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Using mHealth technologies to improve the identification of behavioral health problems in urban primary care settings

INTRODUCTION: Behavioral health disorders remain under recognized and under diagnosed among urban primary care patients. Screening patients for such problems is widely recommended, yet is challenging to do in a brief primary care encounter, particularly for this socially and medically complex patien...

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Detalles Bibliográficos
Autores principales: Staeheli, Martha, Aseltine, Robert H, Schilling, Elizabeth, Anderson, Daren, Gould, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467966/
https://www.ncbi.nlm.nih.gov/pubmed/28634539
http://dx.doi.org/10.1177/2050312117712656
Descripción
Sumario:INTRODUCTION: Behavioral health disorders remain under recognized and under diagnosed among urban primary care patients. Screening patients for such problems is widely recommended, yet is challenging to do in a brief primary care encounter, particularly for this socially and medically complex patient population. METHODS: In 2013, intervention patients at an urban Connecticut primary clinic were screened for post-traumatic stress disorder, depression, and risky drinking (n = 146) using an electronic tablet-based screening tool. Screening data were compared to electronic health record data from control patients (n = 129) to assess differences in the prevalence of behavioral health problems, rates of follow-up care, and the rate of newly identified cases in the intervention group. RESULTS: Results from logistic regressions indicated that both groups had similar rates of disorder at baseline. Patients in the intervention group were five times more likely to be identified with depression (p < 0.05). Post-traumatic stress disorder was virtually unrecognized among controls but was observed in 23% of the intervention group (p < 0.001). The vast majority of behavioral health problems identified in the intervention group were new cases. Follow-up rates were significantly higher in the intervention group relative to controls, but were low overall. CONCLUSION: This tablet-based electronic screening tool identified significantly higher rates of behavioral health disorders than have been previously reported for this patient population. Electronic risk screening using patient-reported outcome measures offers an efficient approach to improving the identification of behavioral health problems and improving rates of follow-up care.