Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Sep;50(5):712-724.
doi: 10.1007/s10488-023-01271-0. Epub 2023 May 26.

Can a Home-Based Collaborative Care Model Reduce Health Services Utilization for Older Medicaid Beneficiaries Living with Depression and Co-occurring Chronic Conditions? A Quasi-experimental Study

Lesley Steinman  1   2 , Jingping Xing  3 , Beverly Court  3 , Norma B Coe  4   5 , Andrea Yip  6 , Clara Hill  7 , Bea Rector  8 , Barbara Baquero  9 , Bryan J Weiner  10 , Mark Snowden  11
Affiliations

Can a Home-Based Collaborative Care Model Reduce Health Services Utilization for Older Medicaid Beneficiaries Living with Depression and Co-occurring Chronic Conditions? A Quasi-experimental Study

Lesley Steinman et al. Adm Policy Ment Health. 2023 Sep.

Abstract

Depression remains a major public health issue for older adults, increasing risk of costly health services utilization. While home-based collaborative care models (CCM) like PEARLS have been shown to effectively treat depression in low-income older adults living with multiple chronic conditions, their economic impact is unclear. We conducted a quasi-experimental study to estimate PEARLS effect on health service utilization among low-income older adults. Our secondary data analysis merged de-identified PEARLS program data (N = 1106), home and community-based services (HCBS) administrative data (N = 16,096), and Medicaid claims and encounters data (N = 164) from 2011 to 2016 in Washington State. We used nearest neighbor propensity matching to create a comparison group of social service recipients similar to PEARLS participants on key determinants of utilization guided by Andersen's Model. Primary outcomes were inpatient hospitalizations, emergency room (ER) visits, and nursing home days; secondary outcomes were long-term supports and services (LTSS), mortality, depression and health. We used an event study difference-in-difference (DID) approach to compare outcomes. Our final dataset included 164 older adults (74% female, 39% people of color, mean PHQ-9 12.2). One-year post-enrollment, PEARLS participants had statistically significant improvements in inpatient hospitalizations (69 fewer hospitalizations per 1000 member months, p = 0.02) and 37 fewer nursing home days (p < 0.01) than comparison group participants; there were no significant improvements in ER visits. PEARLS participants also experienced lower mortality. This study shows the potential value of home-based CCM for participants, organizations and policymakers. Future research is needed to examine potential cost savings.

Keywords: Depression; Difference-in-difference; Home and community-based services; Older adults; Poverty; Propensity matching.

PubMed Disclaimer

Conflict of interest statement

Conflict of Interest The authors have no competing interests to declare. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of AARP Foundation.

Figures

Fig. 1
Fig. 1
Adapted Andersen model of health services utilization for PEARLS evaluation in Washington State* Abbreviations: BMI = body mass index; ER = emergency room; HCBS = home - and community -based services; LTSS = long -term services and supports; WA = Washington State * adapted from Andersen’s Behavioral Model of Health Services Use (Andersen, 1995; Babitsch, 2012)
Fig. 2
Fig. 2
Flow chart for creating the propensity matched dataset for analysis
Fig. 3
Fig. 3
Event study difference in difference (DiD) approach for PEARLS evaluation
See this image and copyright information in PMC

References

    1. Aldridge MD, & Bradley EH (2017). Epidemiology and patterns of care at the end of life: Rising complexity, shifts in care patterns and sites of death. Health Affairs, 36(7), 1175–1183. 10.1377/hlthaff.2017.0182 - DOI - PubMed
    1. AIMS. (2019). Cheat Sheet on Medicare Payments for Behavioral Health Integration Services. AIMS (Advancing Integrated Mental health Solutions) Center, Department of Psychiatry and Behavioral Sciences, University of Washington, https://aims.uw.edu/sites/default/files/CMS_FinalRule_BHI_CheatSheet.pdf. Accessed May 24 2023.
    1. Andersen R (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(March), 1–10. - PubMed
    1. Antonelli-Incalzi R, Ancona C, Forastiere F, Belleudi V, Corsonello A, & Perucci CA (2007). Socioeconomic status and hospitalization in the very old: A retrospective study. BMC Public Health, 7(1), 227. 10.1186/1471-2458-7-227 - DOI - PMC - PubMed
    1. Archibald N, Moses K, & Rava L (2019). Using Health Homes to Integrate Care for Dually Eligible Individuals: Washington State’s Experiences. https://www.integratedcareresourcecenter.com/sites/default/files/Washing...

Publication types

LinkOut - more resources