ArticleAnnals of family medicine
Evaluation of an Electronic Consultation Service for COVID-19 Care.
Article in Annals of family medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Family Physician-to-Hospital Specialist Electronic Consultation and Access to Hospital Care: A Systematic Review.JAMA network open · 2024Pooled it
- The Utilization of Electronic Consultations (eConsults) to Address Emerging Questions Related to Long COVID-19 in Ontario, Canada: Mixed Methods Analysis.JMIR human factors · 2025Article
- Article
- Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians' and Specialists' Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study.JMIR formative research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeCOVID-19 has increased the need for innovative virtual care solutions. Electronic consultation (eConsult) services allow primary care practitioners to pose clinical questions to specialists using a secure remote application. We examined eConsult cases submitted to a COVID-19 specialist group in order to assess usage patterns, impact on response times and referrals, and the content of clinical questions being asked.
methodsThis was a mixed-methods analysis of eConsult cases submitted between March and September 2020 in Ontario, Canada to 2 services. We performed a descriptive analysis of the average response time and the total time spent by the specialist for eConsults. Primary care practitioners completed a post-eConsult questionnaire that asked about the outcome of the eConsult. We performed an inductive and deductive content analysis of a subset of cases to identify common themes among the clinical questions asked.
resultsA total of 208 primary care practitioners submitted 289 eConsult cases. The median specialist response time was 0.6 days (range = 3 minutes to 15 days); the average time spent by specialists per case was 16 minutes (range = 5 to 59 minutes). In 69 cases (24%), the eConsult enabled avoidance of a face-to-face referral. Content analysis of 51 cases identified 5 major themes: precautions for high-risk and special populations, diagnostic clarification and/or need for COVID-19 testing, guidance on self-isolation and return to work, guidance on personal protective equipment, and management of chronic symptoms.
conclusionsThis study demonstrates the considerable potential of eConsults during a pandemic as our service was quickly implemented across Ontario and resulted in primary care practitioners' rapid and low-barrier access to specialist input.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.