Using Nudges to Implement Comparative Effectiveness

NCT ID: NCT01575171

Last Updated: 2015-08-03

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 19 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2010-09-30
• Study Completion Date: 2015-05-31

Brief Summary

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.

Detailed Description

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.

Conditions

Hypercholesterolemia

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Intervention/"Nudge"

Individuals will be analyzed according to their assigned intervention group, to compare the effectiveness of an opt-out EHR decision support system to enhance the prescription of statins to those patients with an elevated LDL-C and to subsequently titrate the medication dose until LDL-C control is obtained. 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.

Nudge

Intervention Type: BEHAVIORAL

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. 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.

Interventions

Nudge

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. 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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

NYU Langone Health

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Joseph Ravenell, MD, MS

Role: PRINCIPAL_INVESTIGATOR

NYU School of Medicine

Brian Elbel, PhD, MPH

Role: PRINCIPAL_INVESTIGATOR

NYU School of Medicine

Locations

Murray Hill Medical Group

New York, New York, United States

Countries

United States

Other Identifiers

10-01287

Identifier Type: -

Identifier Source: org_study_id