matching patient preference to ordered VTE prophylaxis may increase adherence to ordered prophylaxis. In this era of increasingly patient‐centered healthcare and expanding options for VTE prophylaxis, we believe information on patient preferences will be helpful to tailoring options for prevention and treatment.

The 2012 American College of Chest Physicians (ACCP) guidelines on antithrombotic and thrombolytic therapy conducted a systematic review focusing on patient values and preferences regarding antithrombotic therapy, including thromboprophylaxis.[1] They found that patient values and preferences are highly variable and should be considered when developing future clinical practice guidelines. Notably, there were no studies evaluating patient preferences for venous thromboembolism (VTE) prophylaxis, which is prescribed for the vast majority of hospitalized patients.

Historically, interventions to prevent VTE have focused on increasing prescriptions of prophylaxis. At the Johns Hopkins Hospital, we implemented a mandatory clinical decision support tool in our computerized provider order entry system.[2] Following implementation of this tool, prescription of risk‐appropriate VTE prophylaxis dramatically increased for both medical and surgical patients.[3, 4, 5] These efforts were made with the implicit and incorrect assumption that prescribed medication doses will always be administered to patients, when in fact patient refusal is a leading cause of nonadministration. Studies of VTE prophylaxis administration have reported that 10% to 12% of doses are not administered to patients.[6] Alarmingly, it has been reported that among medically ill patients, between 10% and 30% of doses are not administered, with patient refusal as the most frequently documented reason.

The purpose of this study was to assess patient preferences regarding pharmacological VTE prophylaxis.

METHODS

RESULTS

DISCUSSION

Using a mixed‐methods approach, we report the first survey evaluating patient preferences regarding pharmacologic VTE prophylaxis. We found that a majority of patients preferred an oral route of administration. Nevertheless, a substantial number of patients favored a subcutaneous route of administration believing it to be associated with a faster onset of action. Of interest, patients favoring subcutaneous injections were significantly less likely to refuse doses of ordered VTE prophylaxis. Given that all patients were prescribed a subcutaneous form of VTE prophylaxis, matching patient preference to VTE prophylaxis prescription could potentially increase adherence and reduce patient refusal of ordered prophylaxis. Considering the large number of patients who preferred an oral route of administration, the availability of an oral formulation may potentially result in improved adherence to inpatient VTE prophylaxis.

Our findings have significant implications for healthcare providers, and for patient safety and quality‐improvement researchers. VTE prophylaxis is an important patient‐safety practice, particularly for medically ill patients, which is believed to be underprescribed.[7] Recent studies have demonstrated that a significant number of doses of VTE prophylaxis are not administered, primarily due to patient refusal.[6] Our data indicate that tailoring the route of prophylaxis administration to patient preference may represent a feasible strategy to improve VTE prophylaxis administration rates. Recently, several target‐specific oral anticoagulants (TSOACs) have been approved for a variety of clinical indications, and all have been investigated for VTE prophylaxis.[7, 8, 9, 10, 11, 12, 13, 14, 15] However, no agent is currently US Food & Drug Administration (FDA) approved for primary prevention of VTE, although apixaban and rivaroxaban are FDA approved for VTE prevention in joint replacement.[13, 14] Although in some instances these TSOACs were noted to demonstrate only equivalent efficacy to standard subcutaneous forms of VTE prophylaxis, our data suggest that perhaps in some patients, use of these agents may result in better outcomes due to improved adherence to therapy due to a preferred oral route of administration. We think this hypothesis warrants further investigation.

Our study also underscores the importance of considering patient preferences when caring for patients as emphasized by the 2012 ACCP guidelines.[1] Our results indicate that consideration of patient preferences may lead to better patient care and better outcomes. Interestingly, there were no differences in preference based on education level or the type of service to which the patient was admitted. Clarification of uninformed opinions regarding the rationale for preference may also lead to more informed decisions by patients.

This study has a number of limitations. We only included patients on the internal medicine and general surgical services. It is possible that patients on other specialty services may have different opinions regarding prophylaxis that were not captured in our sample. Similarly, our sample size was limited, and approximately 15% of potential subjects did not participate. We do believe that our population is reflective of our institution based upon our previously published evaluation of multiple hospital units and the inclusion of low‐ and high‐performing units on both the medical and surgical services. Nevertheless, we believe that much more investigation of patient perspectives on VTE prophylaxis needs to be done to inform decision making, including the impact of patient preferences on VTE‐related outcomes. Additionally, we did not evaluate potential predictors of preference including admission diagnosis and duration of hospital length of stay.

In conclusion, we conducted a mixed‐methods analysis of patient preferences regarding pharmacologic VTE prophylaxis. Matching patient preference to ordered VTE prophylaxis may increase adherence to ordered prophylaxis. In this era of increasingly patient‐centered healthcare and expanding options for VTE prophylaxis, we believe information on patient preferences will be helpful to tailoring options for prevention and treatment.

The 2012 American College of Chest Physicians (ACCP) guidelines on antithrombotic and thrombolytic therapy conducted a systematic review focusing on patient values and preferences regarding antithrombotic therapy, including thromboprophylaxis.[1] They found that patient values and preferences are highly variable and should be considered when developing future clinical practice guidelines. Notably, there were no studies evaluating patient preferences for venous thromboembolism (VTE) prophylaxis, which is prescribed for the vast majority of hospitalized patients.

Historically, interventions to prevent VTE have focused on increasing prescriptions of prophylaxis. At the Johns Hopkins Hospital, we implemented a mandatory clinical decision support tool in our computerized provider order entry system.[2] Following implementation of this tool, prescription of risk‐appropriate VTE prophylaxis dramatically increased for both medical and surgical patients.[3, 4, 5] These efforts were made with the implicit and incorrect assumption that prescribed medication doses will always be administered to patients, when in fact patient refusal is a leading cause of nonadministration. Studies of VTE prophylaxis administration have reported that 10% to 12% of doses are not administered to patients.[6] Alarmingly, it has been reported that among medically ill patients, between 10% and 30% of doses are not administered, with patient refusal as the most frequently documented reason.

The purpose of this study was to assess patient preferences regarding pharmacological VTE prophylaxis.

METHODS

RESULTS

DISCUSSION

Using a mixed‐methods approach, we report the first survey evaluating patient preferences regarding pharmacologic VTE prophylaxis. We found that a majority of patients preferred an oral route of administration. Nevertheless, a substantial number of patients favored a subcutaneous route of administration believing it to be associated with a faster onset of action. Of interest, patients favoring subcutaneous injections were significantly less likely to refuse doses of ordered VTE prophylaxis. Given that all patients were prescribed a subcutaneous form of VTE prophylaxis, matching patient preference to VTE prophylaxis prescription could potentially increase adherence and reduce patient refusal of ordered prophylaxis. Considering the large number of patients who preferred an oral route of administration, the availability of an oral formulation may potentially result in improved adherence to inpatient VTE prophylaxis.

