A Joint Choice Model of the Decision to Seek Depression Treatment and Choice of Provider Sector

Bibliographic Data

ID9101938
AuthorsJohn C Fortney (0000-0001-9409-8894, University of Arkansas for Medical Sciences, corresponding author), John Fortney, Kathryn Rost (corresponding author), Mingliang Zhang (0000-0002-6421-7730, corresponding author)
Year1998
Volume36
Issue3
Pages307-320
Publication date1998-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-199803000-00008
PMID9520956
OpenAlexW2031682412
LanguageEN
Citations received7
References cited19

OBJECTIVES: Using a community-based sample of currently depressed subjects, this research modeled the joint decision to seek depression treatment and choice of provider sector (primary care or specialty mental health). The objective was to identify those subject-specific case-mix factors and those provider sector-specific access measures that significantly impacted this joint decision. METHODS: A community-based sample of 435 Arkansans with current depression symptoms was compiled using random digit dialing and the Burnam depression screener. Study subjects were administered baseline and 6-month follow-up surveys. All medical, pharmaceutical, and insurance records were collected and abstracted to verify service use and depression treatment. Three discrete choice model specifications were tested: sequential binary logit models, a multinomial logit model, and a nested logit model. The nested logit model makes less restrictive assumptions about the patterns of substitution across treatment alternatives than the other model specifications. RESULTS: In the 6 months after baseline, 73.3% of the sample did not seek depression treatment, 18.9% sought care from a primary care provider, and 7.8% sought care from a mental health specialist. A likelihood ratio test identified the nested logit model as the preferred model specification (chi 2 < or = 0.05), indicating that the expected maximum utility of sector choice significantly affects the decision to seek treatment. Provider sector-specific access measures (e.g., insurance coverage and availability) significantly impacted sector choice and, thus, the decision to seek treatment. Subject-specific case-mix factors (e.g., age, gender, employment status, depression severity, and psychiatric comorbidity) significantly affected the decision to seek treatment. CONCLUSIONS: Sector-specific access measures significantly impact both provider sector choice and the decision to seek treatment. Because the primary care and specialty care treatment alternatives were more substitutable with one another than with the no treatment option, changes in access affected sector choice more than the decision to seek treatment

Actuarial science · Business · Depression (economics) · Economics · Health care · Joint (building) · Patient choice · Engineering · Health Systems, Economic Evaluations, Quality of Life · Mental Health Treatment and Access · Patient Satisfaction in Healthcare · Psychology

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