The Impact of Customized Screening Intervals on the Burden of Drug-Drug Interaction Alerts: An Interrupted Time Series Analysis.
Advanced clinical decision support systems
Alert fatigue
Alert specificity
Clinical decision support systems
Drug interactions
Journal
Journal of medical systems
ISSN: 1573-689X
Titre abrégé: J Med Syst
Pays: United States
ID NLM: 7806056
Informations de publication
Date de publication:
30 Sep 2024
30 Sep 2024
Historique:
received:
24
05
2024
accepted:
25
09
2024
medline:
30
9
2024
pubmed:
30
9
2024
entrez:
30
9
2024
Statut:
epublish
Résumé
Fixed and broad screening intervals for drug-drug interaction (DDI) alerts lead to false positive alerts, thereby contributing to alert fatigue among healthcare professionals. Hence, we aimed to investigate the impact of customized screening intervals on the daily incidence of DDI alerts. An interrupted time series analysis was performed at the University Hospitals Leuven to evaluate the impact of a pragmatic intervention on the daily incidence of DDI alerts per 100 prescriptions. The study period encompassed 100 randomly selected days between April 2021 and December 2022. Preceding the intervention, a fixed and broad screening interval of 7 days before and after prescribing an interacting drug was applied. The intervention involved implementing customized screening intervals for a subset of highly prevalent or clinically relevant DDIs into the hospital information system. Additionally, the sensitivity of the tailored approach was evaluated. During the study period, a mean of 5731 (± 2909) new prescriptions per day was generated. The daily incidence of DDI alerts significantly decreased from 9.8% (95% confidence interval (CI) 8.4;11.1) before the intervention, to 6.3% (95% CI 5.4;7.2) afterwards, p < 0.0001. This corresponded to avoiding 201 (0.035*5731) false positive DDI alerts per day. Sensitivity was not compromised by our intervention. Defining and implementing customized screening intervals was feasible and effective in reducing the DDI alert burden without compromising sensitivity.
Identifiants
pubmed: 39347841
doi: 10.1007/s10916-024-02113-8
pii: 10.1007/s10916-024-02113-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
93Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Institute of Medicine Committee on Quality of Health Care in A. In: Kohn LT, Corrigan JM, Donaldson MS, editors. To Err is Human: Building a Safer Health System. Washington (DC): National Academies Press (US) Copyright 2000 by the National Academy of Sciences. All rights reserved.; 2000.
Bates DW, Levine DM, Salmasian H, Syrowatka A, Shahian DM, Lipsitz S, et al. The Safety of Inpatient Health Care. N Engl J Med. 2023;388(2):142–53. PMID: 36630622. doi: https://doi.org/10.1056/NEJMsa2206117 .
doi: 10.1056/NEJMsa2206117
pubmed: 36630622
Krähenbühl-Melcher A, Schlienger R, Lampert M, Haschke M, Drewe J, Krähenbühl S. Drug-related problems in hospitals: a review of the recent literature. Drug Saf. 2007;30(5):379–407. PMID: 17472418. doi: https://doi.org/10.2165/00002018-200730050-00003 .
doi: 10.2165/00002018-200730050-00003
pubmed: 17472418
Magro L, Moretti U, Leone R. Epidemiology and characteristics of adverse drug reactions caused by drug-drug interactions. Expert Opin Drug Saf. 2012;11(1):83–94. PMID: 22022824. doi: https://doi.org/10.1517/14740338.2012.631910 .
doi: 10.1517/14740338.2012.631910
pubmed: 22022824
Hennessy S, Leonard CE, Gagne JJ, Flory JH, Han X, Brensinger CM, et al. Pharmacoepidemiologic Methods for Studying the Health Effects of Drug-Drug Interactions. Clin Pharmacol Ther. 2016;99(1):92–100. PMID: 26479278. doi: https://doi.org/10.1002/cpt.277 .
doi: 10.1002/cpt.277
pubmed: 26479278
Vélez-Díaz-Pallarés M, Pérez-Menéndez-Conde C, Bermejo-Vicedo T. Systematic review of computerized prescriber order entry and clinical decision support. Am J Health Syst Pharm. 2018;75(23):1909–21. PMID: 30463867. doi: https://doi.org/10.2146/ajhp170870 .
doi: 10.2146/ajhp170870
pubmed: 30463867
Roumeliotis N, Sniderman J, Adams-Webber T, Addo N, Anand V, Rochon P, et al. Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis. J Gen Intern Med. 2019;34(10):2210-23. PMID: 31396810. doi: https://doi.org/10.1007/s11606-019-05236-8 .