Our findings have significant implications for healthcare providers, and for patient safety and quality‐improvement researchers. VTE prophylaxis is an important patient‐safety practice, particularly for medically ill patients, which is believed to be underprescribed.[7] Recent studies have demonstrated that a significant number of doses of VTE prophylaxis are not administered, primarily due to patient refusal.[6] Our data indicate that tailoring the route of prophylaxis administration to patient preference may represent a feasible strategy to improve VTE prophylaxis administration rates. Recently, several target‐specific oral anticoagulants (TSOACs) have been approved for a variety of clinical indications, and all have been investigated for VTE prophylaxis.[7, 8, 9, 10, 11, 12, 13, 14, 15] However, no agent is currently US Food & Drug Administration (FDA) approved for primary prevention of VTE, although apixaban and rivaroxaban are FDA approved for VTE prevention in joint replacement.[13, 14] Although in some instances these TSOACs were noted to demonstrate only equivalent efficacy to standard subcutaneous forms of VTE prophylaxis, our data suggest that perhaps in some patients, use of these agents may result in better outcomes due to improved adherence to therapy due to a preferred oral route of administration. We think this hypothesis warrants further investigation.

Our study also underscores the importance of considering patient preferences when caring for patients as emphasized by the 2012 ACCP guidelines.[1] Our results indicate that consideration of patient preferences may lead to better patient care and better outcomes. Interestingly, there were no differences in preference based on education level or the type of service to which the patient was admitted. Clarification of uninformed opinions regarding the rationale for preference may also lead to more informed decisions by patients.

This study has a number of limitations. We only included patients on the internal medicine and general surgical services. It is possible that patients on other specialty services may have different opinions regarding prophylaxis that were not captured in our sample. Similarly, our sample size was limited, and approximately 15% of potential subjects did not participate. We do believe that our population is reflective of our institution based upon our previously published evaluation of multiple hospital units and the inclusion of low‐ and high‐performing units on both the medical and surgical services. Nevertheless, we believe that much more investigation of patient perspectives on VTE prophylaxis needs to be done to inform decision making, including the impact of patient preferences on VTE‐related outcomes. Additionally, we did not evaluate potential predictors of preference including admission diagnosis and duration of hospital length of stay.

In conclusion, we conducted a mixed‐methods analysis of patient preferences regarding pharmacologic VTE prophylaxis. Matching patient preference to ordered VTE prophylaxis may increase adherence to ordered prophylaxis. In this era of increasingly patient‐centered healthcare and expanding options for VTE prophylaxis, we believe information on patient preferences will be helpful to tailoring options for prevention and treatment.

Patients with human immunodeficiency virus (HIV) are at a 2‐ to 10‐fold greater risk for venous thromboembolism (VTE) compared with the general population.[1] Although antiphospholipid antibodies and protein S deficiency have often been cited as reasons for the thrombophilia associated with HIV, previous studies have also documented an increased risk of VTE with declining CD4+ cell count.[2, 3, 4, 5, 6, 7, 8] Worsening immune function places HIV patients at increased risk for opportunistic and nonopportunistic infections and malignancies, all independently associated with an increased risk of VTE.[5, 9, 10, 11, 12] Although increasing use of antiretroviral therapy has greatly decreased these sequelae, these complications of HIV infection are associated with an increased frequency of hospitalization.[13, 14, 15, 16] HIV infection and associated inflammation has been implicated in cardiovascular conditions such as cardiomyopathy, pulmonary hypertension, and myocardial infarction.[17, 18] Additionally, progression of HIV infection appears to influence T‐cell activation and differentiation in a manner that leads to early immunosenescence in infected individuals.[19, 20]

VTE prophylaxis is effective.[21] Virtually all efforts to decrease VTE have been focused on improving the prescription of prophylaxis with varying degrees of success.[22] These interventions have been employed with the tacit assumption that medication prescribed for inpatients will always be administered. However, at our institution, recent research has demonstrated that a significant proportion of prescribed thromboprophylaxis doses are not administered to hospitalized patients.[23] Refusal by the patient or a family member was the most commonly documented reason for dose nonadministration. In addition, the rate of thromboprophylaxis nonadministration varied greatly between nursing units with distinct patient populations. We hypothesized that nonadministration of VTE prophylaxis may be more common in patients with HIV, and this phenomenon may contribute to their increased risk for VTE.

The purpose of this study was to determine if the proportion of nonadministered thromboprophylaxis is greater among hospitalized patients with HIV and to characterize documented reasons for dose nonadministration.

METHODS

This study was conducted at The Johns Hopkins Hospital (JHH), a large, urban, academic medical center in Baltimore, Maryland. This single‐center retrospective cohort study utilized an existing dataset containing dose administration data extracted from an electronic medication administration record (eMAR). This dataset included information for all prescribed doses of thromboprophylaxis (heparin 5000 U subcutaneously every 8 or 12 hours, heparin 7500 U subcutaneously every 12 hours, enoxaparin 30 mg subcutaneously every 12 hours, or enoxaparin 40 mg subcutaneously daily) for patients hospitalized on medicine units at JHH from November 2007 to December 2008. This time period follows the implementation of an electronic order set for VTE prophylaxis.[24, 25] Data available for each dose included drug name, dose, frequency, patient demographics, and whether or not the dose was administered. Each dose not administered included a reason for nonadministration, which was chosen from a dropdown menu of responses on the eMAR by the nurse at the time the dose was due. A separate electronic report was obtained from an internal administrative database, which identified all patients within the dose administration dataset who had the International Classification of Diseases, 9th Revision code 042 (HIV diagnosis). A report identifying patient history numbers with matching diagnostic code for HIV was appended to the dose administration dataset using a relational database (Microsoft Access; Microsoft Corp., Redmond, WA) prior to analysis. The dose administration data were obtained previously for a separate analysis.[23] Approval for this study was granted from the institutional review board of Johns Hopkins Medicine.

