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Area of Science:

  • Behavioral Health Services Research
  • Health Economics
  • Integrated Care Models

Background:

  • Historically, mental health and substance use treatments have been separate, hindering care for co-occurring disorders.
  • Integrated care models, facilitated by blended payment strategies, are crucial for addressing complex patient needs.
  • This study examines the effect of a blended payment model on diagnosing co-occurring disorders within a community mental health system.

Purpose of the Study:

  • To assess the impact of a blended payment strategy on the diagnosis rates of co-occurring disorders.
  • To evaluate how blended payment models influence the identification of complex behavioral health conditions.

Main Methods:

  • Analysis of electronic health record data from 19,373 individuals (173,889 observations) between January 2017 and December 2019.
  • Utilized multilevel growth modeling with a binary dependent variable for co-occurring disorder diagnoses.
  • Included fixed effects for time, blended payment initiation, race, gender, age, and payor, with random effects for service user and agency.

Main Results:

  • Blended payments (capitated and fee-for-service) significantly increased the likelihood of co-occurring disorder diagnoses.
  • Individuals identifying as people of color had lower odds of receiving co-occurring diagnoses, though this varied in rural settings.
  • Service users in unintegrated agencies showed higher odds of receiving co-occurring diagnoses.

Conclusions:

  • This research is among the first to evaluate the effects of blended payment models on behavioral health access and diagnosis.
  • Blended payment models can serve as a financial incentive for providers to identify complex diagnoses often missed in standard care.
  • Integrated payment strategies show promise in improving the recognition and treatment of co-occurring disorders.