This paper is in the following e-collection/theme issue:

Symptom Checkers (32) Mobile Health (mhealth) (2972) Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (376) Consumer & Patient Education and Shared-Decision Making (688) Web-based and Mobile Health Interventions (3341) Evaluation and Research Methodology for mHealth (209) Clinical Information and Decision Making (1423) E-Health / Health Services Research and New Models of Care (538)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31810, first published .
Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation

Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation

Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation

Authors of this article:

Malte L Schmieding1 Author Orcid Image ;   Marvin Kopka1, 2 Author Orcid Image ;   Konrad Schmidt3, 4 Author Orcid Image ;   Sven Schulz-Niethammer5 Author Orcid Image ;   Felix Balzer1 Author Orcid Image ;   Markus A Feufel5 Author Orcid Image
Article Authors Cited by (46) Tweetations (8) Metrics

Journals

  1. Kopka M, Schmieding M, Rieger T, Roesler E, Balzer F, Feufel M. Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial. JMIR Human Factors 2022;9(2):e35219 View
  2. Kopka M, Feufel M, Balzer F, Schmieding M. The Triage Capability of Laypersons: Retrospective Exploratory Analysis. JMIR Formative Research 2022;6(10):e38977 View
  3. Hirosawa T, Harada Y, Yokose M, Sakamoto T, Kawamura R, Shimizu T. Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints: A Pilot Study. International Journal of Environmental Research and Public Health 2023;20(4):3378 View
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  5. Napierala H, Kopka M, Altendorf M, Bolanaki M, Schmidt K, Piper S, Heintze C, Möckel M, Balzer F, Slagman A, Schmieding M. Examining the impact of a symptom assessment application on patient-physician interaction among self-referred walk-in patients in the emergency department (AKUSYM): study protocol for a multi-center, randomized controlled, parallel-group superiority trial. Trials 2022;23(1) View
  6. Painter A, Hayhoe B, Riboli-Sasco E, El-Osta A. Online Symptom Checkers: Recommendations for a Vignette-Based Clinical Evaluation Standard. Journal of Medical Internet Research 2022;24(10):e37408 View
  7. Fraser H, Cohan G, Koehler C, Anderson J, Lawrence A, Pateña J, Bacher I, Ranney M. Evaluation of Diagnostic and Triage Accuracy and Usability of a Symptom Checker in an Emergency Department: Observational Study. JMIR mHealth and uHealth 2022;10(9):e38364 View
  8. Pairon A, Philips H, Verhoeven V. A scoping review on the use and usefulness of online symptom checkers and triage systems: How to proceed?. Frontiers in Medicine 2023;9 View
  9. Kopka M, Scatturin L, Napierala H, Fürstenau D, Feufel M, Balzer F, Schmieding M. Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e46231 View
  10. North F, Jensen T, Stroebel R, Nelson E, Johnson B, Thompson M, Pecina J, Crum B. Self-Triage Use, Subsequent Healthcare Utilization, and Diagnoses: A Retrospective Study of Process and Clinical Outcomes Following Self-Triage and Self-Scheduling for Ear or Hearing Symptoms. Health Services Research and Managerial Epidemiology 2023;10 View
  11. Kafke S, Kuhlmey A, Schuster J, Blüher S, Czimmeck C, Zoellick J, Grosse P. Can clinical decision support systems be an asset in medical education? An experimental approach. BMC Medical Education 2023;23(1) View
  12. Fraser H, Crossland D, Bacher I, Ranney M, Madsen T, Hilliard R. Comparison of Diagnostic and Triage Accuracy of Ada Health and WebMD Symptom Checkers, ChatGPT, and Physicians for Patients in an Emergency Department: Clinical Data Analysis Study. JMIR mHealth and uHealth 2023;11:e49995 View
