Challenges and Strategies for Promoting Health Equity in Virtual Care: Protocol for a Scoping Review of Reviews (Preprint)
Bibliographic record
Abstract
BACKGROUND The rapid virtualization of health services during the COVID-19 pandemic has drawn increasing attention to the impact of virtual care technologies on health equity. In some circumstances, virtual care initiatives have been shown to increase health disparities, as individuals from underserved communities are less likely to benefit from such initiatives. OBJECTIVE The purpose of this paper is to describe a protocol for a scoping review of reviews that aims to map review-level evidence that describes challenges and strategies for promoting effective engagement with virtual care technologies among underserved communities. METHODS Our methodology was adapted from seminal scoping review guidelines provided by Arksey and O’Malley, Levac at al, Colquhoun et al, and the Joanna Briggs Institute. Our search strategy was developed for the following databases: MEDLINE (on Ovid), EMBASE (on Ovid), CINAHL (on EBSCO), Scopus, and Epistemonikos. Supplementary searches will include the use of Google Scholar and reference tracking. Each citation will be independently screened by 2 researchers at the title and abstract level, and full-text screening will be performed in accordance with our eligibility criteria. The eligibility criteria focused on the inclusion of methods-driven reviews (ie, systematic reviews, scoping reviews, meta-analyses, realist reviews, and critical interpretative syntheses) to enhance rigor and quality. Other inclusion criteria included a focus on virtual care services that facilitate bidirectional patient-provider communication (ie, video, telephone, and asynchronous messaging visits) for underserved populations (ie, those who experience social disadvantage due to race, age, income, and other factors related to the social determinants of health). RESULTS This scoping review of reviews will provide a broad overview of identified challenges associated with the accessibility of virtual health care services among underserved communities. In addition, strategies for improving the access to, uptake of, and engagement with virtual care technologies among underserved communities will be identified. The knowledge synthesized from this review will aid in developing and implementing virtual services that acknowledge the unique needs of populations who experience barriers to care and disproportionately worse health outcomes. The results will also inform gaps in current research. CONCLUSIONS The rapid shift toward virtual health services has highlighted the urgent need to critically examine the intersection of virtual care and health equity. Although technology-driven innovations in health care generally aim to improve access, quality, and health outcomes, it is also possible for these innovations to produce intervention-generated inequities. Assessing current review-level evidence on the key challenges and strategies for improving the application of virtual care in underserved communities is imperative for ensuring that virtual care benefits all populations. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/22847
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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 | 0.152 | 0.187 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.020 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.108 | 0.025 |
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".