The clinical and economic impact of a community-based, hybrid model of in-person and virtual care in a Canadian rural setting: A cross-sectional population-based comparative study
Bibliographic record
Abstract
ABSTRACT Objectives To determine the clinical and economic impact of a community-based, hybrid model of in-person and virtual care by comparing health-system performance of the rural jurisdiction where this model was implemented with neighbouring jurisdictions without such a model and the broader regional health system. Design A cross-sectional comparative study. Setting Ontario, Canada, with a focus on three largely rural public health units from April 1, 2018, until March 31, 2021. Participants All residents of Ontario, Canada under the age of 105 eligible for the Ontario Health Insurance Plan (OHIP) during the study period. Interventions An innovative, community-based, hybrid model of in-person and virtual care, the Virtual Triage and Assessment Centre (VTAC), was implemented in Renfrew County, Ontario on March 27, 2020. Main outcome measures Primary outcome was change in emergency department (ED) visits anywhere in Ontario, secondary outcomes included changes in hospitalizations and health-system costs, using percent changes in mean monthly values of linked health-system administrative data for two years pre-implementation and one year post-implementation. Results Renfrew County saw larger declines in ED visits (−34.4%, 95% confidence interval -41.9% to -26.0%) and hospitalizations (−11.1%, 95% confidence interval -19.7% to -1.5%), and slower growth in health-system costs than other rural regions studied. VTAC patients’ low-acuity ED visits decreased by -32.9%, high-acuity visits increased by 8.2%, and hospitalizations increased by 30.0%. Conclusion After implementing VTAC, Renfrew County saw reduced ED visits and hospitalizations and slower health-system cost growth compared to neighbouring rural jurisdictions. VTAC patients experienced reduced unnecessary ED visits and increased appropriate care. Community-based, hybrid models of in-person and virtual care may reduce the burden on emergency and hospital services in rural, remote and underserved regions. Further study is required to evaluate potential for scale and spread. Trial registration Not applicable. STRENGTHS AND LIMITATIONS OF THE STUDY This study uses population-level health administrative data to investigate the empirical effects of a community-based, hybrid model of in-person and virtual care in rural, remote, and underserved communities, where access to comprehensive primary care is insufficient. Population-level data from administrative datasets were linked using unique encoded identifiers and analyzed at ICES, Ontario’s population health data steward. The intervention jurisdiction is compared with two similar adjoining jurisdictions and with the whole Province. Because of the relatively short time period studied — two years before the intervention and one year post — it remains to be seen whether the observed differences will persist over time. This study’s design does not allow firm inferences about causality; however, the observed changes are in the right temporal sequence and benefit from local comparisons of similar jurisdictions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".