Optimizing Electronic Consultation Between Primary Care Providers and Psychiatrists: Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: The use of electronic consultation (e-consult) between primary care providers (PCPs) and psychiatrists has potential, given the high prevalence of mental health issues in primary care and problematic access to specialist care. Utilization and uptake, however, appears to be lower than would be expected. OBJECTIVE: This study aimed to examine actual utilization of e-consult between PCPs and psychiatrists and investigate the perceptions of PCPs about this form of psychiatric advice to inform how to optimize the utility and thereby the uptake of this service. METHODS: In this mixed-methods study, we conducted a chart review of psychiatry e-consults (N=37) over 2 platforms during early implementation in Ontario, Canada, as well as 3 group interviews and 1 individual interview with PCPs (N=10) with variable experience levels and from a range of practice settings. The chart review assessed response times and referral content including the type of request, referral attachments, and consultant responses. Interviews explored the perceptions of the PCPs about the uses and barriers of psychiatry e-consult. Thematic content analysis of interview data identified common themes as well as themes unique to different provider profiles (eg, experienced PCPs vs new PCPs and rural vs urban practice). On the basis of interpretation of the quantitative and qualitative findings, we developed recommendations for the optimization of psychiatry e-consultation services. RESULTS: During the study period, psychiatry e-consults comprised 3.66% (49/1339) of all e-consults submitted on the studied platforms. Among the e-consults reviewed, different psychiatric diagnoses were represented: 70% of requests (26/37) queried about medication safety or side effects, whereas 59% (22/37) asked about psychiatric symptom management. Moreover, 81% (30/37) of e-consults were answered within 24 hours, and 65% (24/37) were addressed in a single exchange. Themes from the interview data included psychiatry having a complexity that differentiates it from other specialties and may limit the utility of e-consult, other than for psychopharmacology advice. Variability in awareness exists in the way e-consultation could be used in psychiatry, with new PCPs feeling unsure about the appropriateness of a question. In general, new PCPs and PCPs practicing in rural areas were more receptive to psychiatry e-consult. PCPs viewed e-consult as an opportunity to collaborate and desired that it be integrated with other available services. Recommendations include the need for appropriate specialist staffing to address a wide range of requests, adequate education to referrers regarding the use of psychiatry e-consult, and the need to integrate psychiatry e-consult with other geographically relevant services, given the complexity of psychiatric issues. CONCLUSIONS: E-consult is a viable and timely way for PCPs to get much-needed psychiatric advice. For optimizing its utility and uptake, e-consult needs to be integrated into reliable care pathways with adequate referrer and consultant preparation.
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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 | 0.033 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".