Applied clinical informatics
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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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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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Stage 2 Meaningful Use criteria require the use of clinical decision support systems (CDSS) on high priority health conditions to improve clinical quality measures. Although CDSS hold great promise, implementation has been fraught with challenges, evidence of their impact is mixed, and the optimal method of content delivery is unknown. ⋯ A simple CDS tool may be associated with improved adherence to guidelines. Efforts are needed to confirm findings and improve the timeliness of monitoring; investigations to optimize alerts should be ongoing.
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Observational Study
A pilot trial of a computerized renal template note to improve resident knowledge and documentation of kidney disease.
Kidney disease is under-documented in physician notes. The use of template-guided notes may improve physician recognition of kidney disease early in training. ⋯ The renal template note significantly improved staging of earlier stage CKD (CKD3) with a modest but non-significant improvement in resident knowledge. Given the importance of early recognition and treatment of CKD, future studies should focus on teaching early recognition using template notes with supplemental educational interventions.
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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.