TY - JOUR
AU - D. Baslock
AU - J. I. Manuel
AU - V. Stanhope
A1 - 
AB - 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.
AD - School of Social Work, Virginia Commonwealth University, Richmond, VA, USA. Electronic address: baslockd@vcu.edu.; School of Social Work, University of Connecticut, Hartford, CT, USA.; Silver School of Social Work, New York University, New York, NY, USA.
AN - 41338045
BT - Soc Sci Med
C5 - Financing & Sustainability; Opioids & Substance Use
DA - Jan
DO - 10.1016/j.socscimed.2025.118849
DP - NLM
ET - 20251128
JF - Soc Sci Med
LA - eng
N2 - 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.
PY - 2026
SN - 0277-9536
SP - 118849
ST - Incentivizing co-occurring disorder diagnoses through blended payments
T1 - Incentivizing co-occurring disorder diagnoses through blended payments
T2 - Soc Sci Med
TI - Incentivizing co-occurring disorder diagnoses through blended payments
U1 - Financing & Sustainability; Opioids & Substance Use
U3 - 10.1016/j.socscimed.2025.118849
VL - 389
VO - 0277-9536
Y1 - 2026
ER -