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

Design and Usability of Clinical Software and EHRs (268) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Safety and Error Prevention in Health (202) Focus Groups and Qualitative Research for Human Factors Research (852) Health Services Research (482) Clinical Informatics (1022)

Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29019, first published .
Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System–Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses

Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System–Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses

Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System–Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses

Authors of this article:

Emma K Jones1 Author Orcid Image ;   Alyssa Banks2 Author Orcid Image ;   Genevieve B Melton1 Author Orcid Image ;   Carolyn M Porta3 Author Orcid Image ;   Christopher J Tignanelli1, 4 Author Orcid Image
Article Authors Cited by (12) Tweetations (2) Metrics

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  2. Ingraham N, Jones E, King S, Dries J, Phillips M, Loftus T, Evans H, Melton G, Tignanelli C. Re-Aiming Equity Evaluation in Clinical Decision Support. Annals of Surgery 2023;277(3):359 View
  3. Lambert S, Madi M, Sopka S, Lenes A, Stange H, Buszello C, Stephan A. An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals. npj Digital Medicine 2023;6(1) View
  4. Yao Y, Dunn Lopez K, Bjarnadottir R, Macieira T, Dos Santos F, Madandola O, Cho H, Priola K, Wolf J, Wilkie D, Keenan G. Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses’ Graph Literacy: National, Web-Based Randomized Controlled Trial. Journal of Medical Internet Research 2023;25:e45043 View
  5. Jones E, Ninkovic I, Bahr M, Dodge S, Doering M, Martin D, Ottosen J, Allen T, Melton G, Tignanelli C. A novel, evidence-based, comprehensive clinical decision support system improves outcomes for patients with traumatic rib fractures. Journal of Trauma and Acute Care Surgery 2023;95(2):161 View
  6. Michel J, Manns A, Boudersa S, Jaubert C, Dupic L, Vivien B, Burgun A, Campeotto F, Tsopra R. Clinical decision support system in emergency telephone triage: A scoping review of technical design, implementation and evaluation. International Journal of Medical Informatics 2024;184:105347 View
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  8. Hu Z, Wang M, Zheng S, Xu X, Zhang Z, Ge Q, Li J, Yao Y. Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis Within the Frameworks of Knowledge and Practice: Survey Study. JMIR Human Factors 2024;11:e55802 View
  9. Klawunn R, Albrecht U, Katzmarzyk D, Dierks M. Beyond technology acceptance—a focused ethnography on the implementation, acceptance and use of new nursing technology in a German hospital. Frontiers in Digital Health 2024;6 View
  10. Nabelsi V, Lévesque-Chouinard A. Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians’ and Specialists’ Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study. JMIR Formative Research 2024;8:e52921 View
  11. Botha N, Ansah E, Segbedzi C, Dumahasi V, Maneen S, Kodom R, Tsedze I, Akoto L, Atsu F. Artificial intelligent tools: evidence-mapping on the perceived positive effects on patient-care and confidentiality. BMC Digital Health 2024;2(1) View