Bmc Med Inform Decis
-
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.
-
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.
-
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.
-
Bmc Med Inform Decis · Jan 2014
An innovative approach to near-infrared spectroscopy using a standard mobile device and its clinical application in the real-time visualization of peripheral veins.
Excessive venipunctures are a significant problem both in emergency rooms and during hospital stays. Near-infrared (NIR) illumination devices improve venipuncture success rate but their usage is limited by their availability and economic cost. The objectives of this study were to develop a low-cost NIR spectroscopy prototype from a standard mobile device, to evaluate its efficacy and acceptance as an educational tool, and in a clinical setting. ⋯ To the best of our knowledge this is the first study that describes the design, feasibility and application of an NIR spectroscopy prototype developed on a standard mobile device.
-
Bmc Med Inform Decis · Jan 2014
Predicting length of stay from an electronic patient record system: a primary total knee replacement example.
To investigate whether factors can be identified that significantly affect hospital length of stay from those available in an electronic patient record system, using primary total knee replacements as an example. To investigate whether a model can be produced to predict the length of stay based on these factors to help resource planning and patient expectations on their length of stay. ⋯ Valuable information can be found about length of stay from the analysis of variables easily extracted from an electronic patient record system. Models can be successfully created to help improve resource planning and from which a simple decision support system can be produced to help patient expectation on their length of stay.