Forecasting the Potential for Emergency Department Overcrowding

This research study used the Dixon Forecasting Model (DFM), a Bed Ratio (BR), and the National Emergency Department Overcrowding Scale (NEDOCS) to establish a reliable two-hour overcrowding forecasting tool within the Emergency Department. The DFM and BR were used together to predict severe overcrowding based on current census data. This two hour prediction was then be validated by the real-time NEDOCS and real-time Bed Ratio scores. Data analysis indicates that the two-hour predicted BR is moderately correlated with a real-time NEDOCS (correlation coefficient 0.508) and real-time BR (correlation coefficient 0.492) at the forecasted time. Further data analysis revealed a strong correlation between the real-time NEDOCS and the real-time BR, as evidenced by a correlation coefficient of 0.949. The results of this study suggest that the DFM can be used with additional data to calculate a two hour forecasted BR and that using either BR or NEDOCS in real-time to determine overcrowding is effective

Impact of EHR Usability on Provider Efficiency and Patient Safety in Non-Hospital Settings

Healthcare organizations may reap benefits transitioning to electronic health records (EHRs), such as decreased healthcare costs and better care. However, severe unintended consequences from implementation and design of these systems have emerged. Poorly implemented EHR systems may endanger the integrity of clinical or administrative data. That, in turn, can lead to errors jeopardizing patient safety or quality of care. A literature review of 40 sources identified how EHR implementation and design can impact provider centric, patient centric, and outcomes. These categories provided the basis for a comprehensive EHR impact model that was evaluated in non-hospital settings through focus groups interviews