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

Computerized History Taking (6) Registered Report (560) Symptom Checkers (31) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25493, first published .
Use of Self-Reported Computerized Medical History Taking for Acute Chest Pain in the Emergency Department – the Clinical Expert Operating System Chest Pain Danderyd Study (CLEOS-CPDS): Prospective Cohort Study

Use of Self-Reported Computerized Medical History Taking for Acute Chest Pain in the Emergency Department – the Clinical Expert Operating System Chest Pain Danderyd Study (CLEOS-CPDS): Prospective Cohort Study

Use of Self-Reported Computerized Medical History Taking for Acute Chest Pain in the Emergency Department – the Clinical Expert Operating System Chest Pain Danderyd Study (CLEOS-CPDS): Prospective Cohort Study

Authors of this article:

Helge Brandberg1 Author Orcid Image ;   Carl Johan Sundberg2, 3 Author Orcid Image ;   Jonas Spaak1 Author Orcid Image ;   Sabine Koch2 Author Orcid Image ;   David Zakim2 Author Orcid Image ;   Thomas Kahan1 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

Journals

  1. Kahan T. Decisions about antihypertensive treatment should focus on reducing cardiovascular risk. The Lancet 2021;397(10285):1598 View
  2. Sundberg K, Adeli A, Brandberg H, Spaak J, Koch S, Sundberg C, Zakim D, Kahan T, Fritzell K. User experience of self‐reported computerized medical history taking for acute chest pain: The Clinical Expert Operating System Chest Pain Danderyd Study. Health Expectations 2022;25(6):3053 View
  3. Zakim D, Brandberg H, El Amrani S, Hultgren A, Stathakarou N, Nifakos S, Kahan T, Spaak J, Koch S, Sundberg C, Bahl A. Computerized history-taking improves data quality for clinical decision-making—Comparison of EHR and computer-acquired history data in patients with chest pain. PLOS ONE 2021;16(9):e0257677 View
  4. Verma N, Lehmann H, Alam A, Yazdi Y, Acharya S. Development of a Digital Assistant to Support Teleconsultations Between Remote Physicians and Frontline Health Workers in India: User-Centered Design Approach. JMIR Human Factors 2023;10:e25361 View
  5. Kawamura R, Harada Y, Sugimoto S, Nagase Y, Katsukura S, Shimizu T. Incidence of Diagnostic Errors Among Unexpectedly Hospitalized Patients Using an Automated Medical History–Taking System With a Differential Diagnosis Generator: Retrospective Observational Study. JMIR Medical Informatics 2022;10(1):e35225 View
  6. Subbe C, Ahsan S, Smith L, Renggli J. An audible patient voice: How can we ensure that patients are treated as partners in their own safety?. Future Healthcare Journal 2021;8(3):e564 View
  7. Zhakhina G, Tapinova K, Kanabekova P, Kainazarov T. Pre-consultation history taking systems and their impact on modern practices: Advantages and limitations. Journal of Clinical Medicine of Kazakhstan 2023;20(6):26 View
  8. Verma N, Buch B, Pandya R, Taralekar R, Masand I, Rangparia H, Katira J, Acharya S. Evaluation and significance of a digital assistant for patient history-taking and physical examination in telemedicine. Oxford Open Digital Health 2024;2 View
  9. Brandberg H, Sundberg C, Spaak J, Koch S, Kahan T. Are medical history data fit for risk stratification of patients with chest pain in emergency care? Comparing data collected from patients using computerized history taking with data documented by physicians in the electronic health record in the CLEOS-CPDS prospective cohort study. Journal of the American Medical Informatics Association 2024;31(7):1529 View