Design of an information volatility measure for health care decision making

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Design of an information volatility measure for health care decision making
Abstract: Health care decision makers and researchers often use reporting tools (e.g. Online Analytical Processing OLAP)) that present data aggregated from multiple medical registries and electronic medical records to gain insights into health care practices and to understand and improve patient outcomes and quality ofcare. An important limitation is that the data are usually displayed as point estimates without full description of the instability of the underlying data, thus decision makers are often unaware of the presence of outliers or data errors. To manage this problem, we propose an Information Volatility Measure (IVM) to complement business intelligence (BI) tools when considering aggregated data (intra-cell) or when observing trends in data (inter-cell). The IVM definitions and calculations are drawn from volatility measures found in the field of finance, since the underlying data in both arenas display similar behaviors. The presentation of the IVM is supplemented with three types of benchmarking to support improved user understanding of the measure: numerical benchmarking, graphical benchmarking, and categorical benchmarking. The IVM is designed and evaluated using exploratory and confirmatory focus groups.
Keywords:	OLAP Health care informatics Data quality Decision support systems Data instability Information volatility
Author(s):	Monica Chiarini Tremblay , Alan R. Hevner, Donald J. Berndt
Source:	2012
Subject:	تصمیم گیری
Category:	مقاله مجله
Release Date:	2012
No of Pages:	11
Price(Tomans):	0
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