Using Nudges to Implement Comparative Effectiveness

This study is ongoing, but not recruiting participants.
Sponsor:
Information provided by (Responsible Party):
New York University School of Medicine
ClinicalTrials.gov Identifier:
NCT01575171
First received: April 2, 2012
Last updated: September 23, 2014
Last verified: September 2014
  Purpose

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.


Condition Intervention
Hypercholesterolemia
Behavioral: Nudge

Study Type: Observational
Study Design: Observational Model: Case Control
Time Perspective: Prospective
Official Title: Using Nudges to Implement Comparative Effectiveness: Behavioral Economics and Statins

Resource links provided by NLM:


Further study details as provided by New York University School of Medicine:

Primary Outcome Measures:
  • Nudge Acceptance or Rejection [ Time Frame: Doctor visit to 6 months ] [ Designated as safety issue: No ]
    A "Nudge" or opt-out default option is implemented in the electronic health record system based on national clinical guidelines. We plan to measure if the Nudge is accepted or rejected by doctors.


Estimated Enrollment: 40
Study Start Date: September 2010
Estimated Study Completion Date: February 2015
Estimated Primary Completion Date: February 2015 (Final data collection date for primary outcome measure)
Groups/Cohorts Assigned Interventions
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.
Behavioral: 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.

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.

  Eligibility

Ages Eligible for Study:   18 Years and older
Genders Eligible for Study:   Both
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population

Doctors in a large multi-specialty private practice

Criteria

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
  Contacts and Locations
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Please refer to this study by its ClinicalTrials.gov identifier: NCT01575171

Locations
United States, New York
Murray Hill Medical Group
New York, New York, United States, 10016
Sponsors and Collaborators
New York University School of Medicine
Investigators
Principal Investigator: Joseph Ravenell, MD, MS NYU School of Medicine
Principal Investigator: Brian Elbel, PhD, MPH NYU School of Medicine
  More Information

No publications provided

Responsible Party: New York University School of Medicine
ClinicalTrials.gov Identifier: NCT01575171     History of Changes
Other Study ID Numbers: 10-01287
Study First Received: April 2, 2012
Last Updated: September 23, 2014
Health Authority: United States: Institutional Review Board

Additional relevant MeSH terms:
Hypercholesterolemia
Dyslipidemias
Hyperlipidemias
Lipid Metabolism Disorders
Metabolic Diseases

ClinicalTrials.gov processed this record on October 23, 2014