National Healthcare Quality and Disparities Report
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedMeyer AND, Giardina TD, Spitzmueller C
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
This study examined patients’ experiences using an artificial intelligence (AI)-assisted online symptom checker and their doctors’ reactions to that use. From March 2 through March 15, 2018 an online survey was conducted of US users of the Isabel Symptom Checker within 6 months of their use. The majority of users were women, white, and had a mean age of 48. Overall, patients had a positive experience with the symptom checker and felt they would use it again (91.4%). About 48% discussed the findings with their physician and felt about 40% of their physicians were interested. Patients who had previously experienced diagnostic errors were more likely to use the symptom checker to determine if they should seek care.
AHRQ-funded; HS025474; HS027363.
Citation: Meyer AND, Giardina TD, Spitzmueller C .
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
J Med Internet Res 2020 Jan 30;22(1):e14679. doi: 10.2196/14679..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Diagnostic Safety and Quality, Patient Safety
Almario CV, Chey WD, Iriana S
Computer versus physician identification of gastrointestinal alarm features.
This study's objective was to compare the number of alarms documented by physicians during usual care vs. that collected by a computer algorithm called Automated Evaluation of Gastrointestinal Symptoms (AEGIS). AEGIS identified more patients with positive alarm features compared to physicians and also documented more positive alarms. Moreover, clinicians documented only 30% of the positive alarms self-reported by patients through AEGIS.
AHRQ-funded; HS000046.
Citation: Almario CV, Chey WD, Iriana S .
Computer versus physician identification of gastrointestinal alarm features.
Int J Med Inform 2015 Dec;84(12):1111-7. doi: 10.1016/j.ijmedinf.2015.07.006.
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Keywords: Clinical Decision Support (CDS), Diagnostic Safety and Quality, Digestive Disease and Health, Electronic Health Records (EHRs), Patient Safety