Los Angeles Safety-Net Program eConsult System Was Rapidly Adopted And Decreased Wait Times To See Specialists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lack of timely access to specialty care is a significant problem among disadvantaged populations, such as those served by the Los Angeles County Department of Health Services. In 2012 the department implemented an electronic system for the provision of specialty care called the eConsult system, in which all requests from primary care providers for specialty assistance were reviewed by specialists. In many cases, the specialist can address the primary care provider's question via an electronic dialogue, thereby eliminating the need for the patient to see a specialist in person. We observed rapid growth in the use of eConsult: By 2015 the system was in use by over 3,000 primary care providers, and 12,082 consultations were taking place per month, compared to 86 in the third quarter of 2012. The median time to an electronic response from a specialist was one day, and 25 percent of eConsults were resolved without a specialist visit. Three to four years after implementation, the median time to a specialist appointment decreased significantly, while the volume of visits remained stable. eConsult systems are a promising and sustainable intervention that could improve access to specialist care for underserved patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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