Impacts of Symptom Checkers for Laypersons’ Self-diagnosis on Physicians in Primary Care: Scoping Review

Abstract

Background Symptom checkers (SCs) for laypersons’ self-assessment and preliminary self-diagnosis are widely used by the public. Little is known about the impact of these tools on health care professionals (HCPs) in primary care and their work. This is relevant to understanding how technological changes might affect the working world and how this is linked to work-related psychosocial demands and resources for HCPs. Objective This scoping review aimed to systematically explore the existing publications on the impacts of SCs on HCPs in primary care and to identify knowledge gaps. Methods We used the Arksey and O’Malley framework. We based our search string on the participant, concept, and context scheme and searched PubMed (MEDLINE) and CINAHL in January and June 2021. We performed a reference search in August 2021 and a manual search in November 2021. We included publications of peer-reviewed journals that focused on artificial intelligence- or algorithm-based self-diagnosing apps and tools for laypersons and had primary care or nonclinical settings as a relevant context. The characteristics of these studies were described numerically. We used thematic analysis to identify core themes. We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist to report the study. Results Of the 2729 publications identified through initial and follow-up database searches, 43 full texts were screened for eligibility, of which 9 were included. Further 8 publications were included through manual search. Two publications were excluded after receiving feedback in the peer-review process. Fifteen publications were included in the final sample, which comprised 5 (33%) commentaries or nonresearch publications, 3 (20%) literature reviews, and 7 (47%) research publications. The earliest publications stemmed from 2015. We identified 5 themes. The theme finding prediagnosis comprised the comparison between SCs and physicians. We identified the performance of the diagnosis and the relevance of human factors as topics. In the theme layperson-technology relationship, we identified potentials for laypersons’ empowerment and harm through SCs. Our analysis showed potential disruptions of the physician-patient relationship and uncontested roles of HCPs in the theme (impacts on) physician-patient relationship. In the theme impacts on HCPs’ tasks, we described the reduction or increase in HCPs’ workload. We identified potential transformations of HCPs’ work and impacts on the health care system in the theme future role of SCs in health care. Conclusions The scoping review approach was suitable for this new field of research. The heterogeneity of technologies and wordings was challenging. We identified research gaps in the literature regarding the impact of artificial intelligence– or algorithm-based self-diagnosing apps or tools on the work of HCPs in primary care. Further empirical studies on HCPs’ lived experiences are needed, as the current literature depicts expectations rather than empirical findings.

Beyond Rare Disease Patients: Exploring Machine Learning Interventions To Support People Experiencing a Diagnostic Odyssey

“…Moreover, patient-facing technology can provide an avenue for people with rare diseases to go if they lose faith in the healthcare system. The use of technology to research health information can prompt people to seek medical attention [52][53][54][55] and can provide support when patients feel that they have nowhere else to go [56]. However, while clinician-facing technology in this area has a clear aim, to aid diagnosis, the aim of technology for rare disease patients is far more ambiguous.…”

“…Online health information seeking may happen throughout the diagnostic odyssey, from potentially before contact with a clinician, to long after an initial consultation has taken place. The information-seeking behaviours, in addition to the utilisation of technologies which are not specifically designed for health, suggest that patients require further support in addition to that which is available during clinical consultations [55,124].…”