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

Owning Attention: Applying Human Factors Principles to Support Clinical Decision Support

In the best examples, clinical decision support (CDS) systems guide clinician decision-making and actions, prevent errors, improve quality, reduce costs, save time, and promote the use of evidence-based recommendations. However, the potential solution that CDS represents are limited by problems associated with improper design, implementation, and local customization. Despite an emphasis on electronic health record usability, little progress has been made to protect end-users from inadequately designed workflows and unnecessary interruptions. Intelligent and personalized design creates an opportunity to tailor CDS not just at the patient level but specific to the disease condition, provider experience, and available resources at the healthcare system level. This chapter leverages the Five Rights of CDS framework to demonstrate the application of human factors engineering principles and emerging trends to optimize data analytics, usability, workflow, and design

Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems—I-MeDeSA

Background Medication-related decision support can reduce the frequency of preventable adverse drug events. However, the design of current medication alerts often results in alert fatigue and high over-ride rates, thus reducing any potential benefits. Methods The authors previously reviewed human-factors principles for relevance to medication-related decision support alerts. In this study, instrument items were developed for assessing the appropriate implementation of these human-factors principles in drug-drug interaction (DDI) alerts. User feedback regarding nine electronic medical records was considered during the development process. Content validity, construct validity through correlation analysis, and inter-rater reliability were assessed. Results The final version of the instrument included 26 items associated with nine human-factors principles. Content validation on three systems resulted in the addition of one principle (Corrective Actions) to the instrument and the elimination of eight items. Additionally, the wording of eight items was altered. Correlation analysis suggests a direct relationship between system age and performance of DDI alerts (p=0.0016). Inter-rater reliability indicated substantial agreement between raters (κ=0.764). Conclusion The authors developed and gathered preliminary evidence for the validity of an instrument that measures the appropriate use of human-factors principles in the design and display of DDI alerts. Designers of DDI alerts may use the instrument to improve usability and increase user acceptance of medication alerts, and organizations selecting an electronic medical record may find the instrument helpful in meeting their clinicians' usability need

A Systematic Review Of The Types And Causes Of Prescribing Errors Generated From Using Computerized Provider Order Entry Systems in Primary and Secondary Care

Objective To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems. Materials and Methods We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken. Results A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users’ work processes, and clinical decision support systems. Displaying an incomplete list of a patient’s medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users’ misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors. Discussion and Conclusions Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users’ workflow expectations

Are We There Yet? Human Factors Knowledge and Health Information Technology – the Challenges of Implementation and Impact

Objective: To review the developments in human factors (HF)research on the challenges of health information technology(HIT) implementation and impact given the continuing incidenceof usability problems and unintended consequences from HITdevelopment and use.Methods: A search of PubMed/Medline and Web of Science®identified HF research published in 2015 and 2016. Electronichealth records (EHRs) and patient-centred HIT emerged assignificant foci of recent HF research. The authors selected prominentpapers highlighting ongoing HF and usability challenges inthese areas. This selective rather than systematic review of recentHF research highlights these key challenges and reflects on theirimplications on the future impact of HF research on HIT.Results: Research provides evidence of continued poor design,implementation, and usability of HIT, as well as technologyinducederrors and unintended consequences. The paperhighlights support for: (i) strengthening the evidence base on thebenefits of HF approaches; (ii) improving knowledge translationin the implementation of HF approaches during HIT design,implementation, and evaluation; (iii) increasing transparency,governance, and enforcement of HF best practices at all stages ofthe HIT system development life cycle.Discussion and Conclusion: HF and usability approaches are yetto become embedded as integral components of HIT development,implementation, and impact assessment. As HIT becomesever-more pervasive including with patients as end-users, thereis a need to expand our conceptualisation of the problems to beaddressed and the suite of tactics and strategies to be used tocalibrate our pro-active involvement in its improvement

A protocol study of novice interaction design behaviour in Botswana: solution-driven interaction design

Think aloud studies and protocol analysis are well-known in the field of HCI, but most often these studies focus on usability evaluations, or on the use of technology. Rarely are they used to investigate the behaviour of interaction designers. In this paper, we report on a protocol study with novice interaction designers in Botswana. Participants had just completed the design section of an undergraduate module on Interaction Design that actively promotes a problem-driven approach to the design of interactive products, yet the participants behaved in a way that is closer to a solution-driven approach. The module emphasizes user-centred design, prototyping methods to support design development, and evaluating design detail. Yet participants suggest solutions before exploring the context of use, use prototyping methods to capture, rather than to develop, designs, and do not produce detailed designs. In a problem-solving context, some of these behaviours are typical of novices, but in a design context they are also seen in experienced designers. The results presented here reveal the detail of the approach adopted by these students, and contribute to the wider debate concerning the internationalization of HCI education

Advancing the discussion about Clinical Decision Support Systems to tackle Adverse Drug Events: a ‘problematizing’ approach

Clinical decision support systems (CDSS) can prevent situations in which doctors prescribe a drug to a patient that causes a harmful reaction with another drug that a patient already takes (adverse drug events (ADE)). This can be achieved through generating medication alerts in the moment that a drug is prescribed. Researchers have paid considerable attention to how to design these alerts in the best possible ways, however, largely with inconclusive results. We tackle this body of literature using a ‘problematizing’ approach that enables to understand why research results are inconclusive by disclosing underlying assumptions in a body of literature that have over time shaped a scholarly debate into a particular direction. We uncover four problematic assumptions, offer alternatives to these assumptions and outline potentials to implement our ideas in future research projects