Virtual physician triage: impact on access and emergency department visits
Bibliographic record
Abstract
Background: The Virtual MD program was established in 2022 to enhance the appropriateness of nurse teletriage and divert low-acuity patients from the emergency department (ED). The program proved valuable during the peak of the Covid-19 pandemic as an alternate source of access, followed by continued use and expanding uptake in the year following. This study investigates the impact of the Virtual MD program on near-term emergency department visits. Who this is for: A subset of callers to the nurse health advice phone service, Health Link 811 who require more urgent but non-emergent consultation with a health care provider. Engagement/Involvement: Alberta Health Services' Health Link 811 program designed, implemented, and operates the Virtual MD program. It incorporates continuous input and guidance from physicians, nurses, healthcare administrators, allied health professionals, and patient representatives. Initiative: This study examined demographic profiles and immediate emergency department (ED) utilization within 7 days post-Virtual assessment among 21,171 patients directed to the Virtual MD program via the Health Link 811 nurse advice line from April 1st, 2022, to March 31st, 2023. Demographic characteristics including sex, age, rurality, clinical complexity, geographical measures of socio-economic status, prior history of ED utilization among Virtual MD patients were compared with the overall Alberta population as well as all callers to Health Link 811. Recommendations during the Virtual MD consult included: 1) call 911; 2) see primary care provider; 3) go to ED; 4) self-care/remain at home. Outcomes of interest included: 1) percentage of patients who were recommended to self-care who did not visit the ED; 2) percentage of patient who were recommended to attend ED who adhered to recommendations; and 3) and assessment of hospitalizations within 7 days for either outcome. Results/Impact: Results revealed that referral to the program followed similar distribution as the Alberta general population, demonstrating broad uptake across varied patient groups. Moderate differences were observed with respect to age and sex with Virtual MD referrals being slightly more common among younger and female patients, mirroring known trends in healthcare participation in general. 17% of Virtual MD patients lived in rural and remote areas. Preliminary findings suggest that Virtual MD reduces the overall proportion of callers advised to seek urgent in-person visits. Adherence outcomes post-referral and subsequent health care utilization will be completed early 2024. International Relevance: This study offers insights on a novel virtual program linking Health Link 811 callers to physicians via phone or video, aiming to decrease ED visits. These findings are valuable for global healthcare systems seeking timely, quality care and scaling similar programs. Next Steps: Future steps involve analyzing adherence, health care utilization data, and outcomes (e.g., hospitalization) following Virtual MD assessment.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".