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

机译：非紧急医疗用途对美国医疗系统的影响：一项回顾性研究。

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摘要

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.;Keywords: emergency department, emergency department waiting time, emergency visits, inpatient mortality, low-severity, non-emergent, non-emergency conditions, non-emergency medical use, non-emergency visits, patient outcomes, routine, total emergency department charges.
机译：在过去的三十年中，非紧急医疗用途（被视为在非紧急情况下使用紧急医疗服务的方式）迅速发展，并继续成为卫生当局，私人和公立医院以及许多其他机构的令人担忧的问题该领域的研究人员和专家对这一主题进行了辩论和研究。相应地，该回顾性研究通过调查和区分非紧急访问与紧急访问的特征来分析2010 NEDS数据集。此外，这项回顾性研究确定了针对非紧急情况进行紧急就诊的百分比，确定了非紧急医疗使用对患者死亡率，住院急诊时间和急诊总费用的影响，并提出了可行的建议非紧急医疗用途的持续性问题。在整个研究中，使用了五种主要的数据分析方法：描述性统计分析，ED CPT严重程度分析，NYU ED分类算法分析，方差分析和逻辑回归分析。首先，进行描述性统计分析以检测具有统计学意义的数字观察值，这些数字观察值足以指示非紧急医疗利用。其次，将ED CPT严重程度分析和NYU ED分类算法分析应用于2010 NEDS数据集，以探讨诊断和程序方法是否在统计学上有效，以帮助区分非紧急就诊与紧急就诊。第三，使用统计模型ANOVA进行方差分析，以揭示和发现非紧急访问和紧急访问之间在统计上显着的差异。第四，采用概率统计分析方法（逻辑回归）来确定患者的人口统计学特征是否具有统计学意义，以预测急诊就诊。因此，描述性统计结果表明，在所有急诊科就诊中，有54.02％到82.7％的情况是常规，低严重性或非紧急情况，并且有统计学上方便的方法将非紧急就诊与紧急访问。另外，方差分析的其他结果显示，非紧急访问和紧急访问的方式之间存在显着的统计差异。最后，逻辑回归的结果表明，在所有病例中，有76.5％的患者人口统计学特征与急诊就诊结果之间存在统计上显着的预测关系。因此，这项研究的结果得出这样的结论，即非紧急情况下需要进行大量急诊就诊，这可以描述为非紧急医疗用途的主要基础，因为它会对患者的住院死亡率产生负面影响，急诊科等待时间和急诊科总费用。关键字：急诊科，急诊科等待时间，急诊就诊，住院死亡率，低严重度，非紧急情况，非紧急情况，非紧急医疗用途，非紧急情况急诊，病人预后，常规，急诊总费用。

著录项

  • 作者

    Casimir, Patrick.;

  • 作者单位

    Rutgers The State University of New Jersey, School of Health Related Professions.;

  • 授予单位 Rutgers The State University of New Jersey, School of Health Related Professions.;
  • 学科 Health care management.;Public health.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 190 p.
  • 总页数 190
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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