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Low-income minority patient engagement with automated telephonic depression assessment and impact on health outcomes

PURPOSE: We investigated dimensions of low-income minority patient engagement in the context of diabetes-depression care-management with automated telephone assessment (ATA) calls as a facilitator. METHODS: Mixed method analyses (including regression analyses and coding of interviews) were used to e...

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Detalles Bibliográficos
Autores principales: Vidyanti, Irene, Wu, Brian, Wu, Shinyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4412647/
https://www.ncbi.nlm.nih.gov/pubmed/25543270
http://dx.doi.org/10.1007/s11136-014-0900-8
Descripción
Sumario:PURPOSE: We investigated dimensions of low-income minority patient engagement in the context of diabetes-depression care-management with automated telephone assessment (ATA) calls as a facilitator. METHODS: Mixed method analyses (including regression analyses and coding of interviews) were used to examine patient engagement with technology, assess its impact on health outcomes and satisfaction with care, and analyze barriers to engagement. Patient engagement was measured by analyzing patient’s ATA call response rates. We then evaluated those results in the context of the outcomes of the broader clinical trial, which compared three study arms. RESULTS: Average completed call rate throughout the study is about 50 % and decreases after 6 months. The biggest barrier to patient engagement is timing. Patient engagement levels differ by baseline depression status and have no significant effect on health outcomes and satisfaction with care at 6, 12, and 18 months. However, from the preliminary clinical trial results, the arm in which the ATA system is implemented has higher satisfaction with depression care than the two control arms. Thus, it is more likely that technology positively affects satisfaction with depression care outcomes through provider engagement rather than patient engagement. CONCLUSIONS: The study’s patient engagement results and identified barriers would be useful to aid the design and implementation of future automated screening and monitoring systems to optimize patient engagement. The results also suggest that implementing a technology-supported care-management might not result in outcome disparities among patients with different levels of patient engagement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11136-014-0900-8) contains supplementary material, which is available to authorized users.