The impact of non-emergency medical use on the United States healthcare system: a retrospective study

For the last three decades, non-emergency medical use, regarded as the utilization of emergency medical services for conditions that are considered non-emergent, has grown rapidly and continues to be an alarming issue for health authorities, private and public hospitals and a much debated and studied subject by researchers and experts in the field. Correspondingly, this retrospective study was used to analyze the 2010 NEDS data set by investigating and distinguishing the characteristics of non-emergency visits compared to emergency visits. Additionally, this retrospective study identified the percentage of emergency visits made for non-emergency conditions, determined the impact of non-emergency medical use on patient outcomes of inpatient mortality, emergency department waiting time, and total emergency department charges, and made viable recommendations to the ongoing problem of non-emergency medical use. Throughout this study, five main methods of data analysis are used: descriptive statistical analysis, ED CPT severity level analysis, NYU ED classification algorithm analysis, analysis of variance, and logistic regression analysis. First, descriptive statistical analysis is conducted to detect numerical observations that are statistically significant enough to indicate non-emergency medical utilization. Second, ED CPT severity level analysis and NYU ED classification algorithm analysis are applied to the 2010 NEDS data set to probe whether diagnostic and procedural methods are statistically effective to help differentiate non-emergency visits from emergency visits. Third, analysis of variance is performed using the statistical model ANOVA in an effort to expose and uncover differences that are statistically significant between non-emergency visits and emergency visits. Fourth, the probabilistic statistical method of analysis, logistic regression, is employed to determine if patient’s demographic characteristics are statistically significant to predict emergency visits. Consequently, 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 either routine, low-severity, or non-emergent and that there are statistically convenient methods to distinguish non-emergency visits from emergency visits. Also, other 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. Hence, 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.Ph.D.Includes bibliographical referencesby Patrick Casimi