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DOI: 10.1055/s-0044-1782534
Factors Influencing Health Care Professionals' Perceptions of Frequent Drug–Drug Interaction Alerts
Authors
Funding No funding was received.
Abstract
Background Drug–drug interactions (DDIs) remain a highly prevalent issue for patients in both community and hospital settings. Electronic medication management systems have implemented DDI alerts to mitigate DDI-related harm from occurring.
Objectives The primary aim of this study was to explore factors that influence health care professionals' (hospital doctors, hospital pharmacists, general practitioners, and community pharmacists) perceptions and action taken by them in response to DDI alerts.
Methods A qualitative study was conducted using semi-structured interviews between early January and late February 2021. The top 20 most frequently triggered DDI alerts previously identified were used as examples of alert prompts shown to participants.
Results A total of 20 participants were recruited. General practitioners (n = 4) were most likely to consider DDI alerts to be clinically relevant and important, and hospital doctors (n = 4) were most likely to consider these alerts not being clinically relevant nor important. Three main factors were identified to influence health care professionals' perceptions of DDI alerts, which included clinical relevance, visual presentation, and content of alerts.
Conclusion Health care professionals' perceptions of DDI alerts are influenced by multiple factors and considerations are required to create tailored alerts for users and their clinical contexts. Improvement in DDI alerts should be a priority to improve patient medication safety and health outcomes.
Protection of Human and Animal Subjects
This study was conducted at the Royal Prince Alfred Hospital as authorized by Sydney Local Health District (protocol number: X20-0533).
Publication History
Received: 16 March 2023
Accepted: 26 January 2024
Article published online:
31 March 2024
© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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References
- 1 Roughead L, Semple S. Literature Review: Medication Safety in Acute Care in Australia. 2013. Adelaide: Australia: Sansom Institute, University of South;
- 2 Missiakos O, Baysari MT, Day RO. Identifying effective computerized strategies to prevent drug-drug interactions in hospital: a user-centered approach. Int J Med Inform 2015; 84 (08) 595-600
- 3 Westbrook JI, Reckmann M, Li L. et al. Effects of two commercial electronic prescribing systems on prescribing error rates in hospital in-patients: a before and after study. PLoS Med 2012; 9 (01) e1001164
- 4 Lowenstein D, Zheng WY, Burke R. et al. Do user preferences align with human factors assessment scores of drug-drug interaction alerts?. Health Informatics J 2020; 26 (01) 563-575
- 5 Page NJB, Baysari MT, Westbrook JI. Selection and use of decision support alerts in electronic medication management systems in Australian hospitals: a survey of implementers. J Pharm Pract Res 2019; 49 (02) 142-149
- 6 Nabovati E, Vakili-Arki H, Taherzadeh Z. et al. Information technology-based interventions to improve drug-drug interaction outcomes: a systematic review on features and effects. J Med Syst 2017; 41 (01) 12
- 7 Humphrey K, Jorina M, Harper M, Dodson B, Kim S-Y, Ozonoff A. An investigation of drug-drug interaction alert overrides at a pediatric hospital. Hosp Pediatr 2018; 8 (05) 293-299
- 8 Slight SP, Seger DL, Nanji KC. et al. Are we heeding the warning signs? Examining providers' overrides of computerized drug-drug interaction alerts in primary care. PLoS One 2013; 8 (12) e85071
- 9 Yeh M-L, Chang Y-J, Wang P-Y, Li Y-C, Hsu C-Y. Physicians' responses to computerized drug-drug interaction alerts for outpatients. Comput Methods Programs Biomed 2013; 111 (01) 17-25
- 10 Van De Sijpe G, Quintens C, Walgraeve K. 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 (01) 48
- 11 Wright A, McEvoy DS, Aaron S. et al. Structured override reasons for drug-drug interaction alerts in electronic health records. J Am Med Inform Assoc 2019; 26 (10) 934-942
- 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 Cho I, Lee Y, Lee J-H, Bates DW. Wide variation and patterns of physicians' responses to drug-drug interaction alerts. Int J Qual Health Care 2019; 31 (02) 89-95
- 14 Phansalkar S, Zachariah M, Seidling HM, Mendes C, Volk L, Bates DW. Evaluation of medication alerts in electronic health records for compliance with human factors principles. J Am Med Inform Assoc 2014; 21 (e2): e332-e340
- 15 Cho I, Lee J, Han H, Phansalkar S, Bates DW. Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA. Appl Clin Inform 2014; 5 (02) 571-588
- 16 Bagri H, Dahri K, Legal M. Hospital pharmacists' perceptions and decision-making related to drug-drug interactions. Can J Hosp Pharm 2019; 72 (04) 288-294
- 17 Fung KW, Kapusnik-Uner J, Cunningham J, Higby-Baker S, Bodenreider O. Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support. J Am Med Inform Assoc 2017; 24 (04) 806-812
- 18 Ko Y, Abarca J, Malone DC. et al. Practitioners' views on computerized drug-drug interaction alerts in the VA system. J Am Med Inform Assoc 2007; 14 (01) 56-64
- 19 Van Dort BA, Zheng WY, Baysari MT. Prescriber perceptions of medication-related computerized decision support systems in hospitals: a synthesis of qualitative research. Int J Med Inform 2019; 129: 285-295
- 20 Gatenby J, Blomqvist M, Burke R, Ritchie A, Gibson K, Patanwala AE. Adverse events targeted by drug-drug interaction alerts in hospitalized patients. Int J Med Inform 2020; 143: 104266
- 21 Given LM. 100 Questions (and Answers) about Qualitative Research. Thousand Oaks, CA: SAGE publications; 2015
- 22 Braun V, Clarke V. Thematic analysis. In: Cooper H, Camic PM, Long DL, Panter AT, Rindskopf D, Sher KJ. eds. APA Handbook of Research Methods in Psychology, Vol. 2. Research Designs: Quantitative, Qualitative, Neuropsychological, and Biological. Worchester, MA: American Psychological Association; 2012: 57-71
- 23 O'Connor C, Joffe H. Intercoder reliability in qualitative research: debates and practical guidelines. Int J Qual Methods 2020; 19: 1609406919899220
- 24 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
- 25 Chou E, Boyce RD, Balkan B. et al. Designing and evaluating contextualized drug-drug interaction algorithms. JAMIA Open 2021; 4 (01) ooab023
- 26 Pirnejad H, Amiri P, Niazkhani Z. et al. Preventing potential drug-drug interactions through alerting decision support systems: a clinical context based methodology. Int J Med Inform 2019; 127: 18-26
- 27 Feldstein A, Simon SR, Schneider J. et al. How to design computerized alerts to safe prescribing practices. Jt Comm J Qual Saf 2004; 30 (11) 602-613
- 28 Luna DR, Rizzato Lede DA, Otero CM, Risk MR, González Bernaldo de Quirós F. User-centered design improves the usability of drug-drug interaction alerts: Experimental comparison of interfaces. J Biomed Inform 2017; 66: 204-213
- 29 Baysari MT, Lowenstein D, Zheng WY, Day RO. Reliability, ease of use and usefulness of I-MeDeSA for evaluating drug-drug interaction alerts in an Australian context. BMC Med Inform Decis Mak 2018; 18 (01) 83
- 30 Payne TH, Hines LE, Chan RC. et al. Recommendations to improve the usability of drug-drug interaction clinical decision support alerts. J Am Med Inform Assoc 2015; 22 (06) 1243-1250
- 31 Yu KH, Sweidan M, Williamson M, Fraser A. Drug interaction alerts in software–what do general practitioners and pharmacists want?. Med J Aust 2011; 195 (11–12): 676-680
- 32 Abarca J, Malone DC, Skrepnek GH. et al. Community pharmacy managers' perception of computerized drug-drug interaction alerts. J Am Pharm Assoc (Wash DC) 2006; 46 (02) 148-153
- 33 Indermitte J, Erba L, Beutler M, Bruppacher R, Haefeli WE, Hersberger KE. Management of potential drug interactions in community pharmacies: a questionnaire-based survey in Switzerland. Eur J Clin Pharmacol 2007; 63 (03) 297-305
- 34 Humphrey KE, Mirica M, Phansalkar S, Ozonoff A, Harper MB. Clinician perceptions of timing and presentation of drug-drug interaction alerts. Appl Clin Inform 2020; 11 (03) 487-496
- 35 Moxey A, Robertson J, Newby D, Hains I, Williamson M, Pearson S-A. Computerized clinical decision support for prescribing: provision does not guarantee uptake. J Am Med Inform Assoc 2010; 17 (01) 25-33
- 36 Jung M, Riedmann D, Hackl WO. et al. Physicians' perceptions on the usefulness of contextual information for prioritizing and presenting alerts in computerized physician order entry systems. BMC Med Inform Decis Mak 2012; 12: 111-111
- 37 Knight AM, Maygers J, Foltz KA, John IS, Yeh HC, Brotman DJ. The effect of eliminating intermediate severity drug-drug interaction alerts on overall medication alert burden and acceptance rate. Appl Clin Inform 2019; 10 (05) 927-934