OBJECTIVE: To analyze the association between the organizational features of integration of physical and mental healthcare in womens health clinics and the diagnosis of depression among women veterans with or at risk for cardiovascular conditions (ie, diabetes mellitus, heart disease, or hypertension). STUDY DESIGN: Retrospective and observational secondary data analyses. METHODS: We studied 27,972 women veterans from 118 facilities with diagnosed cardiovascular conditions in fiscal year 2001 (FY2001) using merged Medicare claims and Veterans Health Administration (VHA) data merged with the 1999 VHA Survey of Primary Care Practices and the 2001 VHA Survey of Women Veterans Health Programs and Practices. The dependent variable was a binary indicator for diagnosed depression during FY2001 at the individual level. We used a multilevel logistic regression model to control for clustering of women veterans within facilities. Individual-level independent variables included demographics, socioeconomic characteristics, and chronic physical conditions. RESULTS: Overall, 27% of women veterans using the VHA were diagnosed as having depression in FY2001. Across facilities, rates of diagnosed depression varied from 13% to 41%. After controlling for individual-level and facility-level independent variables, women veterans who were served in separate women's health clinics with integrated physical and mental healthcare were more likely to have diagnosed depression. The adjusted odds ratio was 1.12 (95% confidence interval, 1.01-1.25). CONCLUSIONS: Existing women-specific VHA organizational features with integration of primary care and mental health seem effective in diagnosing depression. Emerging patient-centered medical home models may facilitate diagnosis and treatment of mental health issues among women with complex chronic conditions.
OBJECTIVE: To analyze the association between the organizational features of integration of physical and mental healthcare in womens health clinics and the diagnosis of depression among women veterans with or at risk for cardiovascular conditions (ie, diabetes mellitus, heart disease, or hypertension). STUDY DESIGN: Retrospective and observational secondary data analyses. METHODS: We studied 27,972 women veterans from 118 facilities with diagnosed cardiovascular conditions in fiscal year 2001 (FY2001) using merged Medicare claims and Veterans Health Administration (VHA) data merged with the 1999 VHA Survey of Primary Care Practices and the 2001 VHA Survey of Women Veterans Health Programs and Practices. The dependent variable was a binary indicator for diagnosed depression during FY2001 at the individual level. We used a multilevel logistic regression model to control for clustering of women veterans within facilities. Individual-level independent variables included demographics, socioeconomic characteristics, and chronic physical conditions. RESULTS: Overall, 27% of women veterans using the VHA were diagnosed as having depression in FY2001. Across facilities, rates of diagnosed depression varied from 13% to 41%. After controlling for individual-level and facility-level independent variables, women veterans who were served in separate women's health clinics with integrated physical and mental healthcare were more likely to have diagnosed depression. The adjusted odds ratio was 1.12 (95% confidence interval, 1.01-1.25). CONCLUSIONS: Existing women-specific VHA organizational features with integration of primary care and mental health seem effective in diagnosing depression. Emerging patient-centered medical home models may facilitate diagnosis and treatment of mental health issues among women with complex chronic conditions.
Authors: Melissa M Farmer; Maggie A Stanislawski; Mary E Plomondon; Bevanne Bean-Mayberry; Nataria T Joseph; Lauren E Thompson; Jessica L Zuchowski; Stacie L Daugherty; Elizabeth M Yano; P Michael Ho Journal: J Womens Health (Larchmt) Date: 2017-05-12 Impact factor: 2.681
Authors: Elisheva R Danan; Erin E Krebs; Kristine Ensrud; Eva Koeller; Roderick MacDonald; Tina Velasquez; Nancy Greer; Timothy J Wilt Journal: J Gen Intern Med Date: 2017-09-14 Impact factor: 5.128
Authors: Yeonsu Song; Donna L Washington; Elizabeth M Yano; Susan M McCurry; Constance H Fung; Joseph M Dzierzewski; Juan Carlos Rodriguez; Stella Jouldjian; Michael N Mitchell; Cathy A Alessi; Jennifer L Martin Journal: Behav Sleep Med Date: 2016-10-03 Impact factor: 3.492