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Incidence, Persistence, and Steady-State Prevalence in Coding Intensity for Health Plan Payment.

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Medicare diagnosis coding intensity can be measured by incidence and persistence. These metrics explain growing prevalence and inform monitoring of coding practices for risk adjustment.

Keywords:
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Area of Science:

  • Health Services Research
  • Health Economics
  • Epidemiology

Background:

  • Diagnostic coding intensity in Medicare influences risk adjustment and payment models.
  • Understanding coding dynamics is crucial for accurate healthcare policy and financial assessments.
  • Previous measures did not fully capture the temporal aspects of coding prevalence changes.

Purpose of the Study:

  • To define novel measures of Medicare diagnosis coding intensity.
  • To capture the dynamics of changes in coding prevalence over time.
  • To apply these measures to high-cost diagnoses within Medicare's risk-adjustment model for Accountable Care Organizations (ACOs).

Main Methods:

  • Retrospective analysis of Medicare claims data from 2017-2018.
  • Utilized a 20% random sample of beneficiaries assigned to ACOs.
  • Decomposed coding prevalence into incidence (new codes) and persistence (continued codes).

Main Results:

  • Introduced 'steady-state prevalence' as a hypothetical long-run prevalence based on current incidence and persistence rates.
  • Demonstrated how incidence and persistence explain observed growth in coding prevalence.
  • Illustrated the application of these measures to costly diagnoses in Medicare's ACO risk-adjustment model.

Conclusions:

  • Diagnostic coding behavior is heterogeneous and responsive to incentives.
  • Separately measuring incidence and persistence enhances monitoring of coding practices.
  • Changes in coding practices can have long-term effects on prevalence, independent of ongoing behavioral shifts.