Our analytic plan included comparisons between patients with and without HIV on a dose, patient, and unit level. As JHH operates a nursing unit dedicated to the inpatient care of patients with HIV, we included analyses of dose characteristics between this unit and other medicine units. It should be noted that patients without a diagnosis of HIV are sometimes cared for on this unit. Therefore, the electronic medical record for each patient without the diagnosis code for HIV hospitalized on this unit was reviewed to determine HIV status. An analysis was performed comparing visit identification numbers with diagnosis codes to identify potential seroconversions during the study period. Although we planned to compare nonadministration and documented refusal of doses on the unit level, a lack of patients with HIV on a number of units limited our ability to perform these analyses.

RESULTS

During the 8‐month study period, 42,870 doses of thromboprophylaxis were prescribed during 4947 patient admissions to 13 individual medicine units. Overall, the diagnosis code for HIV was present in 12% of patient visits. The proportion of nonadministered doses per unit ranged from 6% to 27%, whereas the number of doses prescribed per unit ranged from 34 to 7301.

Patient characteristics were described on the visit level (Table 1). Patients with HIV were significantly younger, more often male and black, and had a longer length of stay compared with patients without HIV. Patients hospitalized on the HIV care unit had similar characteristics to the overall population of patients with HIV. It should be noted that not all patients cared for on this unit had a diagnosis of HIV, as patients from other medicine services are sometimes cared for in this location.

Overall, 17% of prescribed prophylaxis doses were not administered. A greater proportion of prescribed doses were not administered to patients with HIV compared with patients without HIV (23.5% vs 16.1%, OR: 1.59, 95% CI: 1.49‐1.70, P<0.001) (Table 2). Using a GEE and univariate regression, HIV diagnosis was associated with nonadministration of doses (OR: 1.37, 95% CI: 1.17‐1.60, P<0.001) (Table 3). Race, age, length of stay, and drug (heparin vs enoxaparin) were each associated with nonadministration. There was no significant association between nonadministration and sex, marital status, or payor. When stratified by nursing unit, there was substantial variation in the proportion of nonadministered doses between units. Within each unit, the proportion of doses not administered varied when stratified by HIV status. For example, on unit A, the proportion of doses not administered was greater for patients with HIV compared with patients without HIV (33.3% vs 12.9%, OR: 3.38, 95% CI: 2.61 to 4.37, P<0.001) (Figure 1). However, on unit K, the proportion of doses not administered to patients with HIV was 2‐fold less than in patients without HIV (7.2% vs 14.3%, OR: 0.47, 95% CI: 0.30‐0.74, P<0.001). Unit‐level analysis was not possible in regression models due to drastic imbalance in the prevalence of HIV across units. When comparing doses prescribed in the HIV care unit to all other medicine units, the proportion not administered (23.9% vs 16.3%, OR: 1.61, 95% CI: 1.49‐1.73, P<0.001) closely resembled the values seen when comparing patients with and without HIV hospital wide (23.5% vs 16.1%). However, when doses on the HIV care unit were stratified by HIV status, the doses not administered were 2‐fold greater, as a proportion, for patients with HIV compared with those without HIV (26.4% vs 13.1%, OR: 2.39, 95% CI: 1.93‐2.96, P<0.001).

Figure 1

The results of the multivariate regression analyses with GEE are displayed in Table 4. HIV diagnosis, non‐African American race, and heparin (as compared with enoxaparin) were associated with increased likelihood of nonadministration. Increasing age and increasing length of stay were associated with decreased likelihood of nonadministration by a small but significant amount.

The most commonly documented reason for nonadministration was refusal by the patient or family member (66% of all doses not administered). The second most common reason, patient condition not appropriate, accounted for an additional 10% of doses. Across all nursing units, the proportion of prescribed doses that were documented as refused was significantly greater for patients with HIV compared with patients without HIV (16.5% vs 10.6%, OR: 1.66, 95% CI: 1.54‐1.80, P<0.0001) (Table 2). Using the GEE and multivariate regression, HIV diagnosis, non‐African American race, and heparin were associated with increased risk of documented dose refusal. Age and length of stay were inversely related to the likelihood of documented dose refusal. When all administered doses were excluded from the analysis, the association between these variables and documented dose refusal were not as strong. Age and length of stay remained significantly inversely related; however, the other factors were no longer significantly positively associated with documented dose refusal.

Within the HIV care unit, the proportion of prescribed doses documented as refused was greater for patients with HIV compared with patients without HIV (18.1% vs 6.8%, OR: 3.01, 95% CI: 2.28‐3.99, P<0.0001). For all other medicine units, the proportion of nonadministered doses documented as refused was also greater for patients with HIV compared with patients without HIV (13.7% vs 10.7%, OR: 1.32, 95% CI: 1.16‐1.51, P<0.0001).

DISCUSSION

We have identified that nonadministration of thromboprophylaxis was more common among patients with HIV at our institution. Substantial variation in the proportion of doses not administered existed on the nursing unit level, as well as within each unit when stratified by HIV status. This disparity in dose administration was observed on the HIV care unit as well, as the proportion not administered was about 2‐fold greater for patients with HIV compared with those without HIV. Documented dose refusal appeared to account for the majority of nonadministered doses in our cohort. Our analysis also demonstrated that HIV diagnosis is significantly associated with both dose nonadministration and documented dose refusal at our institution.

Medication refusal is a well‐recognized phenomenon among hospitalized patients. A recent study of medication administration in hospitalized patients in the United Kingdom noted that refusal accounted for about 45% of omitted doses.[26] Fanikos et al. also found that documented refusal of doses contributed significantly to the overall number of VTE prophylaxis doses not administered to patients.[27] In our study, the proportion of nonadministered doses documented as refused by the patient or family member was significantly greater in patients with HIV than in patients without HIV across all units. Interestingly, the difference was greater on the HIV care unit when doses were stratified by HIV status. This observation leads us to hypothesize that specific hospital care environments may influence dose nonadministration and refusal rates among our patient population.

Based on regression analyses, increasing age and length of stay were associated with a decreased likelihood of any particular dose not being administered and with any particular dose being documented as refused. It is important to note that our GEE did not take into account date or time of each dose, and therefore we cannot make conclusions as to the likelihood of dose nonadministration or refusal of doses in relation to each other on a time scale. One cannot assume that a dose due later in a hospital course was more or less likely to be given than a dose due on the first hospital day. Although we did not expect these findings, one can hypothesize that patients who are older or have longer stays may be perceived to have more severe illness, and therefore greater need for prophylaxis, from nursing staff and others involved in their care. The associations were small but significant and warrant future investigation.

