Improving Equity of Access Through Electronic Consultation: A Case Study of an eConsult Service
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Bibliographic record
Abstract
Background: Patients with complex circumstances pertaining to geography, socioeconomic status, or functional health often face inequities in accessing care. Electronic consultation (eConsult) is a secure online application that allows primary care providers (PCPs) and specialists to communicate regarding a patient’s care. eConsult has demonstrated an ability to improve access to specialist care, and may be of particular use in cases of inequitable access. Methods: We examined how eConsult is used to improve equity of access for patients in complex circumstances by conducting a multiple case study of eConsults from seven patient groups: addiction, frail elderly, homeless, long-term care, rural, special needs, and transgender. Cases from these groups were selected from all eConsult cases completed between January 1 and December 31, 2017 using a data collection strategy tailored to each group. An access framework by Levesque et al. was applied to the data to examine five dimensions of access, arranged in chronological order, that reflect the process of a patient seeking care: approachability, acceptability; availability, affordability, and appropriateness. Two reviewers analyzed the cases using an iterative approach, regularly presenting findings to the research team for discussion and interpretation. Results: 825 cases emerged across the seven target groups. The selected cases highlighted a number of key factors, including the value of the patient-PCP relationship, the importance of considering patient perspectives when providing care, and efforts to accommodate patients facing particular challenges to accessing care. Examples emerged among all five dimensions of the Levesque et al. access framework, with the final dimension, appropriateness, emerging across all cases. Conclusions: By leveraging the eConsult platform, PCPs can help improve equitable access to specialist care. More research is needed to understand why patients with complex circumstances face a longer wait time compared to the general population, and the impact that eConsults can have in improving health outcomes and wait times for this population.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it