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Trial Title
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The Effect of Informative Letters on Fraud and Abuse in Medicare
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The Effect of Informative Letters on the Prescription and Receipt of Schedule II Controlled Substances
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Trial Status
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in_development
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on_going
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Abstract
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Before
Fraud and waste is estimated to cost the American health care system nearly $200 billion each year, and the public Medicare and Medicaid programs about $60 billion each year. This study will evaluate a new method for fighting fraud: mailing informative letters to outlier providers to notify them of their aberrant behavior. We will look at the effects of these letters on the behavior of providers and their patients. These effects are of substantial policy interest as they suggest how to best design anti-fraud policies. They are also of academic interest, shedding light on the behavior of physicians and their patients.
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After
Fraud and waste is estimated to cost the American health care system nearly $200 billion each year, and the public Medicare and Medicaid programs about $60 billion each year. This study will evaluate a new method for fighting fraud: mailing informative letters to outlier providers to notify them of their aberrant behavior. These letters are targeted at high prescribers of schedule II controlled substances in Medicare Part D. We will look at the effects of these letters on the behavior of providers and their patients. These effects are of substantial policy interest as they suggest how to best design anti-fraud policies. They are also of academic interest, shedding light on the behavior of physicians and their patients.
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Last Published
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October 06, 2014 05:07 PM
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January 17, 2015 06:42 PM
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Intervention (Public)
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A letter or series of letters to providers explaining that their behavior is highly unlike their peers.
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After
A letter to outlier prescribers of schedule II controlled substances explaining that their prescribing behavior is highly unlike their peers.
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Intervention End Date
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October 01, 2015
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September 11, 2015
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Primary Outcomes (End Points)
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The primary endpoint of this trial will be the outcome targeted by the letter campaign. For example, in a letter targeting outlier prescribers of a controlled substance, the target will be the count of prescriptions of this controlled substance by the prescriber.
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The primary outcome of the study is the effect of the letters on the prescribing of schedule II controlled substances over the 3 months following the initial sending of the letters. Prescribing is defined as the total “days supply” of schedule II controlled substances attributed to the prescriber, expressed in “30-day equivalents” i.e. divided by 30.
We consider additional outcomes as well. Through these additional analyses, we hope to understand the totality of the effects of the letters. The secondary analysis for prescribers includes explorations of effect heterogeneity, quantile treatment effects, substitution toward other substances, and peer effects. We also conduct analyses looking at a cohort of patients who were treated by the prescribers prior to the sending of the letters. We will assign these patients to treatment and control groups based on whether their attributed prescriber was a treatment or control prescriber and study the total receipt of controlled substances by patients, heterogeneity in treatment effects, substitution toward other substances, and health outcomes.
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Experimental Design (Public)
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Before
Working with CMS, we will identify potentially fraudulent providers on a set of dimensions using administrative billing claims data. Once the providers have been identified, we will randomly select half of the providers (the treatment group) to receive the intervention: an informative letter.
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After
An analysis was conducted to identify outlier prescribers of Schedule II controlled substances in the Medicare Part D. This analysis identified a group of prescribers, and they were then randomly allocated to a treatment or a control group.
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Randomization Method
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Randomization done by computer
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Randomization done by computer (in Stata)
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Randomization Unit
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The provider (e.g. physician, nurse, physician assistant, etc.)
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The prescriber (e.g. physician, nurse, physician assistant, etc.)
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Planned Number of Clusters
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Approximately 1500 providers per letter campaign
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Approximately 1500 prescribers
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Planned Number of Observations
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Approximately 1500 providers per letter campaign
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Approximately 1500 prescribers
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Sample size (or number of clusters) by treatment arms
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Approximately 750 providers in the control arm and 750 providers in the treatment arm, per campaign
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Approximately 750 providers in the control arm and 750 providers in the treatment arm
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Power calculation: Minimum Detectable Effect Size for Main Outcomes
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We constructed a sample of outlier prescribers that replicated the method used in the study but was built from a more limited dataset. Using these prescribers we estimated that at a significance level of 5% and a power of 80%, we could detect a change in the number of schedule II prescription drug events of 136.9 (baseline mean level: 1,556.7; standard deviation: 1,231.2; effect as a share of baseline mean: 8.8%) and a change in the dollar value of schedule II prescriptions of $34,069 (baseline mean level: $217,204; standard deviation: $239,759; effect as a share of baseline mean: 15.7%).
Since we will have access to richer data with better control variables, we believe that these estimates are conservative.
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