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

Decision Support for Health Professionals (1127) Clinical Information and Decision Making (1314) Safety and Error Prevention in Health (186) Computerized Provider Order Entry (CPOE) (20)

Published on in Vol 6, No 1 (2018): Jan-Mar

Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review

Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review

Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review

Authors of this article:

Delphine Carli1, 2 Author Orcid Image ;   Guillaume Fahrni3 Author Orcid Image ;   Pascal Bonnabry1, 2 Author Orcid Image ;   Christian Lovis3, 4 Author Orcid Image
Article Authors Cited by (29) Tweetations (2) Metrics

Journals

  1. Buckley M, Knutson K, Agarwal S, Lansburg J, Wicks L, Saggar R, Richards E, Kopp B, Erstad B. Clinical Pharmacist–Led Impact on Inappropriate Albumin Use and Costs in the Critically Ill. Annals of Pharmacotherapy 2020;54(2):105 View
  2. Levy B. Training Aspects of Laboratory-Based Decision Support. Clinics in Laboratory Medicine 2019;39(2):303 View
  3. Jankovic I, Chen J. Clinical Decision Support and Implications for the Clinician Burnout Crisis. Yearbook of Medical Informatics 2020;29(01):145 View
  4. Rosenbaum M, Baron J. Using Machine Learning-Based Multianalyte Delta Checks to Detect Wrong Blood in Tube Errors. American Journal of Clinical Pathology 2018;150(6):555 View
  5. Mann D, Hess R, McGinn T, Richardson S, Jones S, Palmisano J, Chokshi S, Mishuris R, McCullagh L, Park L, Dinh-Le C, Smith P, Feldstein D. Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial. Journal of General Internal Medicine 2020;35(S2):788 View
  6. Rudolf J, Dighe A. Decision Support Tools within the Electronic Health Record. Clinics in Laboratory Medicine 2019;39(2):197 View
  7. Lovis C. Unlocking the Power of Artificial Intelligence and Big Data in Medicine. Journal of Medical Internet Research 2019;21(11):e16607 View
  8. Khalifa M, Magrabi F, Gallego Luxan B. Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals’ Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial. Journal of Medical Internet Research 2020;22(7):e15770 View
  9. Barnes G, Sippola E, Dorsch M, Errickson J, Lanham M, Allen A, Spoutz P, Sales A, Sussman J. Applying population health approaches to improve safe anticoagulant use in the outpatient setting: the DOAC Dashboard multi-cohort implementation evaluation study protocol. Implementation Science 2020;15(1) View
  10. Van Driest S, Wang L, McLemore M, Bridges B, Fleming G, McGregor T, Jones D, Shirey-Rice J, Gatto C, Gay J, Byrne D, Weitkamp A, Roden D, Bernard G. Acute kidney injury risk-based screening in pediatric inpatients: a pragmatic randomized trial. Pediatric Research 2020;87(1):118 View
  11. Muylle K, Gentens K, Dupont A, Cornu P. Evaluation of an optimized context-aware clinical decision support system for drug-drug interaction screening. International Journal of Medical Informatics 2021;148:104393 View
  12. 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
  13. Hughes M, Apostolou A, Reilley B, Leston J, McCollum J, Iralu J. Electronic Health Record Reminders for Chlamydia Screening in an American Indian Population. Public Health Reports 2021;136(3):320 View
  14. Wan P, Satybaldy A, Huang L, Holtskog H, Nowostawski M. Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert). Journal of Medical Internet Research 2020;22(10):e22013 View
  15. Skalafouris C, Samer C, Stirnemann J, Grosgurin O, Eggimann F, Grauser D, Reny J, Bonnabry P, Guignard B. Electronic monitoring of potential adverse drug events related to lopinavir/ritonavir and hydroxychloroquine during the first wave of COVID-19. European Journal of Hospital Pharmacy 2023;30(2):113 View
  16. Ramos S, Alvarez N, dos Santos Alcântara T, Sanchez J, da Costa Lima E, de Lyra Júnior D. Methods for the detection of adverse drug reactions in hospitalized children: a systematic review. Expert Opinion on Drug Safety 2021;20(10):1225 View
  17. Sakhuja A, Bataineh A, Dealmeida D, Bilderback A, Ambrosino R, Fuhrman D, Kellum J. Creating a High-Specificity Acute Kidney Injury Detection System for Clinical and Research Applications. American Journal of Kidney Diseases 2021;78(5):764 View
  18. Jani Y, Franklin B. Interruptive alerts: only one part of the solution for clinical decision support. BMJ Quality & Safety 2021;30(12):933 View
  19. Skalafouris C, Blanc A, Grosgurin O, Marti C, Samer C, Lovis C, Bonnabry P, Guignard B. Development and retrospective evaluation of a clinical decision support system for the efficient detection of drug-related problems by clinical pharmacists. International Journal of Clinical Pharmacy 2023;45(2):406 View
  20. Skalafouris C, Reny J, Stirnemann J, Grosgurin O, Eggimann F, Grauser D, Teixeira D, Jermini M, Bruggmann C, Bonnabry P, Guignard B. Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events. BMC Medical Informatics and Decision Making 2022;22(1) View
  21. Fletcher E, Burns A, Wiering B, Lavu D, Shephard E, Hamilton W, Campbell J, Abel G. Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review. BMC Primary Care 2023;24(1) View
  22. Stoffel M, Desai S, Laine M, Leu M, Liao Z, Jang J, Singh A, Pozdeyev N, Sutton P, Wright A, White A. Lessons Learned from Creating Alert Governance during an Electronic Health Record Transition. ACI Open 2022;06(01):e50 View
  23. Muylle K, van Laere S, Pannone L, Coenen S, de Asmundis C, Dupont A, Cornu P. Added value of patient‐ and drug‐related factors to stratify drug‐drug interaction alerts for risk of QT prolongation: Development and validation of a risk prediction model. British Journal of Clinical Pharmacology 2023;89(4):1374 View
  24. Wake D, Smith D, Kazi S, Dunnenberger H. Pharmacogenomic Clinical Decision Support: A Review, How‐to Guide, and Future Vision. Clinical Pharmacology & Therapeutics 2022;112(1):44 View
  25. Satir A, Pfiffner M, Meier C, Caduff Good A. Prescribing errors in children: what is the impact of a computerized physician order entry?. European Journal of Pediatrics 2023;182(6):2567 View
  26. Stultz J, Shelton C, Kiles T, Wheeler J. Improvement in Pharmacy Student Responses to Medication-Related Problems with and without Clinical Decision Support Alerts. American Journal of Pharmaceutical Education 2023;87(5):100062 View
  27. Dahmke H, Fiumefreddo R, Schuetz P, De Iaco R, Zaugg C. Tackling alert fatigue with a semi-automated clinical decision support system: quantitative evaluation and end-user survey. Swiss Medical Weekly 2023;153(7):40082 View
  28. Fournier A, Fallet C, Sadeghipour F, Perrottet N. Assessing the applicability and appropriateness of ChatGPT in answering clinical pharmacy questions. Annales Pharmaceutiques Françaises 2024;82(3):507 View
  29. Jung W, Yu J, Park H, Chae M, Lee S, Choi J, Kang M, Chang D, Cha W. Effect of knowledgebase transition of a clinical decision support system on medication order and alert patterns in an emergency department. Scientific Reports 2023;13(1) View