Appl Clin Inform 2017; 08(02): 491-501
DOI: 10.4338/ACI-2016-10-RA-0168
Research Article
Schattauer GmbH

The Effects of Medication Alerts on Prescriber Response in a Pediatric Hospital

Judith W Dexheimer
1   Division of Emergency Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
2   Department of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Eric S. Kirkendall
2   Department of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
3   Department of Information Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
4   Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
5   James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Michal Kouril
2   Department of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Philip A. Hagedorn
3   Department of Information Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
4   Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Thomas Minich
3   Department of Information Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
6   Division of Pharmacy, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Leo L. Duan
7   Center for Imaging Research, Johns Hopkins University, Baltimore, MD
,
Monifa Mahdi
4   Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
Rhonda Szczesniak
8   Division of Biostatistics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
9   Division of Pulmonary Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
,
S. Andrew Spooner
2   Department of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
3   Department of Information Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
4   Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
› Author Affiliations
Further Information

Publication History

05 October 2016

28 February 2017

Publication Date:
21 December 2017 (online)

Summary

Objective: More than 70% of hospitals in the United States have electronic health records (EHRs). Clinical decision support (CDS) presents clinicians with electronic alerts during the course of patient care; however, alert fatigue can influence a provider’s response to any EHR alert. The primary goal was to evaluate the effects of alert burden on user response to the alerts.

Methods: We performed a retrospective study of medication alerts over a 24-month period (1/2013–12/2014) in a large pediatric academic medical center. The institutional review board approved this study. The primary outcome measure was alert salience, a measure of whether or not the prescriber took any corrective action on the order that generated an alert. We estimated the ideal number of alerts to maximize salience. Salience rates were examined for providers at each training level, by day of week, and time of day through logistic regressions.

Results: While salience never exceeded 38%, 49 alerts/day were associated with maximal salience in our dataset. The time of day an order was placed was associated with alert salience (maximal salience 2am). The day of the week was also associated with alert salience (maximal salience on Wednesday). Provider role did not have an impact on salience.

Conclusion: Alert burden plays a role in influencing provider response to medication alerts. An increased number of alerts a provider saw during a one-day period did not directly lead to decreased response to alerts. Given the multiple factors influencing the response to alerts, efforts focused solely on burden are not likely to be effective.

Citation: Dexheimer JW, Kirkendall ES, Kouril M, Hagedorn PA, Minich T, Duan LL, Mahdi M, Szczesniak R, Spooner SA. The effects of medication alerts on prescriber response in a pediatric hospital. Appl Clin Inform 2017; 8: 491–501 https://doi.org/10.4338/ACI-2016-10-RA-0168

Institutional Review/Human Subjects

The study was approved by the institutional review board.


