Using Nudges to Implement Comparative Effectiveness
| Status: | Completed |
|---|---|
| Conditions: | High Cholesterol |
| Therapuetic Areas: | Cardiology / Vascular Diseases |
| Healthy: | No |
| Age Range: | 18 - Any |
| Updated: | 4/21/2016 |
| Start Date: | September 2010 |
| End Date: | May 2015 |
Using Nudges to Implement Comparative Effectiveness: Behavioral Economics and Statins
Behavioral economics represents a powerful, albeit underutilized tool to influence provider
and systems behavior in a large-scale, meaningful, and sustainable way. The investigators
propose to use a sophisticated electronic health record (EHR) system to change the default
choice for physicians to the choice most supported by clinical practice guidelines (CPG).
Multiple guidelines exist describing best practices for effective interventions, yet a large
gap persists between actual and optimal guideline compliance. The proposed study will
examine the comparative effectiveness of an opt-out medication management protocol relative
to usual care for patients not at goal, using national guidelines for cholesterol management
implemented in large multispecialty private practices that use an Electronic Health Record
system.
Specific Aim: To determine the effectiveness of altering the default option in an EHR in
prescribing statins to selected patients using clinical decision support.
Hypotheses: Compared to usual care, a CPG-concordant intervention designed using behavioral
economics principles will significantly improve the proportion of patients who are
prescribed statins.
and systems behavior in a large-scale, meaningful, and sustainable way. The investigators
propose to use a sophisticated electronic health record (EHR) system to change the default
choice for physicians to the choice most supported by clinical practice guidelines (CPG).
Multiple guidelines exist describing best practices for effective interventions, yet a large
gap persists between actual and optimal guideline compliance. The proposed study will
examine the comparative effectiveness of an opt-out medication management protocol relative
to usual care for patients not at goal, using national guidelines for cholesterol management
implemented in large multispecialty private practices that use an Electronic Health Record
system.
Specific Aim: To determine the effectiveness of altering the default option in an EHR in
prescribing statins to selected patients using clinical decision support.
Hypotheses: Compared to usual care, a CPG-concordant intervention designed using behavioral
economics principles will significantly improve the proportion of patients who are
prescribed statins.
Historically, many interventions have been studied to improve the quality, safety, and
effectiveness of medical care, particularly through the new focus on comparative
effectiveness research. Unfortunately, sustained provider and system uptake of these
interventions has been severely lacking, to the serious detriment of patient health. The
most commonly tried tools to increase uptake, including pay-for-performance, have
substantially fallen short of expectations. Moreover, often these interventions are created
in highly artificial settings, and we have not come up with ways to implement them in the
long-term. The challenge, therefore, is to create sustainable change that impacts care in
meaningful ways.
In contrast, behavioral economics represents a powerful tool by which to influence provider
and systems behavior in a large-scale, meaningful, and sustainable way. Briefly, behavioral
economics recognizes that individuals often are not fully "rational" in the purely economic
sense, but are subject to the influence of various social, environmental and cognitive
factors in their decision making. And, one can take advantage of these findings to "nudge"
individuals, in our case physicians, towards more optimal choices. While the application of
behavioral economics has been incredibly successful in altering behavior outside the health
sphere, surprisingly little attention has been given to health.
We have chosen to focus on physician behavior in prescribing HMG-CoA reductase inhibitors
(statins) to patients with elevated cardiac risk and elevated low density lipoprotein
cholesterol (LDL-C) as recommended by cholesterol management guidelines. In a cluster
randomized trial at several private, community-based, multispecialty practices, we propose
to compare usual care to a system of automated, default, opt-out clinical decision support
that prescribes statins as appropriate.
We propose to use a cluster randomized trial design in several multispecialty private
practices to examine the comparative effectiveness of an EHR-based lipid management protocol
based on ATP III guidelines vs. usual care. Cluster randomization of participating
physicians is useful when blinding is impossible and "contamination" might be a problem,
i.e. more aggressive management among a physician's non-intervention patients as a result of
experience with intervention patients. Of an estimated 150 primary care physicians at the
recruited private practices, we expect at least 100 to consent to participate. Physicians
will be clustered for randomization based on the number of patients in their panel that meet
ATP III guidelines for statin. Physicians in each cluster will then be individually
randomized to the intervention or control arm.
Physicians randomized to usual care will not get the intervention or decision support.
Physicians randomized to the automated clinical decision support "nudge" will see the new
"optout" prescribing procedure as part of their EHR interface. This will include initially
prescribing the guideline-based medication, simvastatin 20mg. Nearly six months after this
visit, physicians will receive a reminder via EHR to schedule a follow-up fasting lipid
profile as recommended by ATP III guidelines.
effectiveness of medical care, particularly through the new focus on comparative
effectiveness research. Unfortunately, sustained provider and system uptake of these
interventions has been severely lacking, to the serious detriment of patient health. The
most commonly tried tools to increase uptake, including pay-for-performance, have
substantially fallen short of expectations. Moreover, often these interventions are created
in highly artificial settings, and we have not come up with ways to implement them in the
long-term. The challenge, therefore, is to create sustainable change that impacts care in
meaningful ways.
In contrast, behavioral economics represents a powerful tool by which to influence provider
and systems behavior in a large-scale, meaningful, and sustainable way. Briefly, behavioral
economics recognizes that individuals often are not fully "rational" in the purely economic
sense, but are subject to the influence of various social, environmental and cognitive
factors in their decision making. And, one can take advantage of these findings to "nudge"
individuals, in our case physicians, towards more optimal choices. While the application of
behavioral economics has been incredibly successful in altering behavior outside the health
sphere, surprisingly little attention has been given to health.
We have chosen to focus on physician behavior in prescribing HMG-CoA reductase inhibitors
(statins) to patients with elevated cardiac risk and elevated low density lipoprotein
cholesterol (LDL-C) as recommended by cholesterol management guidelines. In a cluster
randomized trial at several private, community-based, multispecialty practices, we propose
to compare usual care to a system of automated, default, opt-out clinical decision support
that prescribes statins as appropriate.
We propose to use a cluster randomized trial design in several multispecialty private
practices to examine the comparative effectiveness of an EHR-based lipid management protocol
based on ATP III guidelines vs. usual care. Cluster randomization of participating
physicians is useful when blinding is impossible and "contamination" might be a problem,
i.e. more aggressive management among a physician's non-intervention patients as a result of
experience with intervention patients. Of an estimated 150 primary care physicians at the
recruited private practices, we expect at least 100 to consent to participate. Physicians
will be clustered for randomization based on the number of patients in their panel that meet
ATP III guidelines for statin. Physicians in each cluster will then be individually
randomized to the intervention or control arm.
Physicians randomized to usual care will not get the intervention or decision support.
Physicians randomized to the automated clinical decision support "nudge" will see the new
"optout" prescribing procedure as part of their EHR interface. This will include initially
prescribing the guideline-based medication, simvastatin 20mg. Nearly six months after this
visit, physicians will receive a reminder via EHR to schedule a follow-up fasting lipid
profile as recommended by ATP III guidelines.
Doctors who have patients that meet the inclusion/exclusion criteria below.
Inclusion Criteria:
- Male patients 18+
- Female patients age 50+ (to avoid the possibility of women of childbearing age being
started on statin)
- Fasting lipid profile from the past year who meet ATP III guidelines for requiring a
statin
Exclusion Criteria:
- Women less than 50 years of age
- Patients with allergy/myopathy to statins in the past
- Patients with active liver disease
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