Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15653, first published .
Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review

Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review

Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review

Journals

  1. Van Dort B, Zheng W, Sundar V, Baysari M. Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals. Journal of the American Medical Informatics Association 2021;28(1):177 View
  2. 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
  3. Yan Q, Jiang Z, Harbin Z, Tolbert P, Davies M. Exploring the relationship between electronic health records and provider burnout: A systematic review. Journal of the American Medical Informatics Association 2021;28(5):1009 View
  4. Gadhiya K, Zamora E, Saiyed S, Friedlander D, Kaelber D. Drug Alert Experience and Salience during Medical Residency at Two Healthcare Institutions. Applied Clinical Informatics 2021;12(02):355 View
  5. Wang C, Nguyen P, (Jack) Li Y, Islam M, Poly T, Tran Q, Huang C, Yang H. Improved diagnosis-medication association mining to reduce pseudo-associations. Computer Methods and Programs in Biomedicine 2021;207:106181 View
  6. Lorenzo-Zúñiga V, Bustamante-Balén M, Pons-Beltrán V, Peña-Gil C. Development of knowledge-based clinical decision support system for patients included in colorectal screening program. Gastroenterología y Hepatología 2022;45(6):419 View
  7. Monteith S, Glenn T. Comparison of potential psychiatric drug interactions in six drug interaction database programs: A replication study after 2 years of updates. Human Psychopharmacology: Clinical and Experimental 2021;36(6) View
  8. Patel B, Steinberg E, Pfohl S, Shah N. Learning decision thresholds for risk stratification models from aggregate clinician behavior. Journal of the American Medical Informatics Association 2021;28(10):2258 View
  9. Ali S, Jung S, Bilal H, Lee S, Hussain J, Afzal M, Hussain M, Ali T, Chung T, Lee S. Clinical Decision Support System Based on Hybrid Knowledge Modeling: A Case Study of Chronic Kidney Disease-Mineral and Bone Disorder Treatment. International Journal of Environmental Research and Public Health 2021;19(1):226 View
  10. Smith K, Durant K, Zimmerman C. Impact of an electronic health record alert on inappropriate prescribing of high-risk medications to patients with concurrent “do not give” orders. American Journal of Health-System Pharmacy 2022;79(14):1198 View
  11. Alsaidan J, Portlock J, Ata S, Aljadhey H, Franklin B. Retrospective descriptive assessment of clinical decision support medication-related alerts in two Saudi Arabian hospitals. BMC Medical Informatics and Decision Making 2022;22(1) View
  12. Nguyen J, Crews K, Moore B, Kornegay N, Baker D, Hasan M, Campbell P, Dean S, Relling M, Hoffman J, Haidar C. Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts. Journal of the American Medical Informatics Association 2022;30(1):132 View
  13. Jungreithmayr V, Meid A, Bittmann J, Fabian M, Klein U, Kugler S, Löpprich M, Reinhard O, Scholz L, Zeeh B, Bitz W, Bugaj T, Kihm L, Kopf S, Liemann A, Wagenlechner P, Zemva J, Benkert C, Merle C, Roman S, Welte S, Haefeli W, Seidling H. The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation—a before-and-after study. BMC Medical Informatics and Decision Making 2021;21(1) View
  14. Lorenzo-Zúñiga V, Bustamante-Balén M, Pons-Beltrán V, Peña-Gil C. Development of knowledge-based clinical decision support system for patients included in colorectal screening program. Gastroenterología y Hepatología (English Edition) 2022;45(6):419 View
  15. Park H, Chae M, Jeong W, Yu J, Jung W, Chang H, Cha W. Appropriateness of Alerts and Physicians’ Responses With a Medication-Related Clinical Decision Support System: Retrospective Observational Study. JMIR Medical Informatics 2022;10(10):e40511 View
  16. Brown A, Cavell G, Dogra N, Whittlesea C. The impact of an electronic alert to reduce the risk of co-prescription of low molecular weight heparins and direct oral anticoagulants. International Journal of Medical Informatics 2022;164:104780 View
  17. Jung S, Bae S, Seong D, Oh O, Kim Y, Yi B. Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study. JMIR Medical Informatics 2022;10(11):e40338 View
  18. Grauer A, Rosen A, Applebaum J, Carter D, Reddy P, Dal Col A, Kumaraiah D, Barchi D, Classen D, Adelman J. Examining medication ordering errors using AHRQ network of patient safety databases. Journal of the American Medical Informatics Association 2023;30(5):838 View
