• Sara F Faqar-Uz-Zaman, Luxia Anantharajah, Philipp Baumartz, Paula Sobotta, Natalie Filmann, Dora Zmuc, Michael von Wagner, Charlotte Detemble, Svenja Sliwinski, Ursula Marschall, Wolf O Bechstein, and Andreas A Schnitzbauer.
• Department of General, Visceral, Transplant, and Thoracic Surgery, Frankfurt University Hospital, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany.
• Ann. Surg. 2022 Nov 1; 276 (5): 935-942.

ObjectiveTo evaluate the diagnostic accuracy of the app-based diagnostic tool Ada and the impact on patient outcome in the emergency room (ER).BackgroundArtificial intelligence-based diagnostic tools can improve targeted processes in health care delivery by integrating patient information with a medical knowledge base and a machine learning system, providing clinicians with differential diagnoses and recommendations.MethodsPatients presenting to the ER with abdominal pain self-assessed their symptoms using the Ada-App under supervision and were subsequently assessed by the ER physician. Diagnostic accuracy was evaluated by comparing the App-diagnoses with the final discharge diagnoses. Timing of diagnosis and time to treatment were correlated with complications, overall survival, and length of hospital stay.ResultsIn this prospective, double-blinded study, 450 patients were enrolled and followed up until day 90. Ada suggested the final discharge diagnosis in 52.0% (95% CI [0.47, 0.57]) of patients compared with the classic doctor-patient interaction, which was significantly superior with 80.9% (95% CI [0.77, 0.84], P <0.001). However, when diagnostic accuracy of both were assessed together, Ada significantly increased the accuracy rate (87.3%, P <0.001), when compared with the ER physician alone. Patients with an early time point of diagnosis and rapid treatment allocation exhibited significantly reduced complications ( P< 0.001) and length of hospital stay ( P< 0.001).ConclusionCurrently, the classic patient-physician interaction is superior to an AI-based diagnostic tool applied by patients. However, AI tools have the potential to additionally benefit the diagnostic efficacy of clinicians and improve quality of care.Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

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