Kwan JL, Lo L, Ferguson J, Goldberg H, Diaz-Martinez JP, Tomlinson G, et al. Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials. Bmj. 2020;370:m3216. PMID: 32943437. doi: https://doi.org/10.1136/bmj.m3216 .
Nabovati E, Vakili-Arki H, Taherzadeh Z, Saberi MR, Medlock S, Abu-Hanna A, et al. Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects. J Med Syst. 2017;41(1):12. PMID: 27889873. doi: https://doi.org/10.1007/s10916-016-0649-4 .
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 Mar-Apr;13(2):138–47. PMID: 16357358. doi: https://doi.org/10.1197/jamia.M1809 .
doi: 10.1197/jamia.M1809
pubmed: 16357358
pmcid: 1447540
Genco EK, Forster JE, Flaten H, Goss F, Heard KJ, Hoppe J, et al. Clinically Inconsequential Alerts: The Characteristics of Opioid Drug Alerts and Their Utility in Preventing Adverse Drug Events in the Emergency Department. Ann Emerg Med. 2016;67(2):240-8.e3. PMID: 26553282. doi: https://doi.org/10.1016/j.annemergmed.2015.09.020 .
Villa Zapata L, Subbian V, Boyce RD, Hansten PD, Horn JR, Gephart SM, et al. Overriding Drug-Drug Interaction Alerts in Clinical Decision Support Systems: A Scoping Review. Stud Health Technol Inform. 2022;290:380–4. PMID: 35673040. doi: https://doi.org/10.3233/shti220101 .
doi: 10.3233/shti220101
pubmed: 35673040
Van De Sijpe G, Quintens C, Walgraeve K, Van Laer E, Penny J, De Vlieger G, et al. Overall performance of a drug-drug interaction clinical decision support system: quantitative evaluation and end-user survey. BMC Med Inform Decis Mak. 2022;22(1):48. PMID: 35193547. doi: https://doi.org/10.1186/s12911-022-01783-z .
Tolley CL, Slight SP, Husband AK, Watson N, Bates DW. Improving medication-related clinical decision support. Am J Health Syst Pharm. 2018;75(4):239–46. PMID: 29436470. doi: https://doi.org/10.2146/ajhp160830 .
doi: 10.2146/ajhp160830
pubmed: 29436470
Shah SN, Seger DL, Fiskio JM, Horn JR, Bates DW. Comparison of Medication Alerts from Two Commercial Applications in the USA. Drug Saf. 2021;44(6):661–8. PMID: 33616888. doi: https://doi.org/10.1007/s40264-021-01048-0 .
doi: 10.1007/s40264-021-01048-0
pubmed: 33616888
pmcid: 8184526
Chou E, Boyce RD, Balkan B, Subbian V, Romero A, Hansten PD, et al. Designing and evaluating contextualized drug-drug interaction algorithms. JAMIA Open. 2021;4(1):ooab023. PMID: 33763631. doi: https://doi.org/10.1093/jamiaopen/ooab023 .
Horn J, Ueng S. The Effect of Patient-Specific Drug-Drug Interaction Alerting on the Frequency of Alerts: A Pilot Study. Ann Pharmacother. 2019;53(11):1087–92. PMID: 31296026. doi: https://doi.org/10.1177/1060028019863419 .
doi: 10.1177/1060028019863419
pubmed: 31296026
Ledger TS, Brooke-Cowden K, Coiera E. Post-implementation optimization of medication alerts in hospital computerized provider order entry systems: a scoping review. J Am Med Inform Assoc. 2023;30(12):2064-71. PMID: 37812769. doi: https://doi.org/10.1093/jamia/ocad193 .