  19. Van De Sijpe G, Quintens C, Walgraeve K, Van Laer E, Penny J, De Vlieger G, Schrijvers R, De Munter P, Foulon V, Casteels M, Van der Linden L, Spriet I. Overall performance of a drug–drug interaction clinical decision support system: quantitative evaluation and end-user survey. BMC Medical Informatics and Decision Making 2022;22(1) View
  20. Brünn R, Lemke D, Basten J, Kellermann-Mühlhoff P, Köberlein-Neu J, Muth C, van den Akker M. Use of an Electronic Medication Management Support System in Patients with Polypharmacy in General Practice: A Quantitative Process Evaluation of the AdAM Trial. Pharmaceuticals 2022;15(6):759 View
  21. Bačar Bole C, Nagode K, Pišlar M, Mrhar A, Grabnar I, Vovk T. Potential Drug-Drug Interactions among Patients with Schizophrenia Spectrum Disorders: Prevalence, Association with Risk Factors, and Replicate Analysis in 2021. Medicina 2023;59(2):284 View
  22. Van Biesen W, Van Cauwenberge D, Decruyenaere J, Leune T, Sterckx S. An exploration of expectations and perceptions of practicing physicians on the implementation of computerized clinical decision support systems using a Qsort approach. BMC Medical Informatics and Decision Making 2022;22(1) View
  23. Gedde-Dahl A, Spigset O, Molden E. Co-prescription of metoprolol and CYP2D6-inhibiting antidepressants before and after implementation of an optimized drug interaction database in Norway. European Journal of Clinical Pharmacology 2022;78(10):1623 View
  24. Bittmann J, Haefeli W, Seidling H. Modulators Influencing Medication Alert Acceptance: An Explorative Review. Applied Clinical Informatics 2022;13(02):468 View
  25. Tukukino C, Parodi López N, Svensson S, Wallerstedt S. Drug interaction alerts in older primary care patients, and related medically justified actions. European Journal of Clinical Pharmacology 2022;78(7):1115 View
  26. Chen J, Cutrona S, Dharod A, Bunch S, Foley K, Ostasiewski B, Hale E, Bridges A, Moses A, Donny E, Sutfin E, Houston T. Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics. JMIR Medical Informatics 2023;11:e43097 View
  27. Okerberg C, Adie S, Konerman M, Zimmerman C. Implementation of a clinical decision support alert to prevent use of intravenous β-blockers and nondihydropyridine calcium channel blockers in hospitalized patients with acute decompensated heart failure. American Journal of Health-System Pharmacy 2023;80(9):e119 View
  28. Ma J, Lowe J, Berkowitz C, Kim A, Togo I, Musser R, Fischer J, Shah K, Ibrahim S, Bosworth H, Totten A, Dolor R. Provider Interaction With an Electronic Health Record Notification to Identify Eligible Patients for a Cluster Randomized Trial of Advance Care Planning in Primary Care: Secondary Analysis. Journal of Medical Internet Research 2023;25:e41884 View
  29. Raban M, Gates P, Gamboa S, Gonzalez G, Westbrook J. Effectiveness of non-interruptive nudge interventions in electronic health records to improve the delivery of care in hospitals: a systematic review. Journal of the American Medical Informatics Association 2023;30(7):1313 View
  30. Khalil V, Hua A. Impact of Redesign of a Clinical Decision Allergy and Drug Interactions Alerts in an Electronic Prescribing System on Patient Safety – A Quantitative Descriptive Study. International Journal of Digital Health 2021;1(1):16 View
  31. Alanazi A, alalawi W, Aldosari B. An Evaluation of Drug-Drug Interaction Alerts Produced by Clinical Decision Support Systems in a Tertiary Hospital. Cureus 2023 View
  32. Colicchio T, Cimino J. Beyond the override: Using evidence of previous drug tolerance to suppress drug allergy alerts; a retrospective study of opioid alerts. Journal of Biomedical Informatics 2023;147:104508 View
  33. Karajizadeh M, Zand F, Vazin A, Saeidnia H, Lund B, Tummuru S, Sharifian R. Design, development, implementation, and evaluation of a severe drug–drug interaction alert system in the ICU: An analysis of acceptance and override rates. International Journal of Medical Informatics 2023;177:105135 View
  34. Ng H, Kansal A, Abdul Naseer J, Hing W, Goh C, Poh H, D’souza J, Lim E, Tan G. Optimizing Best Practice Advisory alerts in electronic medical records with a multi-pronged strategy at a tertiary care hospital in Singapore. JAMIA Open 2023;6(3) View
  35. Rosado-Ingelmo A, Pastor Magro A, Pizarro-Jaraiz M, Sanz-Marquez S, Silva Riádigos G, Peña Acevedo Y, Tejedor-Alberti A, Tejedor-Alonso M. Drug Allergy Alert System in a Spanish University Hospital: Description and Dynamics of Use. International Archives of Allergy and Immunology 2023;184(11):1079 View
  36. Trinkley K, Wright G, Allen L, Bennett T, Glasgow R, Hale G, Heckman S, Huebschmann A, Kahn M, Kao D, Lin C, Malone D, Matlock D, Wells L, Wysocki V, Zhang S, Suresh K. Sustained Effect of Clinical Decision Support for Heart Failure: A Natural Experiment Using Implementation Science. Applied Clinical Informatics 2023;14(05):822 View