To our knowledge, this is the first investigation comparing the proportion of nonadministered doses of thromboprophylaxis between patients with and without HIV. Our data show that nonadministered doses and refused doses of thromboprophylaxis are more frequent among patients with HIV. In addition, we noted that nonadministration was more common on the dedicated HIV care unit compared with other units. We cannot currently offer a clear explanation for the disparity observed between units, and more specifically, within the HIV care unit. However, it is possible that a unique culture of care and provider‐specific factors may contribute.

Our study was limited by a number of factors. Seroconversion among patients during the study period was possible; however, our analysis revealed only 2 instances among nearly 4000 unique patients. A more significant limitation was the level of analysis allowed by the dataset. We examined dose characteristics on a dose and unit level, but the ability to analyze doses based on the prescriber and nurse level may have provided valuable insight into the specific reasons behind the observations presented here. Additionally, the specific unit assigned to a given dose in our dataset represented the discharge location for the corresponding patient, making it possible that some amount of nonadministered doses may be attributed to the incorrect unit. However, we do not believe that unit‐to‐unit transfers would be frequent enough to influence the overall results. In addition, we did not link nonadministration of thromboprophylaxis with VTE events, as these data were not present in the current dataset. Although this is a limitation of the current study, we believe that the notion that missed doses of thromboprophylaxis place patients at higher risk for VTE is plausible, as the efficacy of thromboprophylaxis is well established.[28, 29, 30] It is important to note that the reason for nonadministration selected by the nurse on the eMAR may not always represent the only reason or even the true reason for dose nonadministration. It is possible that dose refusal may be over‐represented in our sample, in part due to inaccurate documentation. Recent investigations at JHH have identified varying attitudes on the part of the patient and the nurse regarding thromboprophylaxis. A questionnaire and interview of patients showed a large knowledge gap regarding thromboprophylaxis, with many individuals unable to explain its role or significance in their medical care.[31] A common theme was also observed in a survey of nurses regarding VTE prophylaxis: doses were sometimes considered optional for reasons such as ambulation status, perceived severity of illness, or reason for hospitalization. Some nurses also reported that after an initial refused dose, they may continue to document subsequent doses as refused, sometimes without offering the dose to the patient.[32] As variation in practice was observed between individual nurses, it is also likely that the culture of care may vary between units, influencing thromboprophylaxis nonadministration rates as well as documentation of doses as refused. The dose‐level data used for the GEE analyses did not include date and time of administration, which limited the ability of the GEE to more completely account for autocorrelation.

To further investigate the findings of this and related studies, we intend to more closely analyze data at multiple levels with the goal of identifying an appropriate and feasible target for intervention. Additionally, further investigation should be performed with the goal of determining the relationship between decreased exposure to thromboprophylaxis and VTE. However, as patients with HIV appear to be at increased risk of VTE, ensuring that thromboprophylaxis is delivered appropriately and consistently should be an important goal for all who provide care to this population.

Patients with human immunodeficiency virus (HIV) are at a 2‐ to 10‐fold greater risk for venous thromboembolism (VTE) compared with the general population.[1] Although antiphospholipid antibodies and protein S deficiency have often been cited as reasons for the thrombophilia associated with HIV, previous studies have also documented an increased risk of VTE with declining CD4+ cell count.[2, 3, 4, 5, 6, 7, 8] Worsening immune function places HIV patients at increased risk for opportunistic and nonopportunistic infections and malignancies, all independently associated with an increased risk of VTE.[5, 9, 10, 11, 12] Although increasing use of antiretroviral therapy has greatly decreased these sequelae, these complications of HIV infection are associated with an increased frequency of hospitalization.[13, 14, 15, 16] HIV infection and associated inflammation has been implicated in cardiovascular conditions such as cardiomyopathy, pulmonary hypertension, and myocardial infarction.[17, 18] Additionally, progression of HIV infection appears to influence T‐cell activation and differentiation in a manner that leads to early immunosenescence in infected individuals.[19, 20]

VTE prophylaxis is effective.[21] Virtually all efforts to decrease VTE have been focused on improving the prescription of prophylaxis with varying degrees of success.[22] These interventions have been employed with the tacit assumption that medication prescribed for inpatients will always be administered. However, at our institution, recent research has demonstrated that a significant proportion of prescribed thromboprophylaxis doses are not administered to hospitalized patients.[23] Refusal by the patient or a family member was the most commonly documented reason for dose nonadministration. In addition, the rate of thromboprophylaxis nonadministration varied greatly between nursing units with distinct patient populations. We hypothesized that nonadministration of VTE prophylaxis may be more common in patients with HIV, and this phenomenon may contribute to their increased risk for VTE.

The purpose of this study was to determine if the proportion of nonadministered thromboprophylaxis is greater among hospitalized patients with HIV and to characterize documented reasons for dose nonadministration.

METHODS

This study was conducted at The Johns Hopkins Hospital (JHH), a large, urban, academic medical center in Baltimore, Maryland. This single‐center retrospective cohort study utilized an existing dataset containing dose administration data extracted from an electronic medication administration record (eMAR). This dataset included information for all prescribed doses of thromboprophylaxis (heparin 5000 U subcutaneously every 8 or 12 hours, heparin 7500 U subcutaneously every 12 hours, enoxaparin 30 mg subcutaneously every 12 hours, or enoxaparin 40 mg subcutaneously daily) for patients hospitalized on medicine units at JHH from November 2007 to December 2008. This time period follows the implementation of an electronic order set for VTE prophylaxis.[24, 25] Data available for each dose included drug name, dose, frequency, patient demographics, and whether or not the dose was administered. Each dose not administered included a reason for nonadministration, which was chosen from a dropdown menu of responses on the eMAR by the nurse at the time the dose was due. A separate electronic report was obtained from an internal administrative database, which identified all patients within the dose administration dataset who had the International Classification of Diseases, 9th Revision code 042 (HIV diagnosis). A report identifying patient history numbers with matching diagnostic code for HIV was appended to the dose administration dataset using a relational database (Microsoft Access; Microsoft Corp., Redmond, WA) prior to analysis. The dose administration data were obtained previously for a separate analysis.[23] Approval for this study was granted from the institutional review board of Johns Hopkins Medicine.

Our analytic plan included comparisons between patients with and without HIV on a dose, patient, and unit level. As JHH operates a nursing unit dedicated to the inpatient care of patients with HIV, we included analyses of dose characteristics between this unit and other medicine units. It should be noted that patients without a diagnosis of HIV are sometimes cared for on this unit. Therefore, the electronic medical record for each patient without the diagnosis code for HIV hospitalized on this unit was reviewed to determine HIV status. An analysis was performed comparing visit identification numbers with diagnosis codes to identify potential seroconversions during the study period. Although we planned to compare nonadministration and documented refusal of doses on the unit level, a lack of patients with HIV on a number of units limited our ability to perform these analyses.

