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Analytical Methods to Support Risk Identification and Analysis in Healthcare Systems

Healthcare systems require continuous monitoring of risk to prevent adverse events. Risk analysis is a time consuming activity that depends on the background of analysts and available data. Patient safety data is often incomplete and biased. This research proposes systematic approaches to monitor risk in healthcare using available patient safety data. The methodologies combine traditional healthcare risk analysis methods with safety theory concepts, in an innovative manner, to allocate available evidence to potential risk sources throughout the system. We propose the use of data mining to analyze near-miss reports and guide the identification of risk sources. In addition, we propose a Maximum-Entropy based approach to monitor risk sources and prioritize investigation efforts accordingly.
The products of this research are intended to facilitate risk analysis and allow
for timely identification of risks to prevent harm to patients.

Identiferoai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-4249
Date01 January 2011
CreatorsCure Vellojin, Laila Nadime
PublisherScholar Commons
Source SetsUniversity of South Flordia
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceGraduate Theses and Dissertations
Rightsdefault

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