  13. Chenais G, Lagarde E, Gil-Jardiné C. Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges. Journal of Medical Internet Research 2023;25:e40031 View
  14. Wiedermann C, Mahlknecht A, Piccoliori G, Engl A. Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools. Journal of Personalized Medicine 2023;13(9):1379 View
  15. de Koning E, van der Haas Y, Saguna S, Stoop E, Bosch J, Beeres S, Schalij M, Boogers M. AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study. JMIR Cardio 2023;7:e51375 View
  16. Hirosawa T, Mizuta K, Harada Y, Shimizu T. Comparative Evaluation of Diagnostic Accuracy Between Google Bard and Physicians. The American Journal of Medicine 2023;136(11):1119 View
  17. Määttä J, Lindell R, Hayward N, Martikainen S, Honkanen K, Inkala M, Hirvonen P, Martikainen T. Diagnostic Performance, Triage Safety, and Usability of a Clinical Decision Support System Within a University Hospital Emergency Department: Algorithm Performance and Usability Study. JMIR Medical Informatics 2023;11:e46760 View
  18. Mahlknecht A, Engl A, Piccoliori G, Wiedermann C. Supporting primary care through symptom checking artificial intelligence: a study of patient and physician attitudes in Italian general practice. BMC Primary Care 2023;24(1) View
  19. Drapkina O, Nedogoda S, Bolotova S, Lavrenova E, Tsoma V, Ledyaeva A, Chumachek E, Barykina I, Salasyuk A, Lutova V, Popova E. Symptom-oriented diagnostics as an important element in improving the quality of medical care. Profilakticheskaya meditsina 2023;26(9):7 View
  20. Kopka M, Feufel M, Berner E, Schmieding M. How suitable are clinical vignettes for the evaluation of symptom checker apps? A test theoretical perspective. DIGITAL HEALTH 2023;9 View
  21. Hirosawa T, Kawamura R, Harada Y, Mizuta K, Tokumasu K, Kaji Y, Suzuki T, Shimizu T. ChatGPT-Generated Differential Diagnosis Lists for Complex Case–Derived Clinical Vignettes: Diagnostic Accuracy Evaluation. JMIR Medical Informatics 2023;11:e48808 View
  22. Liu V, Koskela T, Kaila M. User-Initiated Symptom Assessment With an Electronic Symptom Checker: Protocol for a Mixed Methods Validation Study. JMIR Research Protocols 2023;12:e41423 View
  23. Bushuven S, Bentele M, Bentele S, Gerber B, Bansbach J, Ganter J, Trifunovic-Koenig M, Ranisch R. “ChatGPT, Can You Help Me Save My Child’s Life?” - Diagnostic Accuracy and Supportive Capabilities to Lay Rescuers by ChatGPT in Prehospital Basic Life Support and Paediatric Advanced Life Support Cases – An In-silico Analysis. Journal of Medical Systems 2023;47(1) View
  24. Schnoor K, Versluis A, Chavannes N, Talboom-Kamp E. Digital Triage Tools for Sexually Transmitted Infection Testing Compared With General Practitioners’ Advice: Vignette-Based Qualitative Study With Interviews Among General Practitioners. JMIR Human Factors 2024;11:e49221 View
  25. Peven K, Wickham A, Wilks O, Kaplan Y, Marhol A, Ahmed S, Bamford R, Cunningham A, Prentice C, Meczner A, Fenech M, Gilbert S, Klepchukova A, Ponzo S, Zhaunova L. Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study. JMIR mHealth and uHealth 2023;11:e46718 View
  26. Chanif C, Nursalam N, Sriyono S, Yuniasari L, Pranata S, Armiyati Y. The correlation between nurses' knowledge of triage and the accuracy of triage level interpretation in the emergency department. Scripta Medica 2023;54(4):385 View
