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Data mining to identify quality of care factors associated with liability claims and risk management strategies in Florida nursing homes.

机译：数据挖掘可确定佛罗里达州养老院中与责任索赔和风险管理策略相关的护理因素的质量。

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摘要

The challenges facing the nursing home industry are increasingly important to the population of the United States. As the population grows older, the number of people requiring services from a nursing home will increase. In today's environment the nursing home business face many challenges that will define the future of the industry. Among them is the plaintiff attorney lawsuit against nursing homes, rising liability costs and vulnerability to lawsuits.;The purpose of this study was to examine the influence that quality of care factors and risk management strategies have on liability claims in nursing homes, and to create a risk management model. Four research questions and a hypothesis were tested. The research design was an exploratory and predictive quantitative design using data mining of secondary data. The study analyzed the quality of care factors associated with liability claims and model risk management in order to predict and generate strategies that can decrease claims in Florida nursing homes. The data sets used in the study consisted of data from 106 nursing homes from 67 counties in Florida. The study used data mining software application to conduct data mining analysis and create risk management models. The data models developed were used to identify quality of care factors associated with liability claims in Florida nursing homes.;Findings indicated (a) there was a strong correlation between quality of care indicators and the incidents that led to liability claims; (b) various risk management strategies have been used in Florida, of which the most common seem to be methods for training staff; (c) while various risk management strategies such as training and educating staff do have an effect on the number and severity of lawsuits, they are not necessarily sufficient to decrease nursing homes' exposure to risk substantially; and, (d) the success of the measurements indicated that there are indeed diagnostic tools that can identify areas of risk, but the external factors noted in the answer to the previous question still apply. The implications and recommendations were that the nursing home industry requires a holistic focus on the legal and financial context of that industry.
机译：疗养院行业面临的挑战对美国人口越来越重要。随着人口的老龄化，需要养老院服务的人数将会增加。在当今环境下，养老院业务面临许多挑战，这些挑战将定义该行业的未来。其中包括针对疗养院的原告律师诉讼，责任成本上升和诉讼脆弱性。本研究的目的是研究护理因素的质量和风险管理策略对疗养院责任索赔的影响，并创建风险管理模型。测试了四个研究问题和一个假设。该研究设计是使用辅助数据的数据挖掘进行的探索性和预测性定量设计。这项研究分析了与责任索赔相关的护理因素的质量，并建立了风险管理模型，以预测和生成可以减少佛罗里达养老院索赔的策略。研究中使用的数据集包括来自佛罗里达州67个县的106个疗养院的数据。该研究使用数据挖掘软件应用程序进行数据挖掘分析并创建风险管理模型。所开发的数据模型用于确定佛罗里达州养老院中与责任索赔相关的护理因素的质量。结果表明（a）护理质量指标与导致责任索赔的事件之间存在很强的相关性； （b）在佛罗里达州已经采用了各种风险管理策略，其中最常见的似乎是培训人员的方法； （c）虽然各种风险管理策略（例如培训和教育人员）确实会对诉讼的数量和严重性产生影响，但它们不一定足以大大减少疗养院的风险； （d）测量的成功表明确实存在可以识别风险区域的诊断工具，但对上一个问题的回答中指出的外部因素仍然适用。其含义和建议是，疗养院行业需要全面关注该行业的法律和财务背景。

著录项

  • 作者

    Fortune, Ernande.;

  • 作者单位

    Lynn University.;

  • 授予单位 Lynn University.;
  • 学科 Health Sciences Nursing.;Health Sciences Health Care Management.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 232 p.
  • 总页数 232
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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