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Incidence, Persistence, and Steady-State Prevalence in Coding Intensity for Health Plan Payment
Thomas G McGuire1, Oana M Enache2, Michael Chernew1
1Department of Health Care Policy, Harvard Medical School, Boston, MA.
Objective:
To define measures of Medicare diagnosis coding intensity that capture the dynamics of changes in coding practices.
Study Setting And Design:
Retrospective analysis of coding for risk adjustment using observational claims data from Medicare beneficiaries.
Data Sources:
Enrollment and claims data from 2017-2018 of a random 20 percent sample of Medicare beneficiaries were subset to those assigned to an Accountable Care Organization in 2018.
Principal Findings:
We decompose prevalence of a diagnosis code into incidence (proportion of beneficiaries that newly have the code) and persistence (proportion of beneficiaries who previously had the code and continue to do so). Together these define steady-state prevalence, the hypothetical long-run prevalence implied by no changes in current rates of incidence and persistence of coding. Steady-state prevalence can help explain why observed prevalence tends to grow over time without continued behavioral change. For example, our measures suggest that the prevalence of the Specified Heart Arrhythmias diagnosis would continue to rise from 18.7% in 2018 to 28.0% without changes in coding practices.
Conclusions:
Researchers and policymakers can better understand why changes in coding practices can take years to be fully reflected in data and monitor coding behavior by using our proposed measures.
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