eConsultations to Infectious Disease Specialists: Questions Asked and Impact on Primary Care Providers' Behavior
Bibliographic record
Abstract
Background. Since 2010, the Champlain BASE (Building Access to Specialist Advice through eConsultation) service has allowed primary care providers (PCPs) to submit patient specific clinical questions to specialists through a secure web service. By facilitating communication between PCPs directly with specialists, eConsults can reduce the need for face-to-face consultations in a secure platform. The study objectives are to describe questions asked to infectious diseases specialists through eConsultation and assess eConsultation's impact on physician behaviors. Methods. eConsults completed through the Champlain BASE service from 15 April 15 2013 to 31 January 2015 were characterized based on the type of question asked and infectious disease content. Usage data and PCP responses to a mandatory closeout survey were analyzed to determine eConsult response times, change in need for a face-to-face consultation, and change in planned course of action. Results. Of the 224 infectious diseases eConsults, the most common types of questions were: interpretation of a clinical test 18.0% (41), general management 16.5 % (37), and indications/goals of treating a particular condition 16.5% (37). The most frequently consulted areas of infectious disease content were: tuberculosis 14.3% (32), Lyme disease 14.3% (32), and parasite questions not otherwise specified 12.9% (29). PCPs received their answer within 24 hours in 63% of cases and 82% of cases took the specialist less than 15 minutes to complete. In 32% of cases a face-to- face referral was originally planned by the PCP, but was no longer needed. In 7.8% of cases, the PCP was not originally planning to refer the patient, but did so after the eConsult. In 55% of cases, the PCP either received new information or changed their course of action. Conclusion. Through the use of an eConsult service, PCPs receive timely access to infectious disease specialists' advice that often results in a change in plans for a face-to-face referral. Disclosures. All authors: No reported disclosures.
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.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".