Evidence map›Paper›PMID 34852016›Full record

ArticlePloS one2021

Performance of a new symptom checker in patient triage: Canadian cohort study.

Forson Chan, Simon Lai, Marcus Pieterman, Lisa Richardson, Amanda Singh, Jocelynn Peters, Alex Toy, Caroline Piccininni, Taiysa Rouault, Kristie Wong and 3 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  10. Use of a Kiosk-Model Self-Triage System for COVID-19 Triage.Risk management and healthcare policy · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Forson ChanDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.ORCID 0000-0001-6116-6870
Simon LaiUniversity of British Columbia, Faculty of Medicine, Health Sciences Mall, Vancouver, Canada.
Marcus PietermanDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.ORCID 0000-0002-2929-9814
Lisa RichardsonDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
Amanda SinghDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
Jocelynn PetersDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
Alex ToyDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
Caroline PiccininniDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
Taiysa RouaultUniversity of British Columbia, Faculty of Medicine, Health Sciences Mall, Vancouver, Canada.
Kristie WongDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.
James K QuongWhitehorse General Hospital, Whitehorse, YT, Canada.
Adrienne T WakabayashiDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.ORCID 0000-0001-7018-5424
Anna Pawelec-BrzychczyDepartment of Family Medicine, Schulich School of Medicine and Dentistry, Western University, WCPHFM, London, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputerized algorithms known as symptom checkers aim to help patients decide what to do should they have a new medical concern. However, despite widespread implementation, most studies on symptom checkers have involved simulated patients. Only limited evidence currently exists about symptom checker safety or accuracy when used by real patients. We developed a new prototype symptom checker and assessed its safety and accuracy in a prospective cohort of patients presenting to primary care and emergency departments with new medical concerns.

methodA prospective cohort study was done to assess the prototype's performance. The cohort consisted of adult patients (≥16 years old) who presented to hospital emergency departments and family physician clinics. Primary outcomes were safety and accuracy of triage recommendations to seek hospital care, seek primary care, or manage symptoms at home.

resultsData from 281 hospital patients and 300 clinic patients were collected and analyzed. Sensitivity to emergencies was 100% (10/10 encounters). Sensitivity to urgencies was 90% (73/81) and 97% (34/35) for hospital and primary care patients, respectively. The prototype was significantly more accurate than patients at triage (73% versus 58%, p<0.01). Compliance with triage recommendations in this cohort using this iteration of the symptom checker would have reduced hospital visits by 55% but cause potential harm in 2-3% from delay in care.

interpretationThe prototype symptom checker was superior to patients in deciding the most appropriate treatment setting for medical issues. This symptom checker could reduce a significant number of unnecessary hospital visits, with accuracy and safety outcomes comparable to existing data on telephone triage.

Indexed as

AdolescentAdultAgedAged, 80 and overAlgorithmsCanadaCohort StudiesComputer SimulationData CollectionFemaleHospitalsHumansMaleMiddle AgedPrimary Health CareProspective Studies

Identifiers

PMID34852016
PMCPMC8635379

What OpenQuestion holds

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Registered trials

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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.