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Published in: BMC Medical Informatics and Decision Making 1/2017

Open Access 01-12-2017 | Research article

Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system

Authors: Jessica S. Ancker, Alison Edwards, Sarah Nosal, Diane Hauser, Elizabeth Mauer, Rainu Kaushal, with the HITEC Investigators

Published in: BMC Medical Informatics and Decision Making | Issue 1/2017

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Abstract

Background

Although alert fatigue is blamed for high override rates in contemporary clinical decision support systems, the concept of alert fatigue is poorly defined. We tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time.

Methods

Retrospective cohort study using electronic health record data (both drug alerts and clinical practice reminders) from January 2010 through June 2013 from 112 ambulatory primary care clinicians. The cognitive overload hypotheses were that alert acceptance would be lower with higher workload (number of encounters, number of patients), higher work complexity (patient comorbidity, alerts per encounter), and more alerts low in informational value (repeated alerts for the same patient in the same year). The desensitization hypothesis was that, for newly deployed alerts, acceptance rates would decline after an initial peak.

Results

On average, one-quarter of drug alerts received by a primary care clinician, and one-third of clinical reminders, were repeats for the same patient within the same year. Alert acceptance was associated with work complexity and repeated alerts, but not with the amount of work. Likelihood of reminder acceptance dropped by 30% for each additional reminder received per encounter, and by 10% for each five percentage point increase in proportion of repeated reminders. The newly deployed reminders did not show a pattern of declining response rates over time, which would have been consistent with desensitization. Interestingly, nurse practitioners were 4 times as likely to accept drug alerts as physicians.