  37. 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
  38. Horne K, Noble R, Karelia S, Selby N. Electronic alerts in acute kidney injury: why does evidence of benefit remain elusive?. Current Opinion in Nephrology & Hypertension 2023;32(6):522 View
  39. Virtanen L, Kaihlanen A, Saukkonen P, Reponen J, Lääveri T, Vehko T, Saastamoinen P, Viitanen J, Heponiemi T. Associations of perceived changes in work due to digitalization and the amount of digital work with job strain among physicians: a national representative sample. BMC Medical Informatics and Decision Making 2023;23(1) View
  40. Shakowski C, Page II R, Wright G, Lunowa C, Marquez C, Suresh K, Allen L, Glasgow R, Lin C, Wick A, Trinkley K. Comparative effectiveness of generic commercial versus locally customized clinical decision support tools to reduce prescription of nonsteroidal anti-inflammatory drugs for patients with heart failure. Journal of the American Medical Informatics Association 2023;30(9):1516 View
  41. Zhao S, Dai H, Chen J, Ni M, Peng W, Li X, Li F, Chen B, Cai H, Liu Y, Gu Z, Du S, Ma P. Prevalence, contemporary trends and associated factors of potentially inappropriate prescription of edoxaban in real‐world clinical practice: A subanalysis of the SUNSHINE registry. British Journal of Clinical Pharmacology 2024;90(3):837 View
  42. Dahmke H, Schelshorn J, Fiumefreddo R, Schuetz P, Salili A, Cabrera-Diaz F, Meyer-Massetti C, Zaugg C. Evaluation of Triple Whammy Prescriptions After the Implementation of a Drug Safety Algorithm. Drugs - Real World Outcomes 2024;11(1):125 View
  43. Sundermann M, Clendon O, McNeill R, Doogue M, Chin P. Optimising interruptive clinical decision support alerts for antithrombotic duplicate prescribing in hospital. International Journal of Medical Informatics 2024;186:105418 View
  44. Dil-Nahlieli D, Ben-Yehuda A, Souroujon D, Hyam E, Shafran-Tikvah S. Validation of a novel Artificial Pharmacology Intelligence (API) system for the management of patients with polypharmacy. Research in Social and Administrative Pharmacy 2024;20(7):633 View
  45. Dahmke H, Cabrera-Diaz F, Heizmann M, Stoop S, Schuetz P, Fiumefreddo R, Zaugg C. Development and validation of a clinical decision support system to prevent anticoagulant duplications. International Journal of Medical Informatics 2024;187:105446 View
  46. Graafsma J, Murphy R, van de Garde E, Karapinar-Çarkit F, Derijks H, Hoge R, Klopotowska J, van den Bemt P. The use of artificial intelligence to optimize medication alerts generated by clinical decision support systems: a scoping review. Journal of the American Medical Informatics Association 2024;31(6):1411 View
  47. Jin L, Fang H, Shen J, He Z, Li Y, Dong L, Feng J, Asakawa T. Evaluation of appropriateness of alerts overrides and physicians' responses of the medication-related clinical decision support system in China, a hospital-based study. Drug Discoveries & Therapeutics 2024;18(2):89 View
  48. Felisberto M, Lima G, Celuppi I, Fantonelli M, Zanotto W, Dias de Oliveira J, Mohr E, dos Santos R, Scandolara D, Cunha C, Hammes J, da Rosa J, Demarchi I, Wazlawick R, Dalmarco E. Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis. Health Informatics Journal 2024;30(2) View
  49. Lampe D, Grosser J, Grothe D, Aufenberg B, Gensorowsky D, Witte J, Greiner W. How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review. BMC Medical Informatics and Decision Making 2024;24(1) View
  50. Bauer J, Busse M, Kopetzky T, Seggewies C, Fromm M, Dörje F. Interprofessional Evaluation of a Medication Clinical Decision Support System Prior to Implementation. Applied Clinical Informatics 2024;15(03):637 View
  51. Van De Sijpe G, Walgraeve K, Van Laer E, Quintens C, Machiels C, Foulon V, Casteels M, Van der Linden L, Spriet I. The Impact of Customized Screening Intervals on the Burden of Drug-Drug Interaction Alerts: An Interrupted Time Series Analysis. Journal of Medical Systems 2024;48(1) View
  52. Awad S, Loveday T, Lau R, Baysari M. Development of a Human Factors–Based Guideline to Support the Design, Evaluation, and Continuous Improvement of Clinical Decision Support. Mayo Clinic Proceedings: Digital Health 2025;3(1):100182 View

Books/Policy Documents

  1. Shirazian S, Maesaka J, Imbriano L, Mattana J. Diabetes and Kidney Disease. View
  2. Benson N, Salmasian H, Bates D. Clinical Decision Support and Beyond. View
  3. Julius M, Alo U, Onu F, Akobundu C, Agwu C, Ogbu N, Eze F. Proceedings of Ninth International Congress on Information and Communication Technology. View