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A Logistic Regression Analysis of Multiple Independent Variables Impacting Psychiatric Readmissions.

机译：影响精神科再入院的多个独立变量的Logistic回归分析。

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摘要

This dissertation explored several internal and external factors in relation to psychiatric readmissions. Internal factors are directly related to the individual i.e., demographic information, diagnosis, admission history and status. External factors are factors outside of the individuals control i.e., length of hospital stay and reimbursement processes. The goal of the study was to explore the impact of multiple factors in relation to the phenomenon of psychiatric readmissions. Dynamic Systems Theory (1994) was used as a theoretical foundation to understand the complexities associated with psychiatric readmissions. The study utilized state archival data provided by the Maryland Health Services Cost Review Commission; an agency charged with collecting statewide hospital data on hospital admissions.;A quasi experimental study was conducted using a logistic regression design to answer the research question: When taken together do age, sex, ethnicity, diagnosis, insurance type, admission status and length of stay predict psychiatric readmission? This researcher predicted that the null hypothesis will be rejected. The sample included a large state-wide data set of over 130,000 individuals who fell under the criteria of being over the age of 18 when readmitted for psychiatric care in Maryland in 2015. The research methodology includes a logistic regression research design, exploring multiple factors, simultaneously, that impact psychiatric readmissions.;The results of the study indicate that length of stay is the most important factor impacting psychiatric readmissions. The second most important factor associated with psychiatric readmission, is a psychiatric readmission within 30 days. Medicare and Medicaid were also found to be significant factors associated with psychiatric readmission. Additionally, affective disorders were found to be the primary diagnosis associated with psychiatric readmissions. Lastly, individuals at greatest risk for psychiatric readmissions are between the age of 18-39, are non-Hispanic, are enrolled in Medicare, most likely to be disabled, are diagnosed with an affective disorder and have had a previous psychiatric readmission.
机译：本文探讨了与精神科再入院相关的一些内在和外在因素。内部因素与个人直接相关，即人口统计信息，诊断，入院历史和状态。外部因素是个人无法控制的因素，即住院时间和报销过程。该研究的目的是探讨与精神科再入院现象相关的多种因素的影响。动态系统理论（1994年）被用作了解与精神科再入院有关的复杂性的理论基础。该研究利用了马里兰州卫生服务成本审查委员会提供的州档案数据；负责收集全州医院入院数据的机构。使用逻辑回归设计进行了一项准实验研究，回答了以下研究问题：将年龄，性别，种族，诊断，保险类型，入院状态和时长综合在一起保持预测的精神病再入院率？该研究人员预测，原假设将被拒绝。该样本包括2015年在马里兰州重新接受精神病治疗时不满18岁的标准的超过13万个人的全州范围的大型数据集。研究方法包括逻辑回归研究设计，探索多种因素，研究结果表明，住院时间是影响精神科再入院的最重要因素。与精神科再入院有关的第二个最重要因素是30天内的精神科再入院。还发现Medicare和Medicaid是与精神科再入院相关的重要因素。另外，发现情感障碍是与精神科再入院有关的主要诊断。最后，精神病患者再次入院的风险最高，年龄在18-39岁之间，非西班牙裔，参加了Medicare，最有可能是残疾人，被诊断患有情感障碍，并且曾接受过精神病患者入院。

著录项

  • 作者

    Simmons, Carol Ivy.;

  • 作者单位

    Capella University.;

  • 授予单位 Capella University.;
  • 学科 Mental health.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 135 p.
  • 总页数 135
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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