Understanding Ontario eConsult Utilization in Rural vs. Urban Settings
Bibliographic record
Abstract
<h3>Context:</h3> Accessing specialty medical services in rural Ontario is a longstanding issue. Numerous barriers, including a scarcity of local specialist offices and excess travel times to urban centres, results in inequitable access to care for rural patients and can negatively impact health outcomes. <h3>Objective:</h3> To determine the proportion of rural vs. urban eConsults in each Ontario Health (OH) Region as well as the number of providers, specialty distribution, response interval, time billed, and results from a close-out survey. <h3>Study Design and Analysis:</h3> Retrospective, cross-sectional descriptive analysis. <h3>Setting or Dataset:</h3> Ontario, Canada. Population Studied: 72,948 eConsults submitted through Ontario eConsult Service (OES) between January 01 – December 31, 2021 were included. <h3>Intervention/Instrument:</h3> The OES allows clinicians to securely access asynchronous specialist advice in Ontario through the Ontario Telemedicine Network. <h3>Outcome Measures:</h3> The proportion of rural vs. urban eConsults in OH regions were identified using the forward sortation area (FSW) of the primary organization for each requesting provider. FSWs with 0 as the second character were identified as rural and values 1-9 were identified as urban. <h3>Results:</h3> 10% (n=7550) of eConsults were submitted by 591 providers with a rural FSW. 1.74 eConsults per 1000 residents were sent by rural providers in OH North and 0.98, 0.62, 0.05 and 0.0 per 1000 residents in OH Regions West, East, Central and Toronto respectively. The top four specialties for both rural and urban eConsults were Dermatology, Obstetrics/Gynecology, Hematology & Allergy/Clinical Immunology. For both rural and urban eConsults, the median specialist response time was 1.0 days and the median specialist time spent was 15 minutes. In 76% of rural eConsults, specialist appointments were avoided vs. 75% in urban. In 58% of rural eConsults, providers indicated that they received good advice for a new/additional course of action vs. 54% in urban cases. <h3>Conclusions:</h3> Rural and urban eConsults had similar results for specialty distribution, time spent, response interval and survey results. The OES is successfully improving equity of access in rural Ontario across different health regions. Further research should determine clinical content and types of questions that are being asked by rural vs. urban providers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".