RESULTS

During the 8‐month study period, 42,870 doses of thromboprophylaxis were prescribed during 4947 patient admissions to 13 individual medicine units. Overall, the diagnosis code for HIV was present in 12% of patient visits. The proportion of nonadministered doses per unit ranged from 6% to 27%, whereas the number of doses prescribed per unit ranged from 34 to 7301.

Patient characteristics were described on the visit level (Table 1). Patients with HIV were significantly younger, more often male and black, and had a longer length of stay compared with patients without HIV. Patients hospitalized on the HIV care unit had similar characteristics to the overall population of patients with HIV. It should be noted that not all patients cared for on this unit had a diagnosis of HIV, as patients from other medicine services are sometimes cared for in this location.

Overall, 17% of prescribed prophylaxis doses were not administered. A greater proportion of prescribed doses were not administered to patients with HIV compared with patients without HIV (23.5% vs 16.1%, OR: 1.59, 95% CI: 1.49‐1.70, P<0.001) (Table 2). Using a GEE and univariate regression, HIV diagnosis was associated with nonadministration of doses (OR: 1.37, 95% CI: 1.17‐1.60, P<0.001) (Table 3). Race, age, length of stay, and drug (heparin vs enoxaparin) were each associated with nonadministration. There was no significant association between nonadministration and sex, marital status, or payor. When stratified by nursing unit, there was substantial variation in the proportion of nonadministered doses between units. Within each unit, the proportion of doses not administered varied when stratified by HIV status. For example, on unit A, the proportion of doses not administered was greater for patients with HIV compared with patients without HIV (33.3% vs 12.9%, OR: 3.38, 95% CI: 2.61 to 4.37, P<0.001) (Figure 1). However, on unit K, the proportion of doses not administered to patients with HIV was 2‐fold less than in patients without HIV (7.2% vs 14.3%, OR: 0.47, 95% CI: 0.30‐0.74, P<0.001). Unit‐level analysis was not possible in regression models due to drastic imbalance in the prevalence of HIV across units. When comparing doses prescribed in the HIV care unit to all other medicine units, the proportion not administered (23.9% vs 16.3%, OR: 1.61, 95% CI: 1.49‐1.73, P<0.001) closely resembled the values seen when comparing patients with and without HIV hospital wide (23.5% vs 16.1%). However, when doses on the HIV care unit were stratified by HIV status, the doses not administered were 2‐fold greater, as a proportion, for patients with HIV compared with those without HIV (26.4% vs 13.1%, OR: 2.39, 95% CI: 1.93‐2.96, P<0.001).

Figure 1

The results of the multivariate regression analyses with GEE are displayed in Table 4. HIV diagnosis, non‐African American race, and heparin (as compared with enoxaparin) were associated with increased likelihood of nonadministration. Increasing age and increasing length of stay were associated with decreased likelihood of nonadministration by a small but significant amount.

The most commonly documented reason for nonadministration was refusal by the patient or family member (66% of all doses not administered). The second most common reason, patient condition not appropriate, accounted for an additional 10% of doses. Across all nursing units, the proportion of prescribed doses that were documented as refused was significantly greater for patients with HIV compared with patients without HIV (16.5% vs 10.6%, OR: 1.66, 95% CI: 1.54‐1.80, P<0.0001) (Table 2). Using the GEE and multivariate regression, HIV diagnosis, non‐African American race, and heparin were associated with increased risk of documented dose refusal. Age and length of stay were inversely related to the likelihood of documented dose refusal. When all administered doses were excluded from the analysis, the association between these variables and documented dose refusal were not as strong. Age and length of stay remained significantly inversely related; however, the other factors were no longer significantly positively associated with documented dose refusal.

Within the HIV care unit, the proportion of prescribed doses documented as refused was greater for patients with HIV compared with patients without HIV (18.1% vs 6.8%, OR: 3.01, 95% CI: 2.28‐3.99, P<0.0001). For all other medicine units, the proportion of nonadministered doses documented as refused was also greater for patients with HIV compared with patients without HIV (13.7% vs 10.7%, OR: 1.32, 95% CI: 1.16‐1.51, P<0.0001).

DISCUSSION

We have identified that nonadministration of thromboprophylaxis was more common among patients with HIV at our institution. Substantial variation in the proportion of doses not administered existed on the nursing unit level, as well as within each unit when stratified by HIV status. This disparity in dose administration was observed on the HIV care unit as well, as the proportion not administered was about 2‐fold greater for patients with HIV compared with those without HIV. Documented dose refusal appeared to account for the majority of nonadministered doses in our cohort. Our analysis also demonstrated that HIV diagnosis is significantly associated with both dose nonadministration and documented dose refusal at our institution.

Medication refusal is a well‐recognized phenomenon among hospitalized patients. A recent study of medication administration in hospitalized patients in the United Kingdom noted that refusal accounted for about 45% of omitted doses.[26] Fanikos et al. also found that documented refusal of doses contributed significantly to the overall number of VTE prophylaxis doses not administered to patients.[27] In our study, the proportion of nonadministered doses documented as refused by the patient or family member was significantly greater in patients with HIV than in patients without HIV across all units. Interestingly, the difference was greater on the HIV care unit when doses were stratified by HIV status. This observation leads us to hypothesize that specific hospital care environments may influence dose nonadministration and refusal rates among our patient population.

Based on regression analyses, increasing age and length of stay were associated with a decreased likelihood of any particular dose not being administered and with any particular dose being documented as refused. It is important to note that our GEE did not take into account date or time of each dose, and therefore we cannot make conclusions as to the likelihood of dose nonadministration or refusal of doses in relation to each other on a time scale. One cannot assume that a dose due later in a hospital course was more or less likely to be given than a dose due on the first hospital day. Although we did not expect these findings, one can hypothesize that patients who are older or have longer stays may be perceived to have more severe illness, and therefore greater need for prophylaxis, from nursing staff and others involved in their care. The associations were small but significant and warrant future investigation.

To our knowledge, this is the first investigation comparing the proportion of nonadministered doses of thromboprophylaxis between patients with and without HIV. Our data show that nonadministered doses and refused doses of thromboprophylaxis are more frequent among patients with HIV. In addition, we noted that nonadministration was more common on the dedicated HIV care unit compared with other units. We cannot currently offer a clear explanation for the disparity observed between units, and more specifically, within the HIV care unit. However, it is possible that a unique culture of care and provider‐specific factors may contribute.

