ABSTRACT
OBJECTIVES: (1) Characterize persistent hazards and inefficiencies in inpatient medication administration; (2) Explore cognitive attributes of medication administration tasks; and (3) Discuss strategies to reduce medication administration technology-related hazards. MATERIALS AND METHODS: Interviews were conducted with 32 nurses practicing at 2 urban, eastern and western US health systems. Qualitative analysis using inductive and deductive coding included consensus discussion, iterative review, and coding structure revision. We abstracted hazards and inefficiencies through the lens of risks to patient safety and the cognitive perception-action cycle (PAC). RESULTS: Persistent safety hazards and inefficiencies related to MAT organized around the PAC cycle included: (1) Compatibility constraints create information silos; (2) Missing action cues; (3) Intermittent communication flow between safety monitoring systems and nurses; (4) Occlusion of important alerts by other, less helpful alerts; (5) Dispersed information: Information required for tasks is not collocated; (6) Inconsistent data organization: Mismatch of the display and the user's mental model; (7) Hidden medication administration technologies (MAT) limitations: Inaccurate beliefs about MAT functionality contribute to overreliance on the technology; (8) Software rigidity causes workarounds; (9) Cumbersome dependencies between technology and the physical environment; and (10) Technology breakdowns require adaptive actions. DISCUSSION: Errors might persist in medication administration despite successful Bar Code Medication Administration and Electronic Medication Administration Record deployment for reducing errors. Opportunities to improve MAT require a deeper understanding of high-level reasoning in medication administration, including control over the information space, collaboration tools, and decision support. CONCLUSION: Future medication administration technology should consider a deeper understanding of nursing knowledge work for medication administration.
Subject(s)
Medication Errors , Patient Safety , Humans , Medication Errors/prevention & control , Pharmaceutical Preparations , Electronic Data Processing , Communication , Medication Systems, HospitalABSTRACT
BACKGROUND: Although electronic medication administration records (eMARs) and bar-coded medication administration (BCMA) have improved medication safety, poor usability of these technologies can increase patient safety risks. OBJECTIVES: The objective of our systematic review was to identify the impact of eMAR and BCMA design on usability, operationalized as efficiency, effectiveness, and satisfaction. METHODS: We retrieved peer-reviewed journal articles on BCMA and eMAR quantitative usability measures from PsycInfo and MEDLINE (1946-August 20, 2019), and EMBASE (1976-October 23, 2019). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we screened articles, extracted and categorized data into the usability categories of effectiveness, efficiency, and satisfaction, and evaluated article quality. RESULTS: We identified 1,922 articles and extracted data from 41 articles. Twenty-four articles (58.5%) investigated BCMA only, 10 (24.4%) eMAR only, and seven (17.1%) both BCMA and eMAR. Twenty-four articles (58.5%) measured effectiveness, 8 (19.5%) efficiency, and 17 (41.5%) satisfaction. Study designs included randomized controlled trial (n = 1; 2.4%), interrupted time series (n = 1; 2.4%), pretest/posttest (n = 21; 51.2%), posttest only (n = 14; 34.1%), and pretest/posttest and posttest only for different dependent variables (n = 4; 9.8%). Data collection occurred through observations (n = 19, 46.3%), surveys (n = 17, 41.5%), patient safety event reports (n = 9, 22.0%), surveillance (n = 6, 14.6%), and audits (n = 3, 7.3%). CONCLUSION: Of the 100 measures across the 41 articles, implementing BCMA and/or eMAR broadly resulted in an increase in measures of effectiveness (n = 23, 52.3%) and satisfaction (n = 28, 62.2%) compared to measures of efficiency (n = 3, 27.3%). Future research should focus on eMAR efficiency measures, utilize rigorous study designs, and generate specific design requirements.
