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SUMMARY:Bayesian variable selection in generalized linear models under cos
 t constraints - David Draper\, University of California\, Santa Cruz\, USA
DTSTART:20080208T141500Z
DTEND:20080208T150000Z
UID:TALK10683@talks.cam.ac.uk
CONTACT:Nikolaos Demiris
DESCRIPTION:In the field of quality of health care measurement\, patient s
 ickness at admission is traditionally assessed by using logistic regressio
 n of mortality within (say) 30 days of admission on a fairly large number 
 of sickness indicators (on the order of 100) to construct a sickness scale
 \, employing classical variable selection methods to find an "optimal" sub
 set of 10-20 indicators. In a world where electronic medical records are o
 nly now