Applied clinical informatics
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Poor usability is a threat to patient safety and linked to productivity loss, workflow disruption, user frustration, sub-optimal product use and system de-installations. Although usability is receiving more attention nationally and internationally, myths about usability persist. This editorial debunks five common myths about usability (1) usability only concerns the look and feel of a product and is, therefore, only a minor concern, (2) usability is not measurable, (3) usability stifles innovation, (4) vendors are solely responsible for product usability, and (5) usability methods are not practical for use in healthcare.
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To compare the completeness of Emergency Department (ED) discharge instructions before and after introduction of an electronic discharge instructions module by scoring compliance with the Centers for Medicare and Medicaid Services (CMS) Outpatient Measure 19 (OP-19). ⋯ With careful design, information technology can improve the completeness of ED patient discharge instructions and performance on the OP-19 quality measure.
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Healthcare Electronic Syndromic Surveillance (ESS) is the systematic collection, analysis and interpretation of ongoing clinical data with subsequent dissemination of results, which aid clinical decision-making. ⋯ There is significant heterogeneity in the diagnostic performance of the available ESS implements in acute care, stemming from the wide spectrum of different clinical entities and ESS systems. Based on the results, we introduce a conceptual framework using a likelihood ratio matrix for evaluation and meaningful application of future, frontline clinical decision support systems.
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Comparative Study
Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department.
Asthma exacerbations are one of the most common medical reasons for children to be brought to the hospital emergency department (ED). Various prediction models have been proposed to support diagnosis of exacerbations and evaluation of their severity. ⋯ Both the PRAM score and the NB model were less accurate than physicians. The NB model can handle incomplete patient data and as such may complement the PRAM score. However, it requires further research to improve its accuracy.
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Self-administered computer-assisted interviewing (SACAI) gathers accurate information from patients and could facilitate Emergency Department (ED) diagnosis. As part of an ongoing research effort whose long-range goal is to develop automated medical interviewing for diagnostic decision support, we explored usability attributes of SACAI in the ED. ⋯ Understanding human-computer interactions in real-world clinical settings is essential to implementing automated interviewing as means to a larger long-term goal of enhancing clinical care, diagnostic accuracy, and patient safety.