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- Title
Evaluating the diagnostic and triage performance of digital and online symptom checkers for the presentation of myocardial infarction; A retrospective cross-sectional study.
- Authors
Wallace, William; Chan, Calvin; Chidambaram, Swathikan; Hanna, Lydia; Acharya, Amish; Daniels, Elisabeth; Normahani, Pasha; Matin, Rubeta N.; Markar, Sheraz R.; Sounderajah, Viknesh; Liu, Xiaoxuan; Darzi, Ara
- Abstract
Online symptom checkers are increasingly popular health technologies that enable patients to input their symptoms to produce diagnoses and triage advice. However, there is concern regarding the performance and safety of symptom checkers in diagnosing and triaging patients with life-threatening conditions. This retrospective cross-sectional study aimed to evaluate and compare commercially available symptom checkers for performance in diagnosing and triaging myocardial infarctions (MI). Symptoms and biodata of MI patients were inputted into 8 symptom checkers identified through a systematic search. Anonymised clinical data of 100 consecutive MI patients were collected from a tertiary coronary intervention centre between 1st January 2020 to 31st December 2020. Outcomes included (1) diagnostic sensitivity as defined by symptom checkers outputting MI as the primary diagnosis (D1), or one of the top three (D3), or top five diagnoses (D5); and (2) triage sensitivity as defined by symptom checkers outputting urgent treatment recommendations. Overall D1 sensitivity was 48±31% and varied between symptom checkers (range: 6–85%). Overall D3 and D5 sensitivity were 73±20% (34–92%) and 79±14% (63–94%), respectively. Overall triage sensitivity was 83±13% (55–91%). 24±16% of atypical cases had a correct D1 though for female atypical cases D1 sensitivity was only 10%. Atypical MI D3 and D5 sensitivity were 44±21% and 48±24% respectively and were significantly lower than typical MI cases (p<0.01). Atypical MI triage sensitivity was significantly lower than typical cases (53±20% versus 84±15%, p<0.01). Female atypical cases had significantly lower diagnostic and triage sensitivity than typical female MI cases (p<0.01).Given the severity of the pathology, the diagnostic performance of symptom checkers for correctly diagnosing an MI is concerningly low. Moreover, there is considerable inter-symptom checker performance variation. Patients presenting with atypical symptoms were under-diagnosed and under-triaged, especially if female. This study highlights the need for improved clinical performance, equity and transparency associated with these technologies. Author summary: Online symptom checkers are increasingly popular tools that patients turn to in order to understand their symptoms, self-diagnose and ultimately seek further medical attention. We wanted to evaluate how accurately different commercially available symptom checkers are able to diagnose a severe medical condition (myocardial infarction) and give appropriate medical advice (i.e., seek immediate medical assistance). In this study, we collected anonymous clinical data of 100 people who had confirmed myocardial infarctions. Their presenting symptoms and biodata (e.g., age, sex, co-morbidities) were inputted into the eight most popular commercially available symptom checkers found through a Google and an App Store search. We found that the performance of the online symptom checkers for correctly diagnosing a myocardial infarction was low, especially given the severity of the disease. Additionally, there was considerable variability in performance between different symptom checkers. Finally, we found that patients with atypical presenting symptoms were less likely to be diagnosed and given correct medical advice, especially if female. Our study highlights the need for better clinical performance, equality and transparency of online symptom checkers.
- Subjects
UNITED Kingdom; MYOCARDIAL infarction diagnosis; CROSS-sectional method; MYOCARDIAL infarction; INTERNET searching; PEARSON correlation (Statistics); COMPUTER software; STATISTICAL hypothesis testing; T-test (Statistics); OUTPATIENT medical care; SEX distribution; HEALTH; RETROSPECTIVE studies; TERTIARY care; DESCRIPTIVE statistics; SEVERITY of illness index; DIAGNOSTIC errors; AGE distribution; INFORMATION resources; CHI-squared test; ELECTRONIC health records; CASE studies; DATA analysis software; MEDICAL triage; SENSITIVITY &; specificity (Statistics); ST elevation myocardial infarction; SYMPTOMS
- Publication
PLoS Digital Health, 2024, Vol 3, Issue 8, p1
- ISSN
2767-3170
- Publication type
Article
- DOI
10.1371/journal.pdig.0000558