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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2018

Open Access 01-12-2018 | Research article

Reliability, ease of use and usefulness of I-MeDeSA for evaluating drug-drug interaction alerts in an Australian context

Authors: Melissa T Baysari, David Lowenstein, Wu Yi Zheng, Richard O Day

Published in: BMC Medical Informatics and Decision Making | Issue 1/2018

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Abstract

Background

Recently, attention has shifted to improving the design of computerized alerts via the incorporation of human factors design principles. The Instrument for Evaluating Human Factors Principles in Medication-Related Decision Support Alerts (I-MeDeSA) is a tool developed in the United States to guide improvements to alert design and facilitate selection of electronic systems with superior design. In this study, we aimed to determine the reliability, ease of use and usefulness of I-MeDeSA for assessing drug-drug interaction (DDI) alerts in an Australian context.

Methods

Using the I-MeDeSA, three reviewers independently evaluated DDI alert interfaces of seven electronic systems used in Australia. Inter-rater reliability was assessed and reviewers met to discuss difficulties in using I-MeDeSA and the tool’s usefulness.

Results

Inter-rater reliability was high (Krippendorff’s alpha = 0.76), however, ambiguous wording and the inclusion of conditional items impacted ease of use. A number of items were not relevant to Australian implementations and as a result, most systems achieved an I-MeDeSA score of less than 50%.

Conclusions

The I-MeDeSA proved to be reliable, but item wording and structure made application difficult. Future studies should investigate potential modifications to the I-MeDeSA to improve ease of use and increase applicability to a variety of system configurations.
Appendix
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Literature
1.
Zwart-van Rijkom J, Uijtendaal E, ten Berg M, van Solinge W, Egberts A. Frequency and nature of drug-drug interactions in a Dutch univeristy hospital. Br J Clin Pharmacol. 2009;68(2):187–93.CrossRef
2.
Guédon-Moreau L, Ducrocq D, Duc M-F, Quieureux Y, L’Hôte C, Deligne J, Caron J. Absolute contraindications in relation to potential drug interactions in outpatient prescriptions: analysis of the first five million prescriptions in 1999. Eur J Clin Pharmacol. 2003;59(8):689–95.CrossRef
3.
Pirmohamed M, James S, Meakin S, Green C, Scott AK, Walley TJ, Farrar K, Park BK, Breckenridge AM. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ (Clinical research ed). 2004;329(7456):15–9.CrossRef
4.
Leone R, Magro L, Moretti U, Cutroneo P, Moschini M, Motola D, Tuccori M, Conforti A. Identifying adverse drug reactions associated with drug-drug interactions. Drug Saf. 2010;33(8):667–75.CrossRef
5.
Dechanont S, Maphanta S, Butthum B, Kongkaew C. Hospital admissions/visits associated with drug-drug interactions: a systematic review and meta-analysis. Pharmacoepidemiol Drug Saf. 2014;23(5):489–97.CrossRef
6.
Ko Y, Malone D, Skrepnek G. Prescribers’ knowledge of and sources of information for potential drug-drug interactions; a postal survey of US prescribers. Drug Saf. 2008;31:525–36.CrossRef
7.
Bates DW, Cullen DJ, Laird N, et al. Incidence of adverse drug events and potential adverse drug events: implications for prevention. JAMA. 1995;274(1):29–34.CrossRef
8.
Payne TH, Nichol WP, Hoey P, Savarino J. Characteristics and override rates of order checks in a practitioner order entry system. Proceedings of the AMIA Symposium. 2002:602–6.
9.
Weingart SN, Simchowitz B, Padolsky H, et al. AN empirical model to estimate the potential impact of medication safety alerts on patient safety, health care utilization, and cost in ambulatory care. Arch Intern Med. 2009;169(16):1465–73.CrossRef
10.
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(1):29–40.CrossRef
11.
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.CrossRef
12.
Glassman PA, Simon B, Belperio P, Lanto A. Improving recognition of drug interactions: benefits and barriers to using automated drug alerts. Med Care. 2002;40(12):1161–71.CrossRef
13.
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):676–80.CrossRef
14.
Coleman JJ, van der Sijs H, Haefeli WE, Slight SP, McDowell SE, Seidling HM, Eiermann B, Aarts J, Ammenwerth E, Ferner RE, et al. 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(1):1–8.CrossRef
15.
Payne TH, Hines LE, Chan RC, Hartman S, Kapusnik-Uner J, Russ AL, Chaffee BW, Hartman C, Tamis V, Galbreth B, 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.CrossRef
16.
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(5):493–501.CrossRef
17.
Seidling HM, Phansalkar S, Seger DL, Paterno MD, Shaykevich S, Haefeli WE, Bates DW. Factors influencing alert acceptance: a novel approach for predicting the success of clinical decision support. J Am Med Inform Assoc. 2011;18(4):479–84.CrossRef
18.
Zachariah M, Phansalkar S, Seidling HM, Neri PM, Cresswell KM, Duke J, Bloomrosen M, Volk LA, Bates DW. Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems—I-MeDeSA. J Am Med Inform Assoc. 2011;18(Supplement 1):i62–72.CrossRef
19.
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):e332–40.CrossRef
20.
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(2):571–88.CrossRef
21.
Baysari MT, Westbrook JI, Richardson KL, Day RO. The influence of computerized decision support on prescribing during ward-rounds: are the decision-makers targeted? JAMIA. 2011;18:754–9.PubMed
22.
Iarossi G. The power of survey design: A User’s Guide for Managing Surveys, Interpeting Results and Influencing Respondents: World Bank Publications; 2006.
Metadata
Title
Reliability, ease of use and usefulness of I-MeDeSA for evaluating drug-drug interaction alerts in an Australian context
Authors
Melissa T Baysari
David Lowenstein
Wu Yi Zheng
Richard O Day
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2018
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-018-0666-y

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