Measuring Healthcare Quality: A Robust Healthcare Quality Index (HQI) Based on the Generalized Maximum Entropy Formulation

Add to your list(s) Download to your calendar using vCal

• Alexander Komashie (University of Cambridge, UK)
• Wednesday 26 January 2011, 16:00-17:00
• Arthur Marshall Meeting Room (next to EDC loft), Inglis Building, Engineering Department.

If you have a question about this talk, please contact Saba Hinrichs.

This talk will discuss the development of a robust index for the measurement, monitoring and improvement of healthcare quality. The Generalized Maximum Entropy (GME) methodology was employed for the formulation and estimation of the linear system of equations used to develop the index. 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 England. 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 popular Least Square Regression (LSR) method and also that service quality values predicted by the HQI , correspond significantly to patients’ perception of the quality of the care they had received as indicated by survey responses.

This talk is part of the Engineering Design Centre series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Arthur Marshall Meeting Room (next to EDC loft), Inglis Building, Engineering Department
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Civil Engineering Talks
• Engineering Design Centre
• Featured lists
• Interested Talks
• School of Technology
• Trust & Technology Initiative - interesting events
• bld31

Note that ex-directory lists are not shown.