Our study was limited by a number of factors. Seroconversion among patients during the study period was possible; however, our analysis revealed only 2 instances among nearly 4000 unique patients. A more significant limitation was the level of analysis allowed by the dataset. We examined dose characteristics on a dose and unit level, but the ability to analyze doses based on the prescriber and nurse level may have provided valuable insight into the specific reasons behind the observations presented here. Additionally, the specific unit assigned to a given dose in our dataset represented the discharge location for the corresponding patient, making it possible that some amount of nonadministered doses may be attributed to the incorrect unit. However, we do not believe that unit‐to‐unit transfers would be frequent enough to influence the overall results. In addition, we did not link nonadministration of thromboprophylaxis with VTE events, as these data were not present in the current dataset. Although this is a limitation of the current study, we believe that the notion that missed doses of thromboprophylaxis place patients at higher risk for VTE is plausible, as the efficacy of thromboprophylaxis is well established.[28, 29, 30] It is important to note that the reason for nonadministration selected by the nurse on the eMAR may not always represent the only reason or even the true reason for dose nonadministration. It is possible that dose refusal may be over‐represented in our sample, in part due to inaccurate documentation. Recent investigations at JHH have identified varying attitudes on the part of the patient and the nurse regarding thromboprophylaxis. A questionnaire and interview of patients showed a large knowledge gap regarding thromboprophylaxis, with many individuals unable to explain its role or significance in their medical care.[31] A common theme was also observed in a survey of nurses regarding VTE prophylaxis: doses were sometimes considered optional for reasons such as ambulation status, perceived severity of illness, or reason for hospitalization. Some nurses also reported that after an initial refused dose, they may continue to document subsequent doses as refused, sometimes without offering the dose to the patient.[32] As variation in practice was observed between individual nurses, it is also likely that the culture of care may vary between units, influencing thromboprophylaxis nonadministration rates as well as documentation of doses as refused. The dose‐level data used for the GEE analyses did not include date and time of administration, which limited the ability of the GEE to more completely account for autocorrelation.

To further investigate the findings of this and related studies, we intend to more closely analyze data at multiple levels with the goal of identifying an appropriate and feasible target for intervention. Additionally, further investigation should be performed with the goal of determining the relationship between decreased exposure to thromboprophylaxis and VTE. However, as patients with HIV appear to be at increased risk of VTE, ensuring that thromboprophylaxis is delivered appropriately and consistently should be an important goal for all who provide care to this population.

Patients with human immunodeficiency virus (HIV) are at a 2‐ to 10‐fold greater risk for venous thromboembolism (VTE) compared with the general population.[1] Although antiphospholipid antibodies and protein S deficiency have often been cited as reasons for the thrombophilia associated with HIV, previous studies have also documented an increased risk of VTE with declining CD4+ cell count.[2, 3, 4, 5, 6, 7, 8] Worsening immune function places HIV patients at increased risk for opportunistic and nonopportunistic infections and malignancies, all independently associated with an increased risk of VTE.[5, 9, 10, 11, 12] Although increasing use of antiretroviral therapy has greatly decreased these sequelae, these complications of HIV infection are associated with an increased frequency of hospitalization.[13, 14, 15, 16] HIV infection and associated inflammation has been implicated in cardiovascular conditions such as cardiomyopathy, pulmonary hypertension, and myocardial infarction.[17, 18] Additionally, progression of HIV infection appears to influence T‐cell activation and differentiation in a manner that leads to early immunosenescence in infected individuals.[19, 20]

VTE prophylaxis is effective.[21] Virtually all efforts to decrease VTE have been focused on improving the prescription of prophylaxis with varying degrees of success.[22] These interventions have been employed with the tacit assumption that medication prescribed for inpatients will always be administered. However, at our institution, recent research has demonstrated that a significant proportion of prescribed thromboprophylaxis doses are not administered to hospitalized patients.[23] Refusal by the patient or a family member was the most commonly documented reason for dose nonadministration. In addition, the rate of thromboprophylaxis nonadministration varied greatly between nursing units with distinct patient populations. We hypothesized that nonadministration of VTE prophylaxis may be more common in patients with HIV, and this phenomenon may contribute to their increased risk for VTE.

The purpose of this study was to determine if the proportion of nonadministered thromboprophylaxis is greater among hospitalized patients with HIV and to characterize documented reasons for dose nonadministration.

METHODS

This study was conducted at The Johns Hopkins Hospital (JHH), a large, urban, academic medical center in Baltimore, Maryland. This single‐center retrospective cohort study utilized an existing dataset containing dose administration data extracted from an electronic medication administration record (eMAR). This dataset included information for all prescribed doses of thromboprophylaxis (heparin 5000 U subcutaneously every 8 or 12 hours, heparin 7500 U subcutaneously every 12 hours, enoxaparin 30 mg subcutaneously every 12 hours, or enoxaparin 40 mg subcutaneously daily) for patients hospitalized on medicine units at JHH from November 2007 to December 2008. This time period follows the implementation of an electronic order set for VTE prophylaxis.[24, 25] Data available for each dose included drug name, dose, frequency, patient demographics, and whether or not the dose was administered. Each dose not administered included a reason for nonadministration, which was chosen from a dropdown menu of responses on the eMAR by the nurse at the time the dose was due. A separate electronic report was obtained from an internal administrative database, which identified all patients within the dose administration dataset who had the International Classification of Diseases, 9th Revision code 042 (HIV diagnosis). A report identifying patient history numbers with matching diagnostic code for HIV was appended to the dose administration dataset using a relational database (Microsoft Access; Microsoft Corp., Redmond, WA) prior to analysis. The dose administration data were obtained previously for a separate analysis.[23] Approval for this study was granted from the institutional review board of Johns Hopkins Medicine.

Our analytic plan included comparisons between patients with and without HIV on a dose, patient, and unit level. As JHH operates a nursing unit dedicated to the inpatient care of patients with HIV, we included analyses of dose characteristics between this unit and other medicine units. It should be noted that patients without a diagnosis of HIV are sometimes cared for on this unit. Therefore, the electronic medical record for each patient without the diagnosis code for HIV hospitalized on this unit was reviewed to determine HIV status. An analysis was performed comparing visit identification numbers with diagnosis codes to identify potential seroconversions during the study period. Although we planned to compare nonadministration and documented refusal of doses on the unit level, a lack of patients with HIV on a number of units limited our ability to perform these analyses.