Conclusions

Clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert. Reducing within-patient repeats may be a promising target for reducing alert overrides and alert fatigue.
Literature
1.
go back to reference Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280(15):1311–6.CrossRefPubMed Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280(15):1311–6.CrossRefPubMed
2.
go back to reference 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(12):1409–16.CrossRefPubMed 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(12):1409–16.CrossRefPubMed
3.
go back to reference 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(1):29–40.CrossRefPubMedPubMedCentral 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(1):29–40.CrossRefPubMedPubMedCentral
4.
go back to reference Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363:501–4.CrossRefPubMed Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363:501–4.CrossRefPubMed
5.
go back to reference Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med. 2001;345(13):965–70.CrossRefPubMed Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med. 2001;345(13):965–70.CrossRefPubMed
6.
7.
go back to reference 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(2):138–47.CrossRefPubMedPubMedCentral 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(2):138–47.CrossRefPubMedPubMedCentral
8.
go back to reference 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(6):482–91.CrossRefPubMedPubMedCentral 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(6):482–91.CrossRefPubMedPubMedCentral
9.
go back to reference 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(6):e1970–3.CrossRefPubMed 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(6):e1970–3.CrossRefPubMed
10.
go back to reference 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):2625–31.CrossRefPubMed 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):2625–31.CrossRefPubMed
11.
go back to reference Oppenheim MI, Vidal C, Velasco FT, et al. Impact of a computerized alert during physician order entry on medication dosing in patients with renal impairment. In: Proceedings of the AMIA annual symposium. 2002. p. 577–81. Oppenheim MI, Vidal C, Velasco FT, et al. Impact of a computerized alert during physician order entry on medication dosing in patients with renal impairment. In: Proceedings of the AMIA annual symposium. 2002. p. 577–81.
12.
go back to reference Nanji KC, Slight SP, Seger DL, et al. Overrides of medication-related clinical decision support alerts in outpatients. Journal of the American Medical Informatics Association. 2013;21(3):487–91. Nanji KC, Slight SP, Seger DL, et al. Overrides of medication-related clinical decision support alerts in outpatients. Journal of the American Medical Informatics Association. 2013;21(3):487–91.
13.
go back to reference Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inform Assoc. 2004;11(2):104–12.CrossRefPubMedPubMedCentral Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inform Assoc. 2004;11(2):104–12.CrossRefPubMedPubMedCentral
14.
go back to reference Phansalkar S, van der Sijs H, Tucker AD, et al. 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(3):489–93.CrossRefPubMed Phansalkar S, van der Sijs H, Tucker AD, et al. 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(3):489–93.CrossRefPubMed
15.
go back to reference 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(5):361–9.CrossRefPubMed 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(5):361–9.CrossRefPubMed
16.
go back to reference Rayo MF, Moffatt-Bruce SD. Alarm system management: evidence-based guidance encouraging direct measurement of informativeness to improve alarm response. BMJ Qual Saf. 2015;24(4):282–86. Rayo MF, Moffatt-Bruce SD. Alarm system management: evidence-based guidance encouraging direct measurement of informativeness to improve alarm response. BMJ Qual Saf. 2015;24(4):282–86.
17.
go back to reference Dixon SR, Wickens CD, McCarley JS. How do automation false alarms and misses affect operator compliance and reliance? Proceedings of the human factors and ergonomics society 50th annual meeting, vol. 50. 2006. p. 25–9. Dixon SR, Wickens CD, McCarley JS. How do automation false alarms and misses affect operator compliance and reliance? Proceedings of the human factors and ergonomics society 50th annual meeting, vol. 50. 2006. p. 25–9.
18.
go back to reference Endsley M, Jones DG. Designing for situational awareness: an approach to user-centered design. 2nd ed. Boca Raton, FL: CRC Press, Taylor & Francis Group; 2004. Endsley M, Jones DG. Designing for situational awareness: an approach to user-centered design. 2nd ed. Boca Raton, FL: CRC Press, Taylor & Francis Group; 2004.
19.
go back to reference Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. J Am Med Inform Assoc. 2012;19(e1):e145–8.CrossRefPubMedPubMedCentral Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. J Am Med Inform Assoc. 2012;19(e1):e145–8.CrossRefPubMedPubMedCentral
20.
21.
go back to reference Simpao AF, Ahumada LM, Desai BR, et al. Optimization of drug–drug interaction alert rules in a pediatric hospital’s electronic health record system using a visual analytics dashboard. Journal of the Am Med Inform Assoc. 2014;22(2):361–69. Simpao AF, Ahumada LM, Desai BR, et al. Optimization of drug–drug interaction alert rules in a pediatric hospital’s electronic health record system using a visual analytics dashboard. Journal of the Am Med Inform Assoc. 2014;22(2):361–69.
22.
23.
go back to reference Miller AM, Boro MS, Korman NE, Davoren JB. Provider and pharmacist responses to warfarin drug–drug interaction alerts: a study of healthcare downstream of CPOE alerts. J Am Med Inform Assoc. 2011;18 Suppl 1:i45–50.CrossRefPubMedPubMedCentral Miller AM, Boro MS, Korman NE, Davoren JB. Provider and pharmacist responses to warfarin drug–drug interaction alerts: a study of healthcare downstream of CPOE alerts. J Am Med Inform Assoc. 2011;18 Suppl 1:i45–50.CrossRefPubMedPubMedCentral
24.
