Advancing Regional and Remote Health Care With Virtual Hospital Implementation: Rapid Review
Bibliographic record
Abstract
BACKGROUND: Disparities in health equity between metropolitan and rural areas are a global concern, especially in vast countries such as Australia, Canada, and the United States. Virtual care models in health care settings are promising in reducing inequalities, with virtual hospitals (VHs) potentially bridging the gap for isolated or underserved regions. However, evidence-based strategies and the complexities of VH implementation necessitate further research. OBJECTIVE: This rapid review aims to examine the role of VHs in enhancing regional and remote health care by focusing on accessibility, patient and health care provider experiences, and implementation barriers and facilitators. It provides tailored recommendations for large-scale implementation in communities with access issues, contributing to the discussion on equitable health care. METHODS: A rapid review was conducted in accordance with the World Health Organization guidelines. A systematic search was performed across PubMed, MEDLINE, CINAHL, and the La Trobe University Library for peer-reviewed articles published between January 2015 and March 2023. Additional gray literature was identified through Google searches and snowballing from relevant web articles. Studies were included if they focused on regional or remote populations and addressed VHs or virtual care. Studies that solely discussed hybrid models of care were excluded. Data were systematically extracted using a customized Microsoft Excel template. A mixed methods thematic analysis was conducted to identify recurring themes, barriers, facilitators, and recommendations related to VH implementation as well as patterns in clinical outcomes and stakeholder perspectives. RESULTS: A total of 35 articles were included in this review, comprising 23 (66%) peer-reviewed studies and 12 (34%) gray literature sources. Positive clinical outcomes were reported in 9 (26%) articles, highlighting outcomes such as reduced disease transmission, improved patient safety, fewer admissions and readmissions, lower mortality, shorter hospital stays, and better adherence to clinical best practices. Health system outcomes were identified in 15 (43%) articles, including reduced costs, enhanced patient experience and safety, improved care delivery and health care provider support, greater efficiency, broader geographic coverage, and better integration of services. Patient and health care provider perspectives were discussed in 12 (34%) articles, with positive views attributed to convenience, time and cost savings, and improved service quality. Barriers and facilitators were the most frequently discussed themes, appearing in 27 (77%) and 26 (74%) articles, respectively, with challenges and enablers commonly linked to people, processes, technology, and financial sustainability. CONCLUSIONS: VHs have the potential to revolutionize regional and remote health care by overcoming barriers, using facilitators, and following recommended practices, leading to better clinical outcomes and increased satisfaction for patients and health care providers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".