  27. Kearney L, Jansen E, Kathuria H, Steiling K, Jones K, Walkey A, Cordella N. Efficacy of Digital Outreach Strategies for Collecting Smoking Data: Pragmatic Randomized Trial. JMIR Formative Research 2024;8:e50465 View
  28. Müller R, Klemmt M, Koch R, Ehni H, Henking T, Langmann E, Wiesing U, Ranisch R. “That’s just Future Medicine” - a qualitative study on users’ experiences of symptom checker apps. BMC Medical Ethics 2024;25(1) View
  29. Wetzel A, Koch R, Koch N, Klemmt M, Müller R, Preiser C, Rieger M, Rösel I, Ranisch R, Ehni H, Joos S. ‘Better see a doctor?’ Status quo of symptom checker apps in Germany: A cross-sectional survey with a mixed-methods design (CHECK.APP). DIGITAL HEALTH 2024;10 View
  30. Kachman M, Brennan I, Oskvarek J, Waseem T, Pines J. How artificial intelligence could transform emergency care. The American Journal of Emergency Medicine 2024;81:40 View
  31. Meczner A, Cohen N, Qureshi A, Reza M, Sutaria S, Blount E, Bagyura Z, Malak T. Controlling Inputter Variability in Vignette Studies Assessing Web-Based Symptom Checkers: Evaluation of Current Practice and Recommendations for Isolated Accuracy Metrics. JMIR Formative Research 2024;8:e49907 View
  32. Harada Y, Sakamoto T, Sugimoto S, Shimizu T. Longitudinal Changes in Diagnostic Accuracy of a Differential Diagnosis List Developed by an AI-Based Symptom Checker: Retrospective Observational Study. JMIR Formative Research 2024;8:e53985 View
  33. Petrella R. The AI Future of Emergency Medicine. Annals of Emergency Medicine 2024;84(2):139 View
  34. Liu V, Kaila M, Koskela T. Triage Accuracy and the Safety of User-Initiated Symptom Assessment With an Electronic Symptom Checker in a Real-Life Setting: Instrument Validation Study. JMIR Human Factors 2024;11:e55099 View
  35. Kopka M, Feufel M. Software symptomcheckR: an R package for analyzing and visualizing symptom checker triage performance. BMC Digital Health 2024;2(1) View
  36. Hirosawa T, Harada Y, Mizuta K, Sakamoto T, Tokumasu K, Shimizu T. Diagnostic performance of generative artificial intelligences for a series of complex case reports. DIGITAL HEALTH 2024;10 View
  37. Hirosawa T, Harada Y, Tokumasu K, Ito T, Suzuki T, Shimizu T. Comparative Study to Evaluate the Accuracy of Differential Diagnosis Lists Generated by Gemini Advanced, Gemini, and Bard for a Case Report Series Analysis: Cross-Sectional Study. JMIR Medical Informatics 2024;12:e63010 View
  38. Shah-Mohammadi F, Finkelstein J. Accuracy Evaluation of GPT-Assisted Differential Diagnosis in Emergency Department. Diagnostics 2024;14(16):1779 View
  39. North F, Buss R, Nelson E, Thompson M, Pecina J, Crum B. Patient Opportunities to Self-Schedule in a Large Multisite, Multispecialty Medical Practice: Program Description and Uptake of 7 Unique Processes for Patients to Successfully Self-Schedule (and Reschedule) Their Medical Appointments. Health Services Research and Managerial Epidemiology 2024;11 View
  40. de Arriba-Pérez F, García-Méndez S. Leveraging large language models through natural language processing to provide interpretable machine learning predictions of mental deterioration in real time. Arabian Journal for Science and Engineering 2024 View
  41. Wetzel A, Preiser C, Müller R, Joos S, Koch R, Henking T, Haumann H. Unveiling Usage Patterns and Explaining Usage of Symptom Checker Apps: Explorative Longitudinal Mixed Methods Study. Journal of Medical Internet Research 2024;26:e55161 View
  42. Kopka M, Feufel M. Statistical refinement of patient-centered case vignettes for digital health research. Frontiers in Digital Health 2024;6 View

Books/Policy Documents

  1. Milligan J. Degenerative Cervical Myelopathy. View