Published on in Vol 8, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17283, first published .
Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review

Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review

Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review

Authors of this article:

Clemens Scott Kruse1 Author Orcid Image ;   Nolan Ehrbar1 Author Orcid Image

Journals

  1. Poly T, Islam M, Muhtar M, Yang H, Nguyen P, Li Y. Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication–Related Clinical Decision Support System: Model Development and Validation. JMIR Medical Informatics 2020;8(11):e19489 View
  2. ten Broeke A, Hulscher J, Heyning N, Kooi E, Chorus C. BAIT: A New Medical Decision Support Technology Based on Discrete Choice Theory. Medical Decision Making 2021;41(5):614 View
  3. Bachhuber M, Nash D, Southern W, Heo M, Berger M, Schepis M, Thakral M, Cunningham C. Effect of Changing Electronic Health Record Opioid Analgesic Dispense Quantity Defaults on the Quantity Prescribed. JAMA Network Open 2021;4(4):e217481 View
  4. R G, G S. Iterative principal component analysis method for improvised classification of breast cancer disease using blood sample analysis. Medical & Biological Engineering & Computing 2021;59(10):1973 View
  5. Cross D, Adler-Milstein J, Degenholtz H. Progress Toward Digital Transformation in an Evolving Post-Acute Landscape. Innovation in Aging 2022;6(4) View
  6. Cornelissen N, van Eerdt R, Schraffenberger H, Haselager W. Reflection machines: increasing meaningful human control over Decision Support Systems. Ethics and Information Technology 2022;24(2) View
  7. ROZIER M, PATEL K, CROSS D. Electronic Health Records as Biased Tools or Tools Against Bias: A Conceptual Model. The Milbank Quarterly 2022;100(1):134 View
  8. Glock H, Milos Nymberg V, Borgström Bolmsjö B, Holm J, Calling S, Wolff M, Pikkemaat M. Attitudes, Barriers, and Concerns Regarding Telemedicine Among Swedish Primary Care Physicians: A Qualitative Study. International Journal of General Medicine 2021;Volume 14:9237 View
  9. Heider A, Mang H. Integration of Risk Scores and Integration Capability in Electronic Patient Records. Applied Clinical Informatics 2022;13(04):828 View
  10. Yung A, Kay J, Beale P, Gibson K, Shaw T. Computer-Based Decision Tools for Shared Therapeutic Decision-making in Oncology: Systematic Review. JMIR Cancer 2021;7(4):e31616 View
  11. Knop M, Weber S, Mueller M, Niehaves B. Human Factors and Technological Characteristics Influencing the Interaction of Medical Professionals With Artificial Intelligence–Enabled Clinical Decision Support Systems: Literature Review. JMIR Human Factors 2022;9(1):e28639 View
  12. Thiess H, Del Fiol G, Malone D, Cornia R, Sibilla M, Rhodes B, Boyce R, Kawamoto K, Reese T. Coordinated use of Health Level 7 standards to support clinical decision support: Case study with shared decision making and drug-drug interactions. International Journal of Medical Informatics 2022;162:104749 View
  13. Merianos A, Fiser K, Mahabee-Gittens E, Lyons M, Stone L, Gordon J. Clinical decision support for tobacco screening and counseling parents of pediatric patients: A qualitative analysis of pediatric emergency department and urgent care professionals. Drug and Alcohol Dependence Reports 2022;2:100019 View
  14. van Varsseveld O, ten Broeke A, Chorus C, Heyning N, Kooi E, Hulscher J. Surgery or comfort care for neonates with surgical necrotizing enterocolitis: Lessons learned from behavioral artificial intelligence technology. Frontiers in Pediatrics 2023;11 View
  15. Hauschildt J, Lyon-Scott K, Sheppler C, Larson A, McMullen C, Boston D, O’Connor P, Sperl-Hillen J, Gold R. Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers. JAMIA Open 2023;6(1) View
  16. Yang J, Shu K, Peng Y, Hsu S, Chiu Y, Pai M, Wu H, Tsai W, Tung K, Kuo R. Physician Compliance With a Computerized Clinical Decision Support System for Anemia Management of Patients With End-stage Kidney Disease on Hemodialysis: Retrospective Electronic Health Record Observational Study. JMIR Formative Research 2023;7:e44373 View
  17. Jung H, Park H, Lee H. Impact of a Decision Support System on Fall-Prevention Nursing Practices. Journal of Patient Safety 2023;19(8):525 View
  18. Shear K, Horgas A, Lucero R. Experts’ Perspectives on Use of Fast Healthcare Interoperable Resources for Computerized Clinical Decision Support. CIN: Computers, Informatics, Nursing 2023;41(10):752 View
  19. Heuft L, Voigt J, Selig L, Schmidt M, Eckelt F, Steinbach D, Federbusch M, Stumvoll M, Schlögl H, Isermann B, Kaiser T. Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study. Nutrients 2023;15(17):3712 View
  20. Shegog R, Savas L, Frost E, Thormaehlen L, Teague T, Steffy J, Healy C, Shay L, Preston S, Vernon S. Adaptation and Formative Evaluation of Online Decision Support to Implement Evidence-Based Strategies to Increase HPV Vaccination Rates in Pediatric Clinics. Vaccines 2023;11(7):1270 View
  21. He W, Chima S, Emery J, Manski-Nankervis J, Williams I, Hunter B, Nelson C, Martinez-Gutierrez J. Perceptions of primary care patients on the use of electronic clinical decision support tools to facilitate health care: A systematic review.. Patient Education and Counseling 2024;125:108290 View
  22. Gencturk M, Laleci Erturkmen G, Akpinar A, Pournik O, Ahmad B, Arvanitis T, Schmidt-Barzynski W, Robbins T, Alcantud Corcoles R, Abizanda P. Transforming evidence-based clinical guidelines into implementable clinical decision support services: the CAREPATH study for multimorbidity management. Frontiers in Medicine 2024;11 View
  23. Sulek R, Robertson J, Goodall E, Liew A, Pillar S, Upson G, Whitehouse A, Wicks R, Trembath D. Support Preferences and Clinical Decision Support Systems (CDSS) in the Clinical Care of Autistic Children: Stakeholder Perspectives. Advances in Neurodevelopmental Disorders 2024 View

Books/Policy Documents

  1. Cross D, Adler-Milstein J, Holmgren A. Responding to the Grand Challenges in Health Care via Organizational Innovation. View
  2. Simon G, Aliferis C. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences. View