Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes
Introduction: Patient satisfaction is a patient-reported outcome with the potential to assess and improve the quality of newer care-management models such as remote patient monitoring using telecommunication technology. Objective: To evaluate differences in patient satisfaction among 3 care manageme...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2020-10-01
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| Series: | Journal of Patient Experience |
| Online Access: | https://doi.org/10.1177/2374373519884177 |
| Summary: | Introduction: Patient satisfaction is a patient-reported outcome with the potential to assess and improve the quality of newer care-management models such as remote patient monitoring using telecommunication technology. Objective: To evaluate differences in patient satisfaction among 3 care management groups in a comparative effectiveness trial. Methods: This study analyzed a comparative effectiveness trial that tested automated remote assessment technology–facilitated comorbid depression care-management (TC, n = 254) in comparison to team-supported depression care (SC, n = 228) and usual primary care (UC, n = 218) among low-income patients with type 2 diabetes. Relationships between patient satisfaction and care group were evaluated at each 6-month phase up to 18 months using linear regression models that controlled for depression status, diabetes symptoms, patient characteristics, and study group differences. Results: While receiving care management, SC and TC patients were significantly more satisfied with depression care than UC patients. No consistently significant associations between patient satisfaction and patient characteristics or disease symptoms were found. Conclusions: Patient satisfaction was found to be influenced by elements of care-management, not by patient characteristics or disease symptoms. Results suggest greater patient satisfaction with depression care in a care-management model than UC, whether through clinician team support or automated remote monitoring technology. |
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| ISSN: | 2374-3735 2374-3743 |