RESULTS

During the 8‐month study period, 42,870 doses of thromboprophylaxis were prescribed during 4947 patient admissions to 13 individual medicine units. Overall, the diagnosis code for HIV was present in 12% of patient visits. The proportion of nonadministered doses per unit ranged from 6% to 27%, whereas the number of doses prescribed per unit ranged from 34 to 7301.

Patient characteristics were described on the visit level (Table 1). Patients with HIV were significantly younger, more often male and black, and had a longer length of stay compared with patients without HIV. Patients hospitalized on the HIV care unit had similar characteristics to the overall population of patients with HIV. It should be noted that not all patients cared for on this unit had a diagnosis of HIV, as patients from other medicine services are sometimes cared for in this location.

Overall, 17% of prescribed prophylaxis doses were not administered. A greater proportion of prescribed doses were not administered to patients with HIV compared with patients without HIV (23.5% vs 16.1%, OR: 1.59, 95% CI: 1.49‐1.70, P<0.001) (Table 2). Using a GEE and univariate regression, HIV diagnosis was associated with nonadministration of doses (OR: 1.37, 95% CI: 1.17‐1.60, P<0.001) (Table 3). Race, age, length of stay, and drug (heparin vs enoxaparin) were each associated with nonadministration. There was no significant association between nonadministration and sex, marital status, or payor. When stratified by nursing unit, there was substantial variation in the proportion of nonadministered doses between units. Within each unit, the proportion of doses not administered varied when stratified by HIV status. For example, on unit A, the proportion of doses not administered was greater for patients with HIV compared with patients without HIV (33.3% vs 12.9%, OR: 3.38, 95% CI: 2.61 to 4.37, P<0.001) (Figure 1). However, on unit K, the proportion of doses not administered to patients with HIV was 2‐fold less than in patients without HIV (7.2% vs 14.3%, OR: 0.47, 95% CI: 0.30‐0.74, P<0.001). Unit‐level analysis was not possible in regression models due to drastic imbalance in the prevalence of HIV across units. When comparing doses prescribed in the HIV care unit to all other medicine units, the proportion not administered (23.9% vs 16.3%, OR: 1.61, 95% CI: 1.49‐1.73, P<0.001) closely resembled the values seen when comparing patients with and without HIV hospital wide (23.5% vs 16.1%). However, when doses on the HIV care unit were stratified by HIV status, the doses not administered were 2‐fold greater, as a proportion, for patients with HIV compared with those without HIV (26.4% vs 13.1%, OR: 2.39, 95% CI: 1.93‐2.96, P<0.001).

Figure 1

The results of the multivariate regression analyses with GEE are displayed in Table 4. HIV diagnosis, non‐African American race, and heparin (as compared with enoxaparin) were associated with increased likelihood of nonadministration. Increasing age and increasing length of stay were associated with decreased likelihood of nonadministration by a small but significant amount.

The most commonly documented reason for nonadministration was refusal by the patient or family member (66% of all doses not administered). The second most common reason, patient condition not appropriate, accounted for an additional 10% of doses. Across all nursing units, the proportion of prescribed doses that were documented as refused was significantly greater for patients with HIV compared with patients without HIV (16.5% vs 10.6%, OR: 1.66, 95% CI: 1.54‐1.80, P<0.0001) (Table 2). Using the GEE and multivariate regression, HIV diagnosis, non‐African American race, and heparin were associated with increased risk of documented dose refusal. Age and length of stay were inversely related to the likelihood of documented dose refusal. When all administered doses were excluded from the analysis, the association between these variables and documented dose refusal were not as strong. Age and length of stay remained significantly inversely related; however, the other factors were no longer significantly positively associated with documented dose refusal.

Within the HIV care unit, the proportion of prescribed doses documented as refused was greater for patients with HIV compared with patients without HIV (18.1% vs 6.8%, OR: 3.01, 95% CI: 2.28‐3.99, P<0.0001). For all other medicine units, the proportion of nonadministered doses documented as refused was also greater for patients with HIV compared with patients without HIV (13.7% vs 10.7%, OR: 1.32, 95% CI: 1.16‐1.51, P<0.0001).

DISCUSSION

We have identified that nonadministration of thromboprophylaxis was more common among patients with HIV at our institution. Substantial variation in the proportion of doses not administered existed on the nursing unit level, as well as within each unit when stratified by HIV status. This disparity in dose administration was observed on the HIV care unit as well, as the proportion not administered was about 2‐fold greater for patients with HIV compared with those without HIV. Documented dose refusal appeared to account for the majority of nonadministered doses in our cohort. Our analysis also demonstrated that HIV diagnosis is significantly associated with both dose nonadministration and documented dose refusal at our institution.

Medication refusal is a well‐recognized phenomenon among hospitalized patients. A recent study of medication administration in hospitalized patients in the United Kingdom noted that refusal accounted for about 45% of omitted doses.[26] Fanikos et al. also found that documented refusal of doses contributed significantly to the overall number of VTE prophylaxis doses not administered to patients.[27] In our study, the proportion of nonadministered doses documented as refused by the patient or family member was significantly greater in patients with HIV than in patients without HIV across all units. Interestingly, the difference was greater on the HIV care unit when doses were stratified by HIV status. This observation leads us to hypothesize that specific hospital care environments may influence dose nonadministration and refusal rates among our patient population.

Based on regression analyses, increasing age and length of stay were associated with a decreased likelihood of any particular dose not being administered and with any particular dose being documented as refused. It is important to note that our GEE did not take into account date or time of each dose, and therefore we cannot make conclusions as to the likelihood of dose nonadministration or refusal of doses in relation to each other on a time scale. One cannot assume that a dose due later in a hospital course was more or less likely to be given than a dose due on the first hospital day. Although we did not expect these findings, one can hypothesize that patients who are older or have longer stays may be perceived to have more severe illness, and therefore greater need for prophylaxis, from nursing staff and others involved in their care. The associations were small but significant and warrant future investigation.

To our knowledge, this is the first investigation comparing the proportion of nonadministered doses of thromboprophylaxis between patients with and without HIV. Our data show that nonadministered doses and refused doses of thromboprophylaxis are more frequent among patients with HIV. In addition, we noted that nonadministration was more common on the dedicated HIV care unit compared with other units. We cannot currently offer a clear explanation for the disparity observed between units, and more specifically, within the HIV care unit. However, it is possible that a unique culture of care and provider‐specific factors may contribute.

