Bmc Med Inform Decis
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Bmc Med Inform Decis · Jan 2014
Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.
The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE) using clinical signs and heart rate variability. ⋯ It is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h. We conclude that more predictors do not necessarily guarantee better prediction results. Furthermore, machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.
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Bmc Med Inform Decis · Jan 2014
ReviewCongruence between patients' preferred and perceived participation in medical decision-making: a review of the literature.
Patients are increasingly expected and asked to be involved in health care decisions. In this decision-making process, preferences for participation are important. In this systematic review we aim to provide an overview the literature related to the congruence between patients' preferences and their perceived participation in medical decision-making. We also explore the direction of mismatched and outline factors associated with congruence. ⋯ This review suggests that a similar approach to all patients is not likely to meet patients' wishes, since preferences for participation vary among patients. Health care professionals should be sensitive to patients individual preferences and communicate about patients' participation wishes on a regular basis during their illness trajectory.
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Bmc Med Inform Decis · Jan 2014
A flexible simulation platform to quantify and manage emergency department crowding.
Hospital-based Emergency Departments are struggling to provide timely care to a steadily increasing number of unscheduled ED visits. Dwindling compensation and rising ED closures dictate that meeting this challenge demands greater operational efficiency. ⋯ In building this robust simulation framework, we have created a novel decision-support tool that ED and hospital managers can use to quantify the impact of proposed changes to patient flow prior to implementation.
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Bmc Med Inform Decis · Jan 2014
Development and pilot testing of an online case-based approach to shared decision making skills training for clinicians.
Although research suggests that patients prefer a shared decision making (SDM) experience when making healthcare decisions, clinicians do not routinely implement SDM into their practice and training programs are needed. Using a novel case-based strategy, we developed and pilot tested an online educational program to promote shared decision making (SDM) by primary care clinicians. ⋯ A comprehensive model of the SDM process was used to design a case-based approach to teaching SDM skills to primary care clinicians. The case was favorably rated in this pilot study. Clinician skills training for helping patients clarify their values and for assessing patients' desire for involvement in decision making remain significant challenges and should be a focus of future comparative studies.
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Bmc Med Inform Decis · Jan 2014
The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study.
Errors in the decision-making process are probably the main threat to patient safety in the prehospital setting. The reason can be the change of focus in prehospital care from the traditional "scoop and run" practice to a more complex assessment and this new focus imposes real demands on clinical judgment. The use of Clinical Guidelines (CG) is a common strategy for cognitively supporting the prehospital providers. However, there are studies that suggest that the compliance with CG in some cases is low in the prehospital setting. One possible way to increase compliance with guidelines could be to introduce guidelines in a Computerized Decision Support System (CDSS). There is limited evidence relating to the effect of CDSS in a prehospital setting. The present study aimed to evaluate the effect of CDSS on compliance with the basic assessment process described in the prehospital CG and the effect of On Scene Time (OST). ⋯ The use of CDSS in prehospital care has the ability to increase compliance with the assessment process of patients with a medical emergency. This study was unable to demonstrate any effects of OST.