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Journal article
Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial
Journal of medical Internet research, v 20(4), pp e147-e147
01 Apr 2018
PMID: 29685872
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background: Comorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers.
Objective: The aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes.
Methods: DCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design.
Results: DCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=. 03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, technology-facilitated care=4.20; P=.05); and increased odds of taking an glycated hemoglobin test (technology-facilitated care vs usual care: OR=3.40, P<.001).
Conclusions: Both the technology-facilitated care and supported care delivery models showed potential to improve 6-month depression and functional disability outcomes. The technology-facilitated care model has a greater likelihood to improve depression remission, patient satisfaction, and diabetes care quality.
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Details
- Title
- Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial
- Creators
- Shinyi Wu - University of Southern CaliforniaKathleen Ell - University of Southern CaliforniaHaomiao Jin - University of Southern CaliforniaIrene Vidyanti - Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.Chih-Ping Chou - University of Southern CaliforniaPey-Jiuan Lee - University of Southern CaliforniaSandra Gross-Schulman - Los Angeles County Department of Health ServicesLaura Myerchin Sklaroff - California State University, NorthridgeDavid Belson - Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.Arthur M. Nezu - Drexel UniversityJoel Hay - University of Southern CaliforniaChien-Ju Wang - Los Angeles County Department of Health ServicesGeoffrey Scheib - Los Angeles County Department of Health ServicesPaul Di Capua - FIU Herbert Wertheim College of MedicineCaitlin Hawkins - Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.Pai Liu - Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.Magaly Ramirez - Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.Brian W. Wu - University of Southern CaliforniaMark Richman - Long Island Jewish Medical CenterCaitlin Myers - Los Angeles County Department of Health ServicesDavin Agustines - Los Angeles County Department of Health ServicesRobert Dasher - Los Angeles County Department of Health ServicesAlex Kopelowicz - Los Angeles County Department of Health ServicesJoseph Allevato - Los Angeles County Department of Health ServicesMike Roybal - Los Angeles County Department of Health ServicesEli Ipp - UCLA Medical CenterUzma Haider - UCLA Medical CenterSharon Graham - Los Angeles County Department of Health ServicesVahid Mahabadi - Los Angeles County Department of Health ServicesJeffrey Guterman - University of California System
- Publication Details
- Journal of medical Internet research, v 20(4), pp e147-e147
- Publisher
- Jmir Publications, Inc
- Number of pages
- 18
- Grant note
- 1R18AE000054-01 / US Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000430956900001
- Scopus ID
- 2-s2.0-85047727478
- Other Identifier
- 991019169557304721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Health Care Sciences & Services
- Medical Informatics