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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 2 of 2 Research Studies DisplayedColey RY, Boggs JM, Beck A
Predicting outcomes of psychotherapy for depression with electronic health record data.
This study evaluated models for predicting outcomes of psychotherapy for depression in a clinical practice setting. Findings showed that prediction models did not accurately predict depression treatment outcomes despite using rich electronic health record data and advanced analytic techniques. Recommendations included caution when considering prediction models for psychiatric outcomes using baseline intake information and transparent research to evaluate performance of any model intended for clinical use.
AHRQ-funded; HS026369.
Citation: Coley RY, Boggs JM, Beck A .
Predicting outcomes of psychotherapy for depression with electronic health record data.
J Affect Disord Rep 2021 Dec;6:100198. doi: 10.1016/j.jadr.2021.100198..
Keywords: Depression, Behavioral Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Outcomes Research, Outcomes
Beck A, Davidson AJ, Xu S
A multilevel analysis of individual, health system, and neighborhood factors associated with depression within a large metropolitan area.
This study geocoded depression diagnosis and demographic data from electronic health records to obtain both individual and neighborhood factors related to depression. The researchers found higher depression rates associated with greater age, female gender, white race, medical comorbidities, and with lower rates of home owner occupancy, residential stability, and higher educational attainment, but not with economic disadvantage. Among the cohort, higher depression rates were associated with higher crime rates and a lower percent of foreign born residents and single mother households.
AHRQ-funded; HS022143.
Citation: Beck A, Davidson AJ, Xu S .
A multilevel analysis of individual, health system, and neighborhood factors associated with depression within a large metropolitan area.
J Urban Health 2017 Dec;94(6):780-90. doi: 10.1007/s11524-017-0190-x..
Keywords: Depression, Electronic Health Records (EHRs), Social Determinants of Health, Urban Health