Mille F, Schwartz C, Brion F, Fontan JE, Bourdon O, Degoulet P, et al. Analysis of overridden alerts in a drug-drug interaction detection system. Int J Qual Health Care. 2008;20(6):400-5. PMID: 18784269. doi: https://doi.org/10.1093/intqhc/mzn038 .
Bhakta SB, Colavecchia AC, Haines L, Varkey D, Garey KW. A systematic approach to optimize electronic health record medication alerts in a health system. Am J Health Syst Pharm. 2019;76(8):530–6. PMID: 31361861. doi: https://doi.org/10.1093/ajhp/zxz012 .
doi: 10.1093/ajhp/zxz012
pubmed: 31361861
Helmons PJ, Suijkerbuijk BO, Nannan Panday PV, Kosterink JG. Drug-drug interaction checking assisted by clinical decision support: a return on investment analysis. J Am Med Inform Assoc. 2015;22(4):764–72. PMID: 25670751. doi: https://doi.org/10.1093/jamia/ocu010 .
doi: 10.1093/jamia/ocu010
pubmed: 25670751
Askari M, Eslami S, Louws M, Wierenga PC, Dongelmans DA, Kuiper RA, et al. Frequency and nature of drug-drug interactions in the intensive care unit. Pharmacoepidemiology and Drug Safety. 2013 2013/04/01;22(4):430–7. doi: https://doi.org/10.1002/pds.3415 .
doi: 10.1002/pds.3415
pubmed: 23420793
Kiesel LM, Bertsche A, Kiess W, Siekmeyer M, Bertsche T, Neininger MP. Drug–Drug Interactions Involving High-Alert Medications that Lead to Interaction-Associated Symptoms in Pediatric Intensive Care Patients: A Retrospective Study. Pediatric Drugs. 2024 2024/07/04. doi: https://doi.org/10.1007/s40272-024-00641-x .
Bakker T, Abu-Hanna A, Dongelmans DA, Vermeijden WJ, Bosman RJ, de Lange DW, et al. Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study. Journal of Critical Care. 2021 2021/04/01/;62:124 – 30. doi: https://doi.org/10.1016/j.jcrc.2020.11.020 .
Wasylewicz ATM, van de Burgt BWM, Manten T, Kerskes M, Compagner WN, Korsten EHM, et al. Contextualized Drug-Drug Interaction Management Improves Clinical Utility Compared With Basic Drug-Drug Interaction Management in Hospitalized Patients. Clin Pharmacol Ther. 2022;112(2):382–90. PMID: 35486411. doi: https://doi.org/10.1002/cpt.2624 .
doi: 10.1002/cpt.2624
pubmed: 35486411
pmcid: 9540177
Muylle KM, Gentens K, Dupont AG, Cornu P. Evaluation of an optimized context-aware clinical decision support system for drug-drug interaction screening. Int J Med Inform. 2021;148:104393. PMID: 33486355. doi: https://doi.org/10.1016/j.ijmedinf.2021.104393 .
Resetar E, Reichley RM, Noirot LA, Dunagan WC, Bailey TC, editors. Customizing a commercial rule base for detecting drug-drug interactions. 2005: American Medical Informatics Association.
Reese T, Wright A, Liu S, Boyce R, Romero A, Del Fiol G, et al. Improving the specificity of drug-drug interaction alerts: Can it be done? Am J Health Syst Pharm. 2022;79(13):1086-95. PMID: 35136935. doi: https://doi.org/10.1093/ajhp/zxac045 .
