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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.
Wu, Shinyi; Ell, Kathleen; Jin, Haomiao; Vidyanti, Irene; Chou, Chih-Ping; Lee, Pey-Jiuan; Gross-Schulman, Sandra; Sklaroff, Laura Myerchin; Belson, David; Nezu, Arthur M; Hay, Joel; Wang, Chien-Ju; Scheib, Geoffrey; Di Capua, Paul; Hawkins, Caitlin; Liu, Pai; Ramirez, Magaly; Wu, Brian W; Richman, Mark; Myers, Caitlin; Agustines, Davin; Dasher, Robert; Kopelowicz, Alex; Allevato, Joseph; Roybal, Mike; Ipp, Eli; Haider, Uzma; Graham, Sharon; Mahabadi, Vahid; Guterman, Jeffrey.
Afiliação
  • Wu S; Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, United States.
  • Ell K; Roybal Institute on Aging, University of Southern California, Los Angeles, CA, United States.
  • Jin H; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Vidyanti I; Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, United States.
  • Chou CP; Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, United States.
  • Lee PJ; Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, United States.
  • Gross-Schulman S; Roybal Institute on Aging, University of Southern California, Los Angeles, CA, United States.
  • Sklaroff LM; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Belson D; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Nezu AM; Policy Analysis Unit, Los Angeles County Department of Public Health, Los Angeles, CA, United States.
  • Hay J; Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
  • Wang CJ; Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, United States.
  • Scheib G; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
  • Di Capua P; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
  • Hawkins C; College of Social and Behavioral Sciences, California State University, Northridge, Los Angeles, CA, United States.
  • Liu P; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Ramirez M; Department of Psychology, Drexel University, Philadelphia, PA, United States.
  • Wu BW; Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, United States.
  • Richman M; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
  • Myers C; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
  • Agustines D; Caremore Medical Group, East Haven, CT, United States.
  • Dasher R; Herbert Wertheim College of Medicine, Florida International University, Miami, FL, United States.
  • Kopelowicz A; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Allevato J; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Roybal M; Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
  • Ipp E; Department of Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, United States.
  • Haider U; Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
  • Graham S; Department of Emergency Medicine, Northwell Health Long Island Jewish Medical Center, New Hyde Park, NY, United States.
  • Mahabadi V; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
  • Guterman J; Los Angeles County Department of Health Services, Los Angeles, CA, United States.
J Med Internet Res ; 20(4): e147, 2018 04 23.
Article em En | MEDLINE | ID: mdl-29685872
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Atenção Primária à Saúde / Depressão / Diabetes Mellitus Tipo 2 Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Atenção Primária à Saúde / Depressão / Diabetes Mellitus Tipo 2 Tipo de estudo: Prognostic_studies / Qualitative_research / Risk_factors_studies Limite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos