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.
Background: Duplicate medication orders are a prominent type of medication error that in some circumstances has increased after implementation of health information technology. Duplicate medication orders are commonly defined as two or more active orders for the same medication or medications within the same therapeutic class. While there have been several studies that have identified contributing factors and described potential solutions, duplicate medication order errors continue to impact patient safety. Methods: We analyzed 377 reports from 95 healthcare facilities to more granularly define the types of duplicate medication order errors and the context under which these errors occurred, as well as potential contributing factors. Results: Of the 377 reports reviewed, 304 (80.6%) met the criteria to be defined as a duplicate medication order error. The most frequent duplicate medication order error type was same order (n=131, 43.1%), followed by same therapeutic class (n=98, 32.2%) and same medication (n=70, 23.0%). Errors were identified during different medication process tasks and most commonly during medication reconciliation during the patient’s stay in the hospital (n=72, 23.7%) and during pharmacy verification (n=36, 11.8%). Factors contributing to these errors included health information technology issues (n=63, 20.7%), gaps in care coordination (n=44, 14.5%), and a prior dose or medication order not being discontinued (n=52, 17.1%). Conclusion: Our results highlight specific areas for practice improvement, and we make recommendations for how healthcare facilities can better address duplicate medication order errors.
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.
Background: Alarms are signals intended to capture and direct human attention to a potential issue that may require monitoring, assessment, or intervention and play a critical safety role in high-risk industries. Healthcare relies heavily on auditory and visual alarms. While there are some guidelines to inform alarm design and use, alarm fatigue and other alarm issues are challenges in the healthcare setting. Automotive, aviation, and nuclear industries have used the science of human factors to develop alarm design and use guidelines. These guidelines may provide important insights for advancing patient safety in healthcare. Methods: We identified documents containing alarm design and use guidelines from the automotive, aviation, and nuclear industries that have been endorsed by oversight agencies. These guidelines were reviewed by human factors and clinical experts to identify those most relevant to healthcare, qualitatively analyze the relevant guidelines to identify meaningful topics, synthesize the guidelines under each topic to identify key commonalities and differences, and describe how the guidelines might be considered by healthcare stakeholders to improve alarm design and use. Results: A total of 356 guidelines were extracted from industry documents (2012–present) and 327 (91.9%) were deemed relevant to healthcare. A qualitative analysis of relevant guidelines resulted in nine distinct topics: Alarm Reduction, Appropriateness, Context-Dependence, Design Characteristics, Mental Model, Prioritization, Specificity, Urgency, and User Control. There were several commonalities, as well as some differences, across industry guidelines. The guidelines under each topic were found to inform the auditory or visual modality, or both. Certain guidelines have clear considerations for healthcare stakeholders, especially technology developers and healthcare facilities. Conclusion: Numerous guidelines from other high-risk industries can inform alarm design and use in healthcare. Healthcare facilities can use the information presented as a framework for working with their technology developers to appropriately design and modify alarming technologies and can evaluate their clinical environments to see how alarming technologies might be improved.
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