Seidling HM, Klein U, Schaier M, Czock D, Theile D, Pruszydlo MG, et al. What, if all alerts were specific - estimating the potential impact on drug interaction alert burden. Int J Med Inform. 2014;83(4):285–91. PMID: 24484781. doi: https://doi.org/10.1016/j.ijmedinf.2013.12.006 .
doi: 10.1016/j.ijmedinf.2013.12.006
pubmed: 24484781
Bakker T, Klopotowska JE, Dongelmans DA, Eslami S, Vermeijden WJ, Hendriks S, et al. The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial. The Lancet. 2024 2024/01/20/. doi: https://doi.org/10.1016/S0140-6736(23)02465-0 .
Quintens C, De Rijdt T, Van Nieuwenhuyse T, Simoens S, Peetermans WE, Van den Bosch B, et al. Development and implementation of “Check of Medication Appropriateness” (CMA): advanced pharmacotherapy-related clinical rules to support medication surveillance. BMC Med Inform Decis Mak. 2019;19(1):29. PMID: 30744674. doi: https://doi.org/10.1186/s12911-019-0748-5 .
Quintens C, Van de Sijpe G, Van der Linden L, Spriet I. Computerised prescribing support still needs a human touch. Age and Ageing. 2020. doi: https://doi.org/10.1093/ageing/afaa200 .
doi: 10.1093/ageing/afaa200
Quintens C, Peetermans WE, Lagrou K, Declercq P, Schuermans A, Debaveye Y, et al. The effectiveness of Check of Medication Appropriateness for antimicrobial stewardship: an interrupted time series analysis. J Antimicrob Chemother. 2021 Oct 7. PMID: 34618025. doi: https://doi.org/10.1093/jac/dkab364 .
Quintens C, Verhamme P, Vanassche T, Vandenbriele C, Van den Bosch B, Peetermans WE, et al. Improving appropriate use of anticoagulants in hospitalised patients: A pharmacist-led Check of Medication Appropriateness intervention. Br J Clin Pharmacol. 2022;88(6):2959–68. PMID: 34913184. doi: https://doi.org/10.1111/bcp.15184 .
doi: 10.1111/bcp.15184
pubmed: 34913184
Quintens C, De Coster J, Van der Linden L, Morlion B, Nijns E, Van den Bosch B, et al. Impact of Check of Medication Appropriateness (CMA) in optimizing analgesic prescribing: An interrupted time series analysis. Eur J Pain. 2021;25(3):704–13. PMID: 33259703. doi: https://doi.org/10.1002/ejp.1705 .
doi: 10.1002/ejp.1705
pubmed: 33259703
Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299–309. PMID: 12174032. doi: https://doi.org/10.1046/j.1365-2710.2002.00430.x .
doi: 10.1046/j.1365-2710.2002.00430.x
pubmed: 12174032
Kane-Gill SL, O’Connor MF, Rothschild JM, Selby NM, McLean B, Bonafide CP, et al. Technologic Distractions (Part 1): Summary of Approaches to Manage Alert Quantity With Intent to Reduce Alert Fatigue and Suggestions for Alert Fatigue Metrics. Critical Care Medicine. 2017;45(9).
Payne TH, Hines LE, Chan RC, Hartman S, Kapusnik-Uner J, Russ AL, et al. Recommendations to improve the usability of drug-drug interaction clinical decision support alerts. J Am Med Inform Assoc. 2015;22(6):1243–50. PMID: 25829460. doi: https://doi.org/10.1093/jamia/ocv011 .
doi: 10.1093/jamia/ocv011
pubmed: 25829460
Edrees H, Amato MG, Wong A, Seger DL, Bates DW. High-priority drug-drug interaction clinical decision support overrides in a newly implemented commercial computerized provider order-entry system: Override appropriateness and adverse drug events. J Am Med Inform Assoc. 2020;27(6):893–900. PMID: 32337561. doi: https://doi.org/10.1093/jamia/ocaa034 .
doi: 10.1093/jamia/ocaa034
pubmed: 32337561
pmcid: 7647273
Wong A, Amato MG, Seger DL, Rehr C, Wright A, Slight SP, et al. Prospective evaluation of medication-related clinical decision support over-rides in the intensive care unit. BMJ Qual Saf. 2018;27(9):718–24. PMID: 29440481. doi: https://doi.org/10.1136/bmjqs-2017-007531 .
doi: 10.1136/bmjqs-2017-007531
pubmed: 29440481
Amaral ACK-B, Cuthbertson BH. The efficiency of computerised clinical decision support systems. The Lancet. doi: https://doi.org/10.1016/S0140-6736(23)02839-8 .
