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SUMMARY:Measuring Healthcare Quality: A Robust Healthcare Quality Index (H
 QI) Based on the Generalized Maximum Entropy Formulation - Alexander Komas
 hie (University of Cambridge\, UK)
DTSTART:20110126T160000Z
DTEND:20110126T170000Z
UID:TALK28721@talks.cam.ac.uk
CONTACT:Saba Hinrichs
DESCRIPTION:This talk will discuss the development of a robust index for t
 he measurement\, monitoring and improvement of healthcare quality. The Gen
 eralized Maximum Entropy (GME) methodology was employed for the formulatio
 n and estimation of the linear system of equations used to develop the ind
 ex. The index was formulated based on n Key Quality Indicators (KQIs) and 
 m quality factors under each indicator. The Healthcare Quality Index (HQI)
  was tested with Monte Carlo experiments and empirical data obtained from 
 the 2006 survey of adult in-patients by the Healthcare Commission in Engla
 nd.  The empirical study was performed with n=3 and m=5. The results show 
 that GME methodology is a more robust estimator of the index than the popu
 lar Least Square Regression (LSR) method and also that service quality val
 ues predicted by the HQI\, correspond significantly to patients’ percept
 ion of the quality of the care they had received as indicated by survey re
 sponses. 
LOCATION:Arthur Marshall Meeting Room (next to EDC loft)\, Inglis Building
 \, Engineering Department
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