Appl Clin Inform 2014; 05(03): 802-813
DOI: 10.4338/ACI-2013-12-RA-0103
Research Article
Schattauer GmbH

Drug interaction alert override rates in the Meaningful Use era

No evidence of progress
A.D. Bryant
1   Department of Medicine, University of Washington
,
G.S. Fletcher
1   Department of Medicine, University of Washington
2   Information Technology Services, UW Medicine, University of Washington
,
T.H. Payne
1   Department of Medicine, University of Washington
2   Information Technology Services, UW Medicine, University of Washington
› Author Affiliations
Further Information

Publication History

received: 04 January 2014

accepted: 18 July 2014

Publication Date:
19 December 2017 (online)

Summary

Background: Interruptive drug interaction alerts may reduce adverse drug events and are required for Stage I Meaningful Use attestation. For the last decade override rates have been very high. Despite their widespread use in commercial EHR systems, previously described interventions to improve alert frequency and acceptance have not been well studied.

Objectives: (1) To measure override rates of inpatient medication alerts within a commercial clinical decision support system, and assess the impact of local customization efforts. (2) To compare override rates between drug-drug interaction and drug-allergy interaction alerts, between attending and resident physicians, and between public and academic hospitals. (3) To measure the correlation between physicians’ individual alert quantities and override rates as an indicator of potential alert fatigue.

Methods: We retrospectively analyzed physician responses to drug-drug and drug-allergy interaction alerts, as generated by a common decision support product in a large teaching hospital system.

Results: (1) Over four days, 461 different physicians entered 18,354 medication orders, resulting in 2,455 visible alerts; 2,280 alerts (93%) were overridden. (2) The drug-drug alert override rate was 95.1%, statistically higher than the rate for drug-allergy alerts (90.9%) (p < 0.001). There was no significant difference in override rates between attendings and residents, or between hospitals. (3) Physicians saw a mean of 1.3 alerts per day, and the number of alerts per physician was not significantly correlated with override rate (R2 = 0.03, p = 0.41).

Conclusions: Despite intensive efforts to improve a commercial drug interaction alert system and to reduce alerting, override rates remain as high as reported over a decade ago. Alert fatigue does not seem to contribute. The results suggest the need to fundamentally question the premises of drug interaction alert systems.

Citation: Bryant AD, Fletcher GS, Payne TH. Drug interaction alert override rates in the Meaningful Use era: No evidence of progress. Appl Clin Inf 2014; 5: 802–813

http://dx.doi.org/10.4338/ACI-2013-12-RA-0103

 
  • References

  • 1 Bates DW, Leape LL, Cullen DJ, Laird N, Petersen LA, Teich JM, Burdick E, Hickey M, Kleefield S, Shea B, Vander Vliet M, Seger DL. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998; 280: 1311-1316.
  • 2 Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma’Luf N, Boyle D, Leape L. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc 1999; 6 (04) 313-321.
  • 3 Juurlink DN, Mamdani M, Kopp A, Laupacis A, Redelmeier DA. Drug-drug interactions among elderly patients hospitalized for drug toxicity. JAMA 2003; 289: 1652-1658.
  • 4 Centers for Medicare & Medicaid Services.. Medicare & Medicaid EHR Incentive Program. Meaningful Use Stage 1 Requirements Overview 2010. https://www.cms.gov/Regulations-and-Guidance/Legislation/ EHRIncentivePrograms/downloads/MU_Stage1_ReqOverview.pdf (accessed July 2013).
  • 5 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: 2625-2631.
  • 6 van der Sijs H, Aarts J, Vulto A, Berg M. Overriding of drug safety alerts in computerized physician order entry. J Am Med Inform Assoc 2006; 13: 138-147.
  • 7 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: 602-606.
  • 8 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: 620-626.
  • 9 Carspecken CW, Sharek PJ, Longhurst C, Pageler NM. A clinical case of electronic health record drug alert fatigue: consequences for patient outcome. Pediatrics 2013; 131: e1970-e1973.
  • 10 Shah NR, Seger AC, Seger DL, Fiskio JM, Kuperman GJ, Blumenfeld B, Recklet EG, Bates DW, Gandhi TK. Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc 2006; 13: 5-11.
  • 11 Paterno MD, Maviglia SM, Gorman PN, Seger DL, Yoshida E, Seger AC, Bates DW, Gandhi TK. Tiering drug-drug interaction alerts by severity increases compliance rates. J Am Med Inform Assoc 2009; 16: 40-46.
  • 12 Nanji KC, Slight SP, Seger DL, Cho I, Fiskio JM, Redden LM, Volk LA, Bates DW. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc 2014; 21 (03) 487-491.
  • 13 Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med 2003; 163: 1409-1416.
  • 14 Hansten PD, Horn JR, Hazlet TK. ORCA: Operational classification of drug interactions. J Am Pharm Assoc 2001; 41: 161-165.
  • 15 Horn JR, Hansten PD, Osborn JD, Wareham P, Somani S. Customizing clinical decision support to prevent excessive drug-drug interaction alerts. Am J Health-Syst Pharm 2011; 68: 662-664.
  • 16 Charles D, King J, Furukawa MF, Patel V. Hospital Adoption of Electronic Health Record Technology to Meet Meaningful Use Objectives: 2008–2012. ONC Data Brief, no. 10. Washington, DC: Office of the National Coordinator for Health Information Technology; 2013
  • 17 Langemeijer MM, Peute LW, Jaspers MW. Impact of alert specifications on clinicians’ adherence. Stud Health Technol Inform 2011; 169: 930-934.
  • 18 Seidling HM, Paterno MD, Haefeli WE, Bates DW. Coded entry versus free-text and alert overrides: What you get depends on how you ask. Int J Med Inform 2010; 79: 792-796.
  • 19 Phansalkar S, van der Sijs H, Tucker AD, Desai AA, Bell DS, Teich JM, Middleton B, Bates DW. Drug–drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records. J Am Med Inform Assoc 2013; 20: 489-493.
  • 20 Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G, Classen DC, Bates DW. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14: 29-40.
  • 21 Scharnweber C, Lau BD, Mollenkopf N, Thiemann DR, Veltri MA, Lehmann CU. Evaluation of medication dose alerts in pediatric inpatients. Int J Med Inform 2013; 82: 676-683.
  • 22 Hug BL, Keohane C, Seger DL, Yoon C, Bates DW. The costs of adverse drug events in community hospitals. Jt Comm J Qual Patient Saf 2012; 38: 120-126.
  • 23 Slight SP, Seger DL, Nanji KC, Cho I, Maniam N, Dykes PC, Bates DW. Are we heeding the warning signs? Examining providers’ overrides of computerized drug-drug interaction alerts in primary care. PLoS ONE 2013; 8 (12) e85071.
  • 24 Hayward J, Thomson F, Milne H, Buckingham S, Sheikh A, Fernando B, Cresswell K, Williams R, Pinnock H. ‘Too much, too late’: mixed methods multi-channel video recording study of computerized decision support systems and GP prescribing. J Am Med Inform Assoc 2013; 20 e1 e76-e84.
  • 25 Phansalkar S, Wright A, Kuperman GJ, Vaida AJ, Bobb AM, Jenders RA, Payne TH, Halamka J, Bloom-rosen M, Bates DW. Towards meaningful medication-related clinical decision support: recommendations for an initial implementation. Appl Clin Inf 2011; 2: 50-62.
  • 26 van der Sijs H, Aarts J, van Gelder T, Berg M, Vulto A. Turning off frequently overridden drug alerts: limited opportunities for doing it safely. J Am Med Inform Assoc 2008; 15 (Suppl. 04) 439-448.
  • 27 Horn JR, Gumpper KF, Hardy JC, McDonnell PJ, Phansalkar S, Reilly C. Clinical decision support for drug–drug interactions: improvement needed. Am J Health-Syst Pharm 2013; 70: 905-909.
  • 28 Hsieh TC, Kuperman GJ, Jaggi T, Hojnowski-Diaz P, Fiskio J, Williams DH. Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J Am Med Inform Assoc 2004; 11: 482-491.
  • 29 Abookire SA, Teich JM, Sandige H, Paterno MD, Martin MT, Kuperman GJ, Bates DW. Improving allergy alerting in a computerized physician order entry system. Proc AMIA Symp 2000: 2-6.
  • 30 Strom BL, Schinnar R, Apter AJ, Margolis DJ, Lautenbach E, Hennessy S, Bilker WB, Pettitt D. Absence of cross-reactivity between sulfonamide antibiotics and sulfonamide nonantibiotics. N Engl J Med 2003; 349: 1628-1635.