A systematic review of the experience of treatment burden of digital health for military personnel in primary healthcare.

Paul Erhahiemen, Catherine A. O'Donnell,Katie Gallacher,Barbara I. Nicholl

Health Open Research(2024)

引用 0|浏览0
暂无评分
摘要
Background Digital Health (DH) integrates digital technologies into healthcare to increase efficiency and improve patient experiences, benefiting both primary care and military healthcare systems. However, it raises concerns about the potential shift of healthcare responsibilities onto patients, creating workloads or treatment burdens that affect care, adherence, equity, and resource allocation. It is critical to assess this in the military context to enhance patient-centred care and outcomes. Objective To understand military personnel’s experience of treatment burden of DH in primary care, to understand the barriers and facilitators of the use of DH, and to map barriers identified to the Burden of Treatment Theory (BOTT). Design A systematic literature review. MEDLINE, Psych INFO, EMBASE, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Google Scholar will be searched. Two independent reviewers will screen papers using inclusion and exclusion criteria, with conflicts decided by a third reviewer. Any retrieved study that meets the inclusion and exclusion criteria will be quality appraised using the appropriate Critical Appraisal Skills Programme (CASP) checklist. The findings will be analysed using thematic synthesis and evaluated in the context of the Burden of Treatment Theory. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA) guidelines have been adhered to in the production of this protocol. Conclusions Understanding the experience of treatment burden whilst using DH in the military has the potential to influence health policy, the commissioning of services and interventions, and most importantly, improve patient experience and health outcomes. PROSPERO registration number: CRD42023494297.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要