Vandael E, Vandenberk B, Vandenberghe J, Van den Bosch B, Willems R, Foulon V. A smart algorithm for the prevention and risk management of QTc prolongation based on the optimized RISQ-PATH model. Br J Clin Pharmacol. 2018;84(12):2824–35. PMID: 30112769. doi: https://doi.org/10.1111/bcp.13740 .
doi: 10.1111/bcp.13740
pubmed: 30112769
pmcid: 6255989
Eppenga WL, Derijks HJ, Conemans JM, Hermens WA, Wensing M, De Smet PA. Comparison of a basic and an advanced pharmacotherapy-related clinical decision support system in a hospital care setting in the Netherlands. J Am Med Inform Assoc. 2012 Jan-Feb;19(1):66–71. PMID: 21890873. doi: https://doi.org/10.1136/amiajnl-2011-000360 .
doi: 10.1136/amiajnl-2011-000360
pubmed: 21890873
Duke JD, Li X, Dexter P. Adherence to drug-drug interaction alerts in high-risk patients: a trial of context-enhanced alerting. J Am Med Inform Assoc. 2013;20(3):494–8. PMID: 23161895. doi: https://doi.org/10.1136/amiajnl-2012-001073 .
doi: 10.1136/amiajnl-2012-001073
pubmed: 23161895
Parke C, Santiago E, Zussy B, Klipa D. Reduction of clinical support warnings through recategorization of severity levels. Am J Health Syst Pharm. 2015;72(2):144–8. PMID: 25550138. doi: https://doi.org/10.2146/ajhp140095 .
doi: 10.2146/ajhp140095
pubmed: 25550138
Paterno MD, Maviglia SM, Gorman PN, Seger DL, Yoshida E, Seger AC, et al. Tiering drug-drug interaction alerts by severity increases compliance rates. J Am Med Inform Assoc. 2009 Jan-Feb;16(1):40–6. PMID: 18952941. doi: https://doi.org/10.1197/jamia.M2808 .
doi: 10.1197/jamia.M2808
pubmed: 18952941
pmcid: 2605599
Bakker T, Dongelmans DA, Nabovati E, Eslami S, de Keizer NF, Abu-Hanna A, et al. Heterogeneity in the Identification of Potential Drug-Drug Interactions in the Intensive Care Unit: A Systematic Review, Critical Appraisal, and Reporting Recommendations. J Clin Pharmacol. 2022;62(6):706–20. PMID: 34957573. doi: https://doi.org/10.1002/jcph.2020 .
doi: 10.1002/jcph.2020
pubmed: 34957573
pmcid: 9303874
van der Sijs H, Lammers L, van den Tweel A, Aarts J, Berg M, Vulto A, et al. Time-dependent Drug–Drug Interaction Alerts in Care Provider Order Entry: Software May Inhibit Medication Error Reductions. Journal of the American Medical Informatics Association. 2009 2009/11/01/;16(6):864–8. doi: https://doi.org/10.1197/jamia.M2810 .
Poly TN, Islam MM, Yang HC, Li YJ. Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review. JMIR Med Inform. 2020;8(7):e15653. PMID: 32706721. doi: https://doi.org/10.2196/15653 .
doi: 10.2196/15653
pubmed: 32706721
pmcid: 7400042
Nanji KC, Seger DL, Slight SP, Amato MG, Beeler PE, Her QL, et al. Medication-related clinical decision support alert overrides in inpatients. J Am Med Inform Assoc. 2018;25(5):476–81. PMID: 29092059. doi: https://doi.org/10.1093/jamia/ocx115 .
doi: 10.1093/jamia/ocx115
pubmed: 29092059