Usability flaws of medication-related alerting functions: A systematic qualitative review

AbstractIntroductionMedication-related alerting functions may include usability flaws that limit their optimal use. A first step on the way to preventing usability flaws is to understand the characteristics of these usability flaws. This systematic qualitative review aims to analyze the type of usability flaws found in medication-related alerting functions.MethodPapers were searched via PubMed, Scopus and Ergonomics Abstracts databases, along with references lists. Paper selection, data extraction and data analysis was performed by two to three Human Factors experts. Meaningful semantic units representing instances of usability flaws were the main data extracted. They were analyzed through qualitative methods: categorization following general usability heuristics and through an inductive process for the flaws specific to medication-related alerting functions.Main resultsFrom the 6380 papers initially identified, 26 met all eligibility criteria. The analysis of the papers identified a total of 168 instances of usability flaws that could be classified into 13 categories of usability flaws representing either violations of general usability principles (i.e. they could be found in any system, e.g. guidance and workload issues) or infractions specific to medication-related alerting functions. The latter refer to issues of low signal-to-noise ratio, incomplete content of alerts, transparency, presentation mode and timing, missing alert features, tasks and control distribution.Main conclusionThe list of 168 instances of usability flaws of medication-related alerting functions provides a source of knowledge for checking the usability of medication-related alerting functions during their design and evaluation process and ultimately constructs evidence-based usability design principles for these functions

The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed. Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully. Methods: We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist. Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy. Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed

A Sustainable Future In The Implementation Of Clinical Pharmacogenomics

Purpose: The sustainability of clinical pharmacogenomics requires further study of clinical education on the topic, its effects on clinical workflow, and the responsibilities of different providers for its delivery. Tools from the discipline of implementation science were utilized herein to help achieve the purposes of the three studies. The broad purpose of this dissertation is to advance the work of clinical pharmacogenomic implementation through a more rigorous convergence with implementation science. Methods: Three studies constitute the whole of this dissertation. The first is a scoping review that provides a broad characterization of the methods utilized in available peer-revieliterature focusing on provider use of and experience with using pharmacogenomics in practice or the study setting. The second study used semi-structured in-depth interviews to elicit strategies and perspectives from leadership in current implementation programs using the Consolidated Framework for Implementation Science (CFIR) Process Domain. The third used a cross-sectional quantitative survey with experimental vignettes to explore the potential for pharmacist-physician collaboration using newly developed implementation science outcomes. Results: The scoping review included 25 studies, with many focused on the interactions of providers with clinical decision support systems and adherence to therapeutic recommendations represented. Results from the interviews were extensive but several highlights included a focus on understanding pharmacogenomic use prior to implementation, high-touch informal communication with providers, and the power of the patient case. The survey analysis revealed that the primary care physicians believe that it is more appropriate to deliver clinical pharmacogenomics when a pharmacist is physically located in a clinic and is responsible for managing and modifying a drug therapy based on these results. Conclusion: These three studies further the convergence of implementation science and genomic medicine, with particular focus on pharmacogenomics and the foundational concept of implementation science, sustainability. The scoping review should provide future researchers with a landscape of available and previously used methodologies for interventional pharmacogenomic studies. The interview results will help new implementers of pharmacogenomics steer around avoidable hurdles or make them easier to address. The survey results showcase the potential for pharmacist-physician collaboration in clinical pharmacogenomics

CDSSs for CVD Risk Management: An Integrative Review

Cardiovascular disease (CVD) is a preventable disease affecting almost half of adults in the United States (U.S.) and can have significant negative outcomes such as stroke and myocardial infarction, which can be fatal. Utilizing clinical decision support systems (CDSSs) in the primary care and community health setting can improve primary prevention of CVD by supporting evidence-based decision making at the point of care. This integrative review synthesizes the most up-to-date literature on the use of clinical decision support (CDS) tools to support guideline-based management of CVD risk. Using Whittemore and Knafl’s framework for integrative reviews, a systematic search of CINAHL, Cochrane, and Medline and ancestry search yielded 492 results; 17 articles were included in the final review after applying inclusion and exclusion criteria. Evidence-based CDSSs for CVD prevention improved guideline-based initiation and intensification of pharmacological treatment, increased frequency and accuracy of CVD risk screening, and facilitated shared decision-making discussions with patients about CVD risk; however, they were not effective in promoting smoking cessation and only sometimes effective in improving blood pressure (BP) control. This integrative review supports future evidence-based practice projects implementing CDSSs designed to improve guideline-based primary prevention of CVD as an, albeit partial, solution to improving prevention of CVD in the U.S. and globally

Doctor of Philosophy

dissertationClinical decision support systems (CDSS) and electronic health records (EHR) have been widely adopted but do not support a high level of reasoning for the clinician. As a result, workflow incongruity and provider frustrations lead to more errors in reasoning. Other successful fields such as defense, aviation, and the military have used task complexity as a key factor in decision support system development. Task complexity arises during the interaction of the user and the tasks. Therefore, in this dissertation I have utilized different human factor methods to explore task complexity factors to understand their utility in health information technology system design. The first study addresses the question of generalizing complexity through a clinical complexity model. In this study, we integrated and validated a patient and task complexity model into a clinical complexity model tailored towards healthcare to serve as the initial framework for data analysis in our subsequent studies. The second study addresses the question of the coping strategies of infectious disease (ID) clinicians while dealing with complex decision tasks. The study concluded that clinicians use multiple cognitive strategies that help them to switch between automatic cognitive processes and analytical processes. The third study identified the complexity contributing factors from the transcripts of the observations conducted in the ID domain. The clinical complexity model developed in the first study guided the research for identifying the prominent complexity iv factors to recommend innovative healthcare technology system design. The fourth study, a pilot exploratory study, demonstrated the feasibility of developing a population information display from querying real complex patient information from an actual clinical database as well as identifying the ideal features of population information display. In summary, this dissertation adds to the knowledge about how clinicians adapt their information environment to deal with complexity. First, it contributes by developing a clinical complexity model that integrates both patient and task complexity. Second, it provides specific design recommendations for future innovative health information technology systems. Last, this dissertation also suggests that understanding task complexity in the healthcare team domain may help to better design of interface system