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

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

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

Revisión sistemática de la literatura sobre evaluación de la e-salud

El propósito del documento es presentar una síntesis de los mecanismos para la medición de la e-Salud (definida como el uso de las TIC en el sector de la salud) publicados en la literatura científica como punto de partida para la elaboración de un modelo evaluativo que sirva como referencia para la medición de la e-Salud. Para lograr este propósito, se desarrolló una revisión sistemática de literatura de los documentos publicados entre los años 2004 y 2014 enfocada en los siguientes cinco objetivos, construir un marco conceptual que permita explicar qué es e-salud y sus características más importantes. planear la revisión sistemática, estableciendo las preguntas de investigación, el alcance de la revisión y los criterios a considerar para la selección y clasificación de los documentos, buscar los documentos en las bases de datos seleccionadas utilizando para ello una ecuación de búsqueda depurada, seleccionar los documentos a ser analizados a través de una evaluación de calidad de los mismos, realizar el análisis de los documentos seleccionados y presentar una síntesis de los resultados obtenidos, el principal resultado de este estudio fue la identificación de 22 procesos o frameworks de evaluación, 16 tipos de factores de evaluación, 11 tipos de variables y 6 tipos de indicadores para la medición de la e-Salud. También se encontraron 8 aspectos sometidos a evaluación, distribuidos en los documentos de la siguiente manera: 7.29% a la implementación, el 11.46% a la adopción, 3.13% a la factibilidad, el 11.46% a la satisfacción, el 9.38% a la calidad, el 26.04% al uso y el 35.42% a otros aspectos generales

Atheoretical Versus Theory-Based Approaches in Promoting Safer ADHD-Medication Prescribing for Adults

Gaps between treatment guidelines and medical decisions persist despite interventions with physicians, which are mostly atheoretical. The purpose of this retrospective cross-sectional study was to compare atheoretical and theory-based logistic regression models of a binary outcome: potentially unsafe prescribing of attention-deficit hyperactivity disorder (ADHD) medications to adults. Social cognitive theory and self-determination theory provided the framework for the study. Predictors were framed as social cognitive theoretical constructs: knowledge (e.g., physician specialty) and environmental influence (e.g., interventions). Atheoretical hypotheses were based on legislation mandating meaningful use of electronic health records and computerized decision support (CDS). Theory-based hypotheses were derived from literature on cognition in medicine and on the controlled motivation construct in self-determination theory. Research questions addressed associations of CDS and meaningful use with the outcome and fit of competing models. The sample included office-based physician visits made by patients aged \u3e 17 years with ADHD (n = 810) or potentially unsafe medical conditions (n = 9,101), recorded in a U.S. database in 2014–2016. Findings for the atheoretical model were reduced odds of the outcome with CDS, and nonsignificant improvement in model fit using theory. Supporting the self-determination theory-based hypothesis, odds were increased with meaningful use. This study adds to research suggesting autonomy as a core issue in medicine. Positive social change may result from psychology-based strategies to empower physicians through participation in developing clinically relevant information systems

An investigation of healthcare professionals’ experiences of training and using electronic prescribing systems: four literature reviews and two qualitative studies undertaken in the UK hospital context

Electronic prescribing (ePrescribing) is the process of ordering medicines electronically for a patient and has been associated with reduced medication errors and improved patient safety. However, these systems have also been associated with unintended adverse consequences. There is a lack of published research about users’ experiences of these systems in UK hospitals. The aim of this research was therefore to firstly describe the literature pertaining to the recent developments and persisting issues with ePrescribing and clinical decision support systems (CDS) (chapter 2). Two further systematic literature reviews (chapters 3 and 4) were then conducted to understand the unintended consequences of ePrescribing and clinical decision support (CDS) systems across both adult and paediatric patients. These revealed a taxonomy of factors, which have contributed to errors during use of these systems e.g., the screen layout, default settings and inappropriate drug-dosage support. The researcher then conducted a qualitative study (chapters 7-10) to explore users’ experiences of using and being trained to use ePrescribing systems. This study involved conducting semi-structured interviews and observations, which revealed key challenges facing users, including issues with using the ‘Medication List’ and how information was presented. Users experienced benefits and challenges when customising the system, including the screen display; however, the process was sometimes overly complex. Users also described the benefits and challenges associated with different forms of interruptive and passive CDS. Order sets, for instance, encouraged more efficient prescribing, yet users often found them difficult to find within the system. A lack of training resulted in users failing to use all features of the ePrescribing system and left some healthcare staff feeling underprepared for using the system in their role. A further literature review (chapter 5) was then performed to complement emerging themes relating to how users were trained to use ePrescribing systems, which were generated as part of a qualitative study. This review revealed the range of approaches used to train users and the need for further research in this area. The literature review and qualitative study-based findings led to a follow-on study (chapter 10), whereby the researcher conducted semi-structured interviews to examine how users were trained to use ePrescribing systems across four NHS Hospital Trusts. A range of approaches were used to train users; tailored training, using clinically specific scenarios or matching the user’s profession to that of the trainer were preferred over lectures and e-learning may offer an efficient way of training large numbers of staff. However, further research is needed to investigate this and whether alternative approaches such as the use of students as trainers could be useful. This programme of work revealed the importance of human factors and user involvement in the design and ongoing development of ePrescribing systems. Training also played a role in users’ experiences of using the system and hospitals should carefully consider the training approaches used. This thesis provides recommendations gathered from the literature and primary data collection that can help inform organisations, system developers and further research in this area