go back to reference Bryant AD, Fletcher GS, Payne TH. Drug interaction alert override rates in the meaningful use era. No evidence of progress. Appl Clin Inform. 2014;5(3):802–13.CrossRefPubMedPubMedCentral Bryant AD, Fletcher GS, Payne TH. Drug interaction alert override rates in the meaningful use era. No evidence of progress. Appl Clin Inform. 2014;5(3):802–13.CrossRefPubMedPubMedCentral
25.
go back to reference 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. 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.
26.
go back to reference Shah NR, Seger AC, Seger DL, et al. Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc. 2006;13(1):5–11.CrossRefPubMedPubMedCentral Shah NR, Seger AC, Seger DL, et al. Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc. 2006;13(1):5–11.CrossRefPubMedPubMedCentral
27.
go back to reference Lin C-P, 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(5):620–6.CrossRefPubMedPubMedCentral Lin C-P, 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(5):620–6.CrossRefPubMedPubMedCentral
28.
go back to reference Isaac T, Weissman JS, Davis RB, et al. Overrides of medication alerts in ambulatory care. Arch Intern Med. 2009;169(3):305–11.CrossRefPubMed Isaac T, Weissman JS, Davis RB, et al. Overrides of medication alerts in ambulatory care. Arch Intern Med. 2009;169(3):305–11.CrossRefPubMed
29.
go back to reference Ancker JS, Kern LM, Edwards A, et al. How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use. J Am Med Inform Assoc. 2014:epub ahead of print June 12, 2014. Ancker JS, Kern LM, Edwards A, et al. How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use. J Am Med Inform Assoc. 2014:epub ahead of print June 12, 2014.
30.
go back to reference Ancker JS, Kern LM, Edwards AM, et al. Associations between health care quality and use of electronic health record functions in ambulatory care. J Am Med Inform Assoc. 2015 In press. Ancker JS, Kern LM, Edwards AM, et al. Associations between health care quality and use of electronic health record functions in ambulatory care. J Am Med Inform Assoc. 2015 In press.
31.
go back to reference Weiner J, Starfield B, Steinwachs D, Mumford L. Development and application of a population-oriented measure of ambulatory care case-mix. Med Care. 1991;29(5):452–72.CrossRefPubMed Weiner J, Starfield B, Steinwachs D, Mumford L. Development and application of a population-oriented measure of ambulatory care case-mix. Med Care. 1991;29(5):452–72.CrossRefPubMed
32.
go back to reference Stultz JS, Nahata MC. Appropriateness of commercially available and partially customized medication dosing alerts among pediatric patients. J Am Med Inform Assoc. 2014;21(e1):e35–42.CrossRefPubMed Stultz JS, Nahata MC. Appropriateness of commercially available and partially customized medication dosing alerts among pediatric patients. J Am Med Inform Assoc. 2014;21(e1):e35–42.CrossRefPubMed
33.
go back to reference Feldman PH, McDonald MV. Exploring the utility of automated drug alerts in home health care. J Healthc Qual. 2006;28(1):29–40.CrossRefPubMed Feldman PH, McDonald MV. Exploring the utility of automated drug alerts in home health care. J Healthc Qual. 2006;28(1):29–40.CrossRefPubMed
34.
go back to reference Huber PJ. The behavior of maximum likelihood estimates under nonstandard conditions. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. 1967. Huber PJ. The behavior of maximum likelihood estimates under nonstandard conditions. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. 1967.
35.
go back to reference Rogers WH. Regression standard errors in clustered samples. In: Stata Technical Bulletin 13: 19–23..Stata Technical Bulletin Reprints. Vol 3. College Station, TX: Stata Press; 1993. p. 88–94. Rogers WH. Regression standard errors in clustered samples. In: Stata Technical Bulletin 13: 19–23..Stata Technical Bulletin Reprints. Vol 3. College Station, TX: Stata Press; 1993. p. 88–94.
36.
go back to reference Vulkan N. An economist’s perspective on probability matching. J Econ Surv. 2000;14(1):101–18.CrossRef Vulkan N. An economist’s perspective on probability matching. J Econ Surv. 2000;14(1):101–18.CrossRef
37.
go back to reference Voogdt-Pruis H, Van Ree J, Gorgels A, Beusmans G. Adherence to a guideline on cardiovascular prevention: a comparison between general practitioners and practice nurses. Int J Nurs Stud. 2011;48(7):798–807.CrossRefPubMed Voogdt-Pruis H, Van Ree J, Gorgels A, Beusmans G. Adherence to a guideline on cardiovascular prevention: a comparison between general practitioners and practice nurses. Int J Nurs Stud. 2011;48(7):798–807.CrossRefPubMed
38.
go back to reference Lenz ER, Mundinger MON, Hopkins SC, Lin SX, Smolowitz JL. Diabetes care processes and outcomes in patients treated by nurse practitioners or physicians. Diabetes Educ. 2002;28(4):590–8.CrossRefPubMed Lenz ER, Mundinger MON, Hopkins SC, Lin SX, Smolowitz JL. Diabetes care processes and outcomes in patients treated by nurse practitioners or physicians. Diabetes Educ. 2002;28(4):590–8.CrossRefPubMed
39.
go back to reference Martin G. Education and Training: Family Physicians and Nurse Practitioners. American Academy of Family Physicians. 2010. Leawood, KS. Martin G. Education and Training: Family Physicians and Nurse Practitioners. American Academy of Family Physicians. 2010. Leawood, KS.
40.
go back to reference Taylor LK, Tamblyn R. Reasons for physician non-adherence to electronic drug alerts. Stud Health Technol Inform. 2004;107(Pt 2):1101–5.PubMed Taylor LK, Tamblyn R. Reasons for physician non-adherence to electronic drug alerts. Stud Health Technol Inform. 2004;107(Pt 2):1101–5.PubMed
Metadata
Title
Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system
Authors
Jessica S. Ancker
Alison Edwards
Sarah Nosal
Diane Hauser
Elizabeth Mauer
Rainu Kaushal
with the HITEC Investigators
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2017
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-017-0430-8

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