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Currently submitted to: Journal of Medical Internet Research

Date Submitted: May 12, 2019
Open Peer Review Period: May 15, 2019 - Jul 10, 2019
(currently open for review and needs more reviewers - can you help?)

Patient Perspectives on Usefulness of an Artificial Intelligence Assisted Symptom-Checker: A Cross-Sectional Survey Study

  • Ashley Meyer; 
  • Traber Giardina; 
  • Christiane Spitzmueller; 
  • Hardeep Singh

ABSTRACT

Background:

Patients increasingly seek online symptom-checkers to obtain diagnoses. Little is known, however, about characteristics of patients who use these resources, their rationale for use, and whether patients find them accurate and useful.

Objective:

To examine patients’ experiences using an artificial intelligence (AI) assisted online symptom-checker.

Methods:

An online survey was administered to US users of Isabel Symptom Checker within 6 months of their use and occurring from March 2, 2018 through March 15, 2018. User characteristics, experiences of symptom-checker use, experiences discussing results with physicians, and prior personal history of experiencing a diagnostic error were collected.

Results:

329 usable/complete responses were obtained. Mean respondent age was 48.0 years (SD=16.7); most were women (n=230;75.7%) and white/Caucasian (n=271;89.1%). Patients used the symptom-checker to better understand their symptoms’ causes (n=232;76.3%), decide whether to seek care (n=101;33.2%) or where (e.g., primary or urgent care; n=63;20.7%), get medical advice without going to a doctor (n=48;15.8%), or better understand their diagnosis (n=39;12.8%). Most reported receiving useful information for their health problems (n=274;83.3%), with half reporting positive health effects (n=154;50.9%). Most perceived it to be useful as a diagnostic tool (n=253;76.9%), as providing insights leading them closer to correct diagnoses (n=231;70.2%), and reported they would use it again (n=278;84.5%). Patients who discussed findings with their physicians (n=103) sometimes felt physicians were disinterested (n=24;23.3%) and not open to discussing the tool’s results (n=21;20.4%). Patients who previously experienced diagnostic errors (missed or delayed diagnoses; n=181;55.0%) were more likely to use the symptom-checker to determine if they should seek care (26.5% vs 12.2%;p=.002), but more often felt physicians were disinterested in discussing the tool’s results (30.4% vs 8.8%;p=.04) than patients who had not previously experienced diagnostic errors.

Conclusions:

Despite ongoing concerns about symptom-checker accuracy, a large patient-user group perceived an AI assisted symptom-checker as useful for diagnosis. Formal validation studies evaluating symptom-checker accuracy and effectiveness in real-world practice could provide additional useful information about their benefit.


 Citation

Please cite as:

Meyer A, Giardina T, Spitzmueller C, Singh H

Patient Perspectives on Usefulness of an Artificial Intelligence Assisted Symptom-Checker: A Cross-Sectional Survey Study

JMIR Preprints. 12/05/2019:14679

DOI: 10.2196/preprints.14679

URL: https://preprints.jmir.org/preprint/14679

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