Evaluation of an electronic consultation service in psychiatry for primary care providers
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
BACKGROUND: This study explores the effectiveness of an electronic consultation (eConsult) service between primary care providers and psychiatry, and the types and content of the clinical questions that were asked. METHODS: This is a retrospective eConsult review study. All eConsults directed to Psychiatry from July 2011 to January 2015 by Primary care providers were reviewed. Response time and the amount of time reported by the specialist to answer each eConsult was analyzed. Each eConsult was also categorized by clinical topic and question type in predetermined categories. Mandatory post-eConsult surveys for primary care providers were analyzed to determine the number of traditional consults avoided and to gain insight into the perceived value of eConsults. RESULTS: Of the 5597 eConsults, 169 psychiatry eConsults were completed during the study period. The average response time for a specialist to a primary care provider was 2.3 days. Eighty-seven percent of clinical responses were completed by the psychiatrist in less than 15 min. The primary care providers most commonly asked clinical questions were about depressive and anxiety disorders. 88.7% of PCPs rated the eConsult service a 5 (excellent value) or 4. CONCLUSIONS: This study indicates that an eConsult psychiatry service has tremendous potential to improve access to psychiatric advice and expand the capacity to treat mental illness in primary care. Future research may include follow-up with PCPs regarding the implementation of specialist advice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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