This paper examines the role of clinical decision support systems (CDSS) as a critical and increasingly prevalent tool in improving clinical practice. Using findings from previously published reference papers, books and other related studies, the paper demonstrates how clinical decision support systems are repeatedly being used in clinical practice to enhance quality of care, improve safety, reduce healthcare costs and heighten efficiency. Although findings from the reference papers, books and studies vary in how clinical decision support systems can advance clinical practice, they strongly identify improvements made in clinical practice as they relate to patient safety, medication errors, clinical workflows and processes, diagnostic processes, compliance with regulatory guidelines, disease management, patient outcomes, genomic and personalized medicine and cost of care.
The use of mammography imaging within healthcare practice is universally accepted as a critical tool to help improve the detection and screening of breast cancer with the emphasis for better diagnosis, treatment, management, and reduction in breast cancer mortality in general. Notably, this pressing need has led to numerous studies on the impact of mammography as
Study Objective: This study analyzes the 2010 NEDS data set to investigate and distinguish the characteristics of non-emergency visits compared to emergency visits. Additionally, this study uses five different statistical methods of analysis to identify the percentage of emergency visits made for non-emergency conditions, determine the impact of non-emergency medical use on patient outcomes of inpatient mortality, emergency department waiting time and total emergency department charges. Methods: In this study various methods of data analysis of the 2010 NEDS data set were used such as: descriptive statistics, EDCPT severity level, NYUED classification algorithm, variance and logistic regression. Results: Results of descriptive statistics show that between 54.02 to 82.7 percent of all emergency department visits were made for conditions found to be routine, lowseverity, or non-emergent. Results of analysis of variance show significant statistical differences between the means of non-emergency visits and emergency visits. Finally, results of logistic regression suggest that there are statistically significant predictive relations between patients' demographic characteristics and outcomes of emergency visits in 76.5% of all cases. Conclusion: The results of this study lead to the conclusions that a significant number of emergency department visits are made for non-emergency conditions, which can be depicted as the main basis for non-emergency medical use as to negatively impact patient outcomes of inpatient mortality, emergency department waiting time and total emergency department charges.
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