Dataset Information

A Remote Collaborative Care Program for Patients with Depression Living in Rural Areas: Open-Label Trial.

ABSTRACT:

Background

In the treatment of depression, primary care teams have an essential role, but they are most effective when inserted into a collaborative care model for disease management. In rural areas, the shortage of specialized mental health resources may hamper management of depressed patients.

Objective

The aim was to test the feasibility, acceptability, and effectiveness of a remote collaborative care program for patients with depression living in rural areas.

Methods

In a nonrandomized, open-label (blinded outcome assessor), two-arm clinical trial, physicians from 15 rural community hospitals recruited 250 patients aged 18 to 70 years with a major depressive episode (DSM-IV criteria). Patients were assigned to the remote collaborative care program (n=111) or to usual care (n=139). The remote collaborative care program used Web-based shared clinical records between rural primary care teams and a specialized/centralized mental health team, telephone monitoring of patients, and remote supervision by psychiatrists through the Web-based shared clinical records and/or telephone. Depressive symptoms, health-related quality of life, service use, and patient satisfaction were measured 3 and 6 months after baseline assessment.

Results

Six-month follow-up assessments were completed by 84.4% (221/250) of patients. The remote collaborative care program achieved higher user satisfaction (odds ratio [OR] 1.94, 95% CI 1.25-3.00) and better treatment adherence rates (OR 1.81, 95% CI 1.02-3.19) at 6 months compared to usual care. There were no statically significant differences in depressive symptoms between the remote collaborative care program and usual care. Significant differences between groups in favor of remote collaborative care program were observed at 3 months for mental health-related quality of life (beta 3.11, 95% CI 0.19-6.02).

Conclusions

Higher rates of treatment adherence in the remote collaborative care program suggest that technology-assisted interventions may help rural primary care teams in the management of depressive patients. Future cost-effectiveness studies are needed.

Trial registration

Clinicaltrials.gov NCT02200367; https://clinicaltrials.gov/ct2/show/NCT02200367 (Archived by WebCite at http://www.webcitation.org/6xtZ7OijZ).

SUBMITTER: Rojas G

PROVIDER: S-EPMC5952120 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Remote Collaborative Care Program for Patients with Depression Living in Rural Areas: Open-Label Trial.

Rojas Graciela G Guajardo Viviana V Martínez Pablo P Castro Ariel A Fritsch Rosemarie R Moessner Markus M Bauer Stephanie S

Journal of medical Internet research 20180430 4

<h4>Background</h4>In the treatment of depression, primary care teams have an essential role, but they are most effective when inserted into a collaborative care model for disease management. In rural areas, the shortage of specialized mental health resources may hamper management of depressed patients.<h4>Objective</h4>The aim was to test the feasibility, acceptability, and effectiveness of a remote collaborative care program for patients with depression living in rural areas.<h4>Methods</h4>In ...[more]

PMID: 29712627

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Project description:IntroductionSmoking rates among people living in rural and remote areas are higher and quit rates are lower over the past 10 years compared with people living in suburban and urban areas. Higher smoking rates contribute to greater tobacco-related disease and morbidity in rural and remote areas. Physical and social isolation, greater exposure to pro-tobacco marketing, pro-tobacco social norms, and lower socioeconomic and educational levels are contributing to these higher smoking rates and lower quit rates. Smoking cessation interventions for people in rural and remote areas have been conducted, however little is known about their effectiveness or their mechanisms of action as well as the quality of such research. Behaviour change techniques (BCTs) are mechanisms of action derived from behaviour change theory, such as goal setting and reward. Improved understanding of the contribution of BCTs for smoking cessation in the rural and remote population will support future intervention development. We aim to review the literature on smoking cessation interventions for people living in rural and remote areas to inform evidence about intervention effectiveness and mechanisms of action.Methods and analysisWe will conduct a systematic review using seven scientific databases (EMBASE, MedLine, PsycINFO, CINAHL, Cochrane, Informit Health and Scopus). We will include peer-reviewed journal articles published in English that examine a smoking cessation intervention delivered to people living in rural and remote areas in the USA, Canada and Australia. We will examine outcome data relating to intervention effectiveness (eg, point prevalence abstinence or continuous abstinence), as well as the BCTs used in included interventions and their relationship with intervention outcomes. We will also assess the feasibility, acceptability and quality of research interventions of included articles, and provide graded recommendations based on the review outcomes. Data will be synthesised using narrative approaches and interpreted using content analysis.Ethics and disseminationEthics was not required for this systematic review. The results will be disseminated through peer-reviewed publication and at conferences by presentations.Prospero registration number177398.

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Project description:ObjectiveTo understand existing care practices and policies, and potential enhancements, to improve the effectiveness of the US Department of Veterans Affairs (VA) Supportive Services for Veteran Families (SSVF) Health Care Navigators (HCN) in linking Veterans experiencing housing instability in rural areas with health care services.Data sources and study settingWe used primary data collected during semistructured interviews with HCNs (n = 21) serving rural areas across the United States during Spring 2022.Study designWe applied the Consolidated Framework for Implementation Research (CFIR) 2009 and the Social Ecological Model (SEM) to the collection and analysis of qualitative data to understand how HCNs administer services within SSVF and the larger community.Data collection/extraction methodsWe used rapid qualitative methods to summarize and analyze data. Templated matrix summaries identified facilitators and barriers to linking Veterans with health care services and policy and practice implications.Principal findingsUsing CFIR 2009, we identified contextual factors affecting successful implementation of HCN services within SSVF; we offer a crosswalk between CFIR 2009 and the version updated in 2022. Framing facilitators and barriers within the SEM provided insight into whether implementation strategies should be addressed at a community, interpersonal, or intrapersonal level within the SEM. Facilitators included sufficient knowledge, training, and mentorship opportunities for HCNs and their capacity to collaborate within their organization and with other community-based organizations. Barriers included lack of local technology and housing resources, inadequate understanding of Veterans' service eligibilities and pathways to access those services, and deficient collaboration with the VA.ConclusionsUnderstanding facilitators and barriers experienced by HCN when linking unstably housed Veterans in rural areas with health care services can inform future strategies, including policy changes such as increased training to support HCNs' understanding of eligibility, benefits, and entitlements as well as improving communication and collaboration between VA and community partners.

Dataset Information

A Remote Collaborative Care Program for Patients with Depression Living in Rural Areas: Open-Label Trial.

Background

Objective

Methods

Results

Conclusions

Trial registration

Publications

A Remote Collaborative Care Program for Patients with Depression Living in Rural Areas: Open-Label Trial.

Similar Datasets

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