Appl Clin Inform 2018; 09(02): 268-274
DOI: 10.1055/s-0038-1642608
Research Article
Schattauer GmbH Stuttgart

Determining Inappropriate Medication Alerts from “Inaccurate Warning” Overrides in the Intensive Care Unit

Christine A. Rehr
1   Department of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Clinical and Quality Analysis, Partners HealthCare, Somerville, Massachusetts, United States
,
Adrian Wong
1   Department of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
3   Massachusetts College of Pharmacy and Health Systems University, Boston, Massachusetts, United States
,
Diane L. Seger
1   Department of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Clinical and Quality Analysis, Partners HealthCare, Somerville, Massachusetts, United States
,
David W. Bates
1   Department of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
2   Clinical and Quality Analysis, Partners HealthCare, Somerville, Massachusetts, United States
4   Harvard Medical School, Boston, Massachusetts, United States
› Author Affiliations
Funding This study was funded by a grant from the CRICO/Risk Management Foundation of the Harvard Medical Institutions.
Further Information

Publication History

19 January 2018

14 March 2018

Publication Date:
25 April 2018 (online)

Abstract

Objective This article aims to understand provider behavior around the use of the override reason “Inaccurate warning,” specifically whether it is an effective way of identifying unhelpful medication alerts.

Materials and Methods We analyzed alert overrides that occurred in the intensive care units (ICUs) of a major academic medical center between June and November 2016, focused on the following high-significance alert types: dose, drug-allergy alerts, and drug–drug interactions (DDI). Override appropriateness was analyzed by two independent reviewers using predetermined criteria.

Results A total of 268 of 26,501 ICU overrides (1.0%) used the reason “Inaccurate warning,” with 93 of these overrides associated with our included alert types. Sixty-one of these overrides (66%) were identified to be appropriate. Twenty-one of 30 (70%) dose alert overrides were appropriate. Forty of 48 drug-allergy alert overrides (83%) were appropriate, for reasons ranging from prior tolerance (n = 30) to inaccurate ingredient matches (n = 5). None of the 15 DDI overrides were appropriate.

Conclusion The “Inaccurate warning” reason was selectively used by a small proportion of providers and overrides using this reason identified important opportunities to reduce excess alerts. Potential opportunities include improved evaluation of dosing mechanisms based on patient characteristics, inclusion of institutional dosing protocols to alert logic, and evaluation of a patient's prior tolerance to a medication that they have a documented allergy for. This resource is not yet routinely used for alert tailoring at our institution but may prove to be a valuable resource to evaluate available alerts.

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by Partners HealthCare Institutional Review Board.


