BACKGROUND: Treatments for mental health and substance use problems have historically been unintegrated, limiting co-occurring disorders treatment. Blending discrete payment models is one potential facilitator of integrated care. This study assesses the impact of one blended payment strategy on the diagnosis of co-occurring disorders in a community mental health system.
METHODS: Electronic health record data for 19373 individuals, with 173889 observations from January 2017 through December 2019 was analyzed for this study. Multilevel growth modelling was used for data analysis. A binary dependent variable represented whether a service user held diagnoses of co-occurring disorders within a month. Fixed effects included time variables and a variable representing blended payment initiation as well as race, gender, age, and payor. Service user and agency variables were modeled as random effects.
FINDINGS: Blended capitated and fee-for-service payments were found to increase the odds of service users receiving co-occurring diagnoses. People of color had lower odds of receiving a co-occurring diagnosis, although this effect did not hold in an analysis of rural agencies. Service users receiving care in unintegrated agencies had higher odds of receiving co-occurring diagnoses.
CONCLUSION: This study is one of the first to assess the impacts of a blended payment model on behavioral health access. Blended payment models can incentivize behavioral health providers and systems to identify complex diagnoses that may go unrecognized in routine care.
Incentivizing co-occurring disorder diagnoses through blended payments
Social Science and Medicine, 389, 118849. doi: 10.1016/j.socscimed.2025.118849.