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Spillovers Within and Between Physicians: Evidence from a Randomized Overprescribing Letter in Medicare
Last registered on December 28, 2018

Pre-Trial

Trial Information
General Information
Title
Spillovers Within and Between Physicians: Evidence from a Randomized Overprescribing Letter in Medicare
RCT ID
AEARCTR-0003209
Initial registration date
September 20, 2018
Last updated
December 28, 2018 11:59 AM EST
Location(s)

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Primary Investigator
Affiliation
Columbia University
Other Primary Investigator(s)
PI Affiliation
Columbia University
PI Affiliation
Harvard T.H. Chan School of Public Health
Additional Trial Information
Status
In development
Start date
2015-04-20
End date
2021-01-01
Secondary IDs
Abstract
In a fragmented healthcare system, efforts to change a physician’s practice patterns for the publicly insured may have implications for healthcare delivery that go beyond just the targeted physicians and insurers. Specifically, these efforts could change how physicians treat privately insured patients, and they could also influence the practice patterns of other physicians through peer effects. In this work, we aim to generate credible estimates of these spillovers by exploiting a randomized intervention that sought to reduce antipsychotic prescribing to publicly insured older and disabled adults. The original trial sent letters to high volume prescribers of the antipsychotic quetiapine in Medicare. The letters contained a peer comparison message and warned prescribers that they were under review by Medicare, and they reduced antipsychotic prescribing to Medicare patients by 16% over two years. We will estimate two spillovers. First, using commercial insurance data, we will estimate the effect of the letters on antipsychotic prescribing in private insurance, a within-prescriber spillover. Second, using Medicare data linked to practice and referral data, we will estimate the effect on antipsychotic prescribing by peers of the original study physicians, a between-prescriber spillover.
Registration Citation
Citation
Barnett, Michael, Andrew Olenski and Adam Sacarny. 2018. "Spillovers Within and Between Physicians: Evidence from a Randomized Overprescribing Letter in Medicare." AEA RCT Registry. December 28. https://doi.org/10.1257/rct.3209-2.0
Former Citation
Barnett, Michael, Andrew Olenski and Adam Sacarny. 2018. "Spillovers Within and Between Physicians: Evidence from a Randomized Overprescribing Letter in Medicare." AEA RCT Registry. December 28. https://www.socialscienceregistry.org/trials/3209/history/39665
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
Placebo Arm: The placebo arm received a letter describing a coming rule in Medicare that required prescribers to enroll in Medicare. The placebo arm then received a correction letter clarifying the rule. None of the letters mentioned prescribing of quetiapine.

Treatment Arm: The treatment arm prescribers received three letters, spaced roughly 3 months apart, about their quetiapine prescribing. Each letter included a peer comparison message and a notification that the prescriber was under review by Medicare.
Intervention Start Date
2015-04-20
Intervention End Date
2015-10-20
Primary Outcomes
Primary Outcomes (end points)
Days of quetiapine supplied during the intervention period of April 20, 2015 to December 31, 2016
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In the original randomized trial, an analysis was conducted to identify outlier general-care prescribers of quetiapine in Medicare Part D. This analysis identified 5,055 prescribers, and they were then randomly allocated to the treatment or the control group. These prescribers are the "original study prescribers". The treatment prescribers were sent peer comparison review letters about their quetiapine prescribing; the control prescribers were sent placebo letters about an unrelated regulation.
This follow-up analysis considers two forms of spillover effects of the original letters. First, we examine whether the intervention altered prescribing by original study prescribers to patients covered by commercial insurance. For this analysis, we compare commercial prescribing in the original treatment and control groups.
Second, we examine whether the intervention influenced Medicare prescribing by peers of the original study participants. Peers are defined as either members of the same group practice as the original study prescribers or as those who share patients with original study prescribers. For this analysis, we study the Medicare prescribing of peers of physicians in the original treatment and control groups, exploiting the random assignment of the original study participants as a source of exogenous exposure to peer effects.
Experimental Design Details
Not available
Randomization Method
In the original study: randomization done by computer (in Stata)
Randomization Unit
Prescriber
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
5,055
Sample size: planned number of observations
Spillovers onto commercial insurance: 5,055 Spillovers onto peers: TBD
Sample size (or number of clusters) by treatment arms
Spillovers onto commercial insurance: 2,528 control arm, 2,527 treatment arm
Spillovers onto peers: TBD
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Columbia University Human Research Protection Office
IRB Approval Date
2018-06-17
IRB Approval Number
AAAR9368(M00Y01)
Analysis Plan

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