Our study was limited by a number of factors. Seroconversion among patients during the study period was possible; however, our analysis revealed only 2 instances among nearly 4000 unique patients. A more significant limitation was the level of analysis allowed by the dataset. We examined dose characteristics on a dose and unit level, but the ability to analyze doses based on the prescriber and nurse level may have provided valuable insight into the specific reasons behind the observations presented here. Additionally, the specific unit assigned to a given dose in our dataset represented the discharge location for the corresponding patient, making it possible that some amount of nonadministered doses may be attributed to the incorrect unit. However, we do not believe that unit‐to‐unit transfers would be frequent enough to influence the overall results. In addition, we did not link nonadministration of thromboprophylaxis with VTE events, as these data were not present in the current dataset. Although this is a limitation of the current study, we believe that the notion that missed doses of thromboprophylaxis place patients at higher risk for VTE is plausible, as the efficacy of thromboprophylaxis is well established.[28, 29, 30] It is important to note that the reason for nonadministration selected by the nurse on the eMAR may not always represent the only reason or even the true reason for dose nonadministration. It is possible that dose refusal may be over‐represented in our sample, in part due to inaccurate documentation. Recent investigations at JHH have identified varying attitudes on the part of the patient and the nurse regarding thromboprophylaxis. A questionnaire and interview of patients showed a large knowledge gap regarding thromboprophylaxis, with many individuals unable to explain its role or significance in their medical care.[31] A common theme was also observed in a survey of nurses regarding VTE prophylaxis: doses were sometimes considered optional for reasons such as ambulation status, perceived severity of illness, or reason for hospitalization. Some nurses also reported that after an initial refused dose, they may continue to document subsequent doses as refused, sometimes without offering the dose to the patient.[32] As variation in practice was observed between individual nurses, it is also likely that the culture of care may vary between units, influencing thromboprophylaxis nonadministration rates as well as documentation of doses as refused. The dose‐level data used for the GEE analyses did not include date and time of administration, which limited the ability of the GEE to more completely account for autocorrelation.

To further investigate the findings of this and related studies, we intend to more closely analyze data at multiple levels with the goal of identifying an appropriate and feasible target for intervention. Additionally, further investigation should be performed with the goal of determining the relationship between decreased exposure to thromboprophylaxis and VTE. However, as patients with HIV appear to be at increased risk of VTE, ensuring that thromboprophylaxis is delivered appropriately and consistently should be an important goal for all who provide care to this population.

Vena cava filters were introduced in the 1960s as a mechanical means to prevent pulmonary embolism (PE).1 Since that time, the number of filters placed has grown steadily, to over 49,000 annually in the United States alone.2 However, patients with vena cava filters can develop complications from the filter itself, which can lead to significant morbidity and, rarely, mortality. In particular, the interruption of venous flow caused by the filter can precipitate lower extremity deep vein thrombosis (DVT),3 as well as vena caval thrombosis involving the filter itself. This has led some experts to recommend indefinite anticoagulation in patients with vena caval filters,4, 5 potentially exposing many patients to the risks of anticoagulation. Given these long‐term safety concerns, there has been recent enthusiasm for the development of optional filters. Optional vena cava filters can be classified into 2 types: temporary and retrievable. Temporary filters, which are not currently available in the United States, are held in place by a tether or catheter5 and cannot be used as permanent devices. Retrievable filters, on the other hand, maintain their position by hooks, radial pressure, or barbs and can either be removed within a prescribed time period after placement or remain in place permanently. In this way, optional filters offer the possibility of avoiding long‐term filter complications in patients with temporary contraindications to anticoagulation. Not surprisingly, the use of retrievable filters has increased dramatically, with many filters being placed for prophylactic indications in patients without known venous thromboembolism (VTE).6 In this work we review the different types of retrievable vena cava filters, current indications for placement, complications, and areas for future research.

Filter Design and Efficacy

Currently, there are 5 U.S. Food and Drug Administration (FDA)‐approved filters in the United States that can be used as retrievable filters: ALN (ALN Implants Chirurgicaux, Ghisonaccia, France); Celect (Cook Medical Incorporated, Bloomington, IN); Gunther‐Tulip (Cook Medical Incorporated, Bloomington, IN); G2 (Bard Peripheral Vascular, Tempe, AZ); and OptEase (Cordis Corporation, Miami Lakes, FL) (Table 1). Three more devices are in U.S. clinical trials: SafeFlo (Rafael Medical Technologies, Hasselt, Belgium); Crux (Crux Biomedical, Portola Valley, CA); and Option (Rex Medical, Conshohocken, PA). Filters are constructed from magnetic resonance imaging (MRI)‐compatible, nonferromagnetic alloys and are produced in either a hexagonal or conical shape. There are potential advantages and disadvantages to both designs. A hexagonal design is thought to be better for trapping small thrombi, but conical filters may have a decreased propensity toward thrombosis.7 When a hexagonal filter becomes partially occluded in vitro, flow disturbances can lead to turbulence, stasis, and progressive clot formation.7 Some clinical studies have demonstrated an increased incidence of thrombosis with hexagonal filters,8 but further investigation is needed to determine if a true correlation exists. Comparisons of the 2 types of filter design are limited but have shown no difference in their efficacy in the prevention of PE.9 Therefore, filter choice is usually dependent upon the physician performing the procedure, although other factors, such as caval size, clot extent, available venous access, and route of retrieval also may affect this decision. Furthermore, retrospective reviews have shown no difference in efficacy between retrievable and permanent filters.10

Insertion of filters is typically performed under fluoroscopy in the operating room or interventional radiology suite. Placement can also occur at the bedside using intravascular ultrasound. This option is particularly useful for critically ill patients who are not stable enough to leave the intensive care unit (ICU) for insertion. The safety of this approach has been documented for both retrievable and permanent filters.11, 12 Duplex ultrasonography has been used to allow bedside placement of permanent filters, but published experience with this modality in placement of retrievable filters is lacking.13, 14

There are no set time limits for retrieving filters, although the retrieval success rate decreases as the time postplacement increases. Rather, the decision to remove them is based on the clinical situation. Table 1 shows data on some of the longest documented successful dwell times for the various retrievable filters. Prior to filter retrieval, a venogram is performed to ensure that there is no clot in the inferior vena cava (IVC) or common iliac veins (Figure 1). Removal of a retrievable filter involves snaring one end of the filter with a hook and then slipping a sheath over the filter, which retracts the filter from the vessel wall as it is being pulled into the sheath (Figure 2). Retrieval rates from various studies are listed in Table 2. Common reasons for nonretrieval include loss to follow up,15 ongoing contraindications to anticoagulation,11, 1618 presence of large thrombi in the filter,16, 1820 poor patient prognosis,16, 18 unrelated death,1618 and filter tilting or embedment.19, 21

Figure 1

Figure 2