 
  • References

  • 1 Lesar TS, Briceland L, Stein DS. Factors related to errors in medication prescribing. JAMA 1997; 277 (04) 312-317
  • 2 Bates DW, Teich JM, Lee J. , et al. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc 1999; 6 (04) 313-321
  • 3 Bates DW, O'Neil AC, Boyle D. , et al. Potential identifiability and preventability of adverse events using information systems. J Am Med Inform Assoc 1994; 1 (05) 404-411
  • 4 Bates DW, Cullen DJ, Laird N. , et al; ADE Prevention Study Group. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. JAMA 1995; 274 (01) 29-34
  • 5 Cullen DJ, Sweitzer BJ, Bates DW, Burdick E, Edmondson A, Leape LL. Preventable adverse drug events in hospitalized patients: a comparative study of intensive care and general care units. Crit Care Med 1997; 25 (08) 1289-1297
  • 6 Morimoto T, Sakuma M, Matsui K. , et al. Incidence of adverse drug events and medication errors in Japan: the JADE study. J Gen Intern Med 2011; 26 (02) 148-153
  • 7 Lin CP, Payne TH, Nichol WP, Hoey PJ, Anderson CL, Gennari JH. Evaluating clinical decision support systems: monitoring CPOE order check override rates in the Department of Veterans Affairs' Computerized Patient Record System. J Am Med Inform Assoc 2008; 15 (05) 620-626
  • 8 Nanji KC, Slight SP, Seger DL. , et al. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc 2014; 21 (03) 487-491
  • 9 Kuperman GJ, Bobb A, Payne TH. , et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14 (01) 29-40
  • 10 Payne TH, Nichol WP, Hoey P, Savarino J. Characteristics and override rates of order checks in a practitioner order entry system. Proc AMIA Symp 2002; 2002: 602-606
  • 11 Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Kaushal R. ; with the HITEC Investigators. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak 2017; 17 (01) 36
  • 12 Weingart SN, Toth M, Sands DZ, Aronson MD, Davis RB, Phillips RS. Physicians' decisions to override computerized drug alerts in primary care. Arch Intern Med 2003; 163 (21) 2625-2631
  • 13 Hsieh TC, Kuperman GJ, Jaggi T. , et al. Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J Am Med Inform Assoc 2004; 11 (06) 482-491
  • 14 Abookire SA, Teich JM, Sandige H. , et al. Improving allergy alerting in a computerized physician order entry system. Proc AMIA Symp 2000; 2000: 2-6
  • 15 Paterno MD, Maviglia SM, Gorman PN. , et al. Tiering drug-drug interaction alerts by severity increases compliance rates. J Am Med Inform Assoc 2009; 16 (01) 40-46
  • 16 Czock D, Konias M, Seidling HM. , et al. Tailoring of alerts substantially reduces the alert burden in computerized clinical decision support for drugs that should be avoided in patients with renal disease. J Am Med Inform Assoc 2015; 22 (04) 881-887
  • 17 Cho I, Slight SP, Nanji KC. , et al. Understanding physicians' behavior toward alerts about nephrotoxic medications in outpatients: a cross-sectional analysis. BMC Nephrol 2014; 15: 200
  • 18 Dekarske BM, Zimmerman CR, Chang R, Grant PJ, Chaffee BW. Increased appropriateness of customized alert acknowledgement reasons for overridden medication alerts in a computerized provider order entry system. Int J Med Inform 2015; 84 (12) 1085-1093
  • 19 Bloomrosen M, Starren J, Lorenzi NM, Ash JS, Patel VL, Shortliffe EH. Anticipating and addressing the unintended consequences of health IT and policy: a report from the AMIA 2009 Health Policy Meeting. J Am Med Inform Assoc 2011; 18 (01) 82-90
  • 20 Office of the National Coordinator for Health Information Technology. Certified Health IT Developers and Editions Reported by Hospitals Participating in the Medicare EHR Incentive Program. Washington, DC: HealthIT.gov; c2017. Available at: https://dashboard.healthit.gov/quickstats/pages/FIG-Vendors-of-EHRs-to-Participating-Hospitals.php . Accessed January 15, 2018
  • 21 Hoste EA, Bagshaw SM, Bellomo R. , et al. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med 2015; 41 (08) 1411-1423
  • 22 Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care 2004; 13 (04) 306-314
  • 23 Wong A, Amato MG, Seger DL. , et al. Evaluation of medication-related clinical decision support alert overrides in the intensive care unit. J Crit Care 2017; 39: 156-161
  • 24 Wong A, Amato MG, Seger DL. , et al. Prospective evaluation of medication-related clinical decision support over-rides in the intensive care unit. [published online ahead-of-print February 9, 2018] BMJ Qual Saf 2018; DOI: 10.1136/bmjqs-2017-007531.
  • 25 Gandhi TK, Weingart SN, Seger AC. , et al. Outpatient prescribing errors and the impact of computerized prescribing. J Gen Intern Med 2005; 20 (09) 837-841
  • 26 Bobb A, Gleason K, Husch M, Feinglass J, Yarnold PR, Noskin GA. The epidemiology of prescribing errors: the potential impact of computerized prescriber order entry. Arch Intern Med 2004; 164 (07) 785-792
  • 27 Bates DW, Kuperman GJ, Wang S. , et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc 2003; 10 (06) 523-530
  • 28 Tolley CL, Slight SP, Husband AK, Watson N, Bates DW. Improving medication-related clinical decision support. Am J Health Syst Pharm 2018; 75 (04) 239-246
  • 29 Carver CS, Scheier MF. The self-attention-induced feedback loop and social facilitation. J Exp Soc Psychol 1981; 17: 545-568
  • 30 Carver CS, Scheier MF. Control theory: a useful conceptual framework for personality-social, clinical, and health psychology. Psychol Bull 1982; 92 (01) 111-135
  • 31 Lesar TS, Briceland LL, Delcoure K, Parmalee JC, Masta-Gornic V, Pohl H. Medication prescribing errors in a teaching hospital. JAMA 1990; 263 (17) 2329-2334