 
  • References

  • 1 Jamoom E, Beatty P, Bercovitz A, Woodwell D, Palso K, Rechtsteiner E. Physician adoption of electronic health record systems: United States, 2011. NCHS Data Brief. 2012; 98: 1-8.
  • 2 Blumenthal D, Tavenner M. The ,,meaningful use“ regulation for electronic health records. N Engl J Med 2010; 363 (06) 501-504.
  • 3 Buntin MB, Jain SH, Blumenthal D. Health information technology: laying the infrastructure for national health reform. Health Aff (Millwood) 2010; 29 (06) 1214-1219.
  • 4 Centers for Medicare and Medicaid Services. CMS Quality Measure Development Plan: Supporting the Transition to the Merit-based Incentive Payment System (MIPS) and Alternative Payment Models (APMs). Baltimore, MD: Centers for Medicare and Medicaid Services; 2016 [updated 2 May 2016;cited 18 May 2016]; Available from: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/MACRA-MIPS-and-APMs/MACRA-MIPS-and-APMs.html
  • 5 Marcotte L, Seidman J, Trudel K, Berwick DM, Blumenthal D, Mostashari F, Jain SH. Achieving meaningful use of health information technology: a guide for physicians to the EHR incentive programs. Arch Intern Med 2012; 172 (09) 731-736.
  • 6 Stultz JS, Nahata MC. Computerized clinical decision support for medication prescribing and utilization in pediatrics. J Am Med Inform Assoc 2012; 19 (06) 942-953.
  • 7 McCoy AB, Cox ZL, Neal EB, Waitman LR, Peterson NB, Bhave G, Siew ED, Danciu I, Lewis JB, Peterson JF. Real-time pharmacy surveillance and clinical decision support to reduce adverse drug events in acute kidney injury: a randomized, controlled trial. Appl Clin Inform 2012; 3 (02) 221-238.
  • 8 Buntin MB, Burke MF, Hoaglin MC, Blumenthal D. The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Aff (Millwood) 2011; 30 (03) 464-471.
  • 9 Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006; 144 (10) 742-752.
  • 10 Kern LM, Edwards AM, Pichardo M, Kaushal R. Electronic health records and health care quality over time in a federally qualified health center. J Am Med Inform Assoc 2015; 22 (02) 453-458.
  • 11 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 (01) 5-11.
  • 12 Singh H, Sittig DF. Measuring and improving patient safety through health information technology: The Health IT Safety Framework. BMJ Qual Saf 2016; 25 (04) 226-232.
  • 13 Steele AW, Eisert S, Witter J, Lyons P, Jones MA, Gabow P, Ortiz E. The effect of automated alerts on provider ordering behavior in an outpatient setting. PLoS Med 2005; 2 (09) e255.
  • 14 Office of the National Coordinator for Health Information Technology, Charles D, Gabriel M, Furukawa M. ONC Data Brief: No. 16. Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008–2013. May 2014 [cited 18 May 2016]; Available from: http://www.healthit.gov/sites/default/files/oncdatabrief16.pdf
  • 15 Lee EK, Mejia AF, Senior T, Jose J. Improving Patient Safety through Medical Alert Management: An Automated Decision Tool to Reduce Alert Fatigue. AMIA Annu Symp Proc 2010; 2010: 417-421.
  • 16 Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005; 293 (10) 1223-1238.
  • 17 Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005; 330 7494 765.
  • 18 Kirkendall ES, Kouril M, Minich T, Spooner SA. Analysis of electronic medication orders with large overdoses: opportunities for mitigating dosing errors. Appl Clin Inform 2014; 5 (01) 25-45.
  • 19 Ash JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annu Symp Proc 2007: 26-30.
  • 20 van der Sijs H, van Gelder T, Vulto A, Berg M, Aarts J. Understanding handling of drug safety alerts: a simulation study. Int J Med Inform 2010; 79 (05) 361-369.
  • 21 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 (15) 1311-1316.
  • 22 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.
  • 23 Kaushal R, Barker KN, Bates DW. How can information technology improve patient safety and reduce medication errors in children‘s health care?. Arch Pediatr Adolesc Med 2001; 155 (09) 1002-1007.
  • 24 Kaushal R, Bates DW, Landrigan C, McKenna KJ, Clapp MD, Federico F, Goldmann DA. Medication errors and adverse drug events in pediatric inpatients. JAMA 2001; 285 (16) 2114-2120.
  • 25 King WJ, Paice N, Rangrej J, Forestell GJ, Swartz R. The effect of computerized physician order entry on medication errors and adverse drug events in pediatric inpatients. Pediatrics 2003; 112 3 Pt 1 506-509.
  • 26 Phansalkar S, Edworthy J, Hellier E, Seger DL, Schedlbauer A, Avery AJ, Bates DW. A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems. J Am Med Inform Assoc 2010; 17 (05) 493-501.
  • 27 Schedlbauer A, Prasad V, Mulvaney C, Phansalkar S, Stanton W, Bates DW, Avery AJ. What evidence supports the use of computerized alerts and prompts to improve clinicians’ prescribing behavior?. J Am Med Inform Assoc 2009; 16 (04) 531-538.
  • 28 Koren G, Barzilay Z, Greenwald M. Tenfold errors in administration of drug doses: a neglected iatrogenic disease in pediatrics. Pediatrics 1986; 77 (06) 848-849.
  • 29 Kozer E, Scolnik D, Macpherson A, Keays T, Shi K, Luk T, Koren G. Variables associated with medication errors in pediatric emergency medicine. Pediatrics 2002; 110 (04) 737-742.
  • 30 Lesar TS. Tenfold medication dose prescribing errors. Ann Pharmacother 2002; 36 (12) 1833-1839.
  • 31 McPhillips H, Stille C, Smith D, Pearson J, Stull J, Hecht J, Andrade S, Miller M, Davis R. Methodological challenges in describing medication dosing errors in children. In: Henriksen K, Battles JB, Marks ES, Lewin DI. editors. Advances in patient safety : from research to implementation. Rockville, MD: Agency for Healthcare Research and Quality; 2005 Feb. p. 213-223.
  • 32 Wong IC, Ghaleb MA, Franklin BD, Barber N. Incidence and nature of dosing errors in paediatric medications: a systematic review. Drug Saf 2004; 27 (09) 661-670.
  • 33 Kirkendall ES, Kouril M, Dexheimer JW, Courter JD, Hagedorn P, Szczesniak R, Li D, Damania R. Automated identification of antibiotic overdoses and adverse drug events via analysis of prescribing alerts and medication administration records [In press]. J Am Med Inform Assoc. 2016
  • 34 Stultz JS, Porter K, Nahata MC. Prescription order risk factors for pediatric dosing alerts. Int J Med Inform 2015; 84 (02) 134-140.
  • 35 Beccaro MA, Villanueva R, Knudson KM, Harvey EM, Langle JM, Paul W. Decision Support Alerts for Medication Ordering in a Computerized Provider Order Entry (CPOE) System: A systematic approach to decrease alerts. Appl Clin Inform 2010; 1 (03) 346-362.
  • 36 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 (02) 138-147.
  • 37 Coleman JJ, van der Sijs H, Haefeli WE, Slight SP, McDowell SE, Seidling HM, Eiermann B, Aarts J, Ammenwerth E, Slee A, Ferner RE. On the alert: future priorities for alerts in clinical decision support for computerized physician order entry identified from a European workshop. BMC Med Inform Decis Mak 2013; 13: 111.
  • 38 Ruppert D, Wand MP, Carroll RJ. Semiparametric regression. Cambridge series in statistical and probabilistic mathematics. Cambridge ; New York: Cambridge University Press; 2003. Chapter 11. p. xvi, 386 p.
  • 39 Ngo L, Wand MP. Smoothing with Mixed Model Software. J Stat Softw 2004; 9 (01) 54.
  • 40 Dewan M, Wolfe H, Young C, Desai B. Payer formulary alerts as a cause of patient harm and the journey to change them. Hosp Pediatr 2016; 6 (09) 529-535.
  • 41 Horsky J, Zhang J, Patel VL. To err is not entirely human: complex technology and user cognition. J Biomed Inform 2005; 38 (04) 264-266.
  • 42 Cash JJ. Alert fatigue. Am J Health Syst Pharm 2009; 66 (23) 2098-2101.
  • 43 Harper MB, Longhurst CA, McGuire TL, Tarrago R, Desai BR, Patterson A. Core drug-drug interaction alerts for inclusion in pediatric electronic health records with computerized prescriber order entry. J Patient Saf 2014; 10 (01) 59-63.
  • 44 Simpao AF, Ahumada LM, Desai BR, Bonafide CP, Galvez JA, Rehman MA, Jawad AF, Palma KL, Shelov ED. Optimization of drug-drug interaction alert rules in a pediatric hospital‘s electronic health record system using a visual analytics dashboard. J Am Med Inform Assoc 2015; 22 (02) 361-369.
  • 45 Sittig DF, Wright A, Osheroff JA, Middleton B, Teich JM, Ash JS, Campbell E, Bates DW. Grand challenges in clinical decision support. J Biomed Inform 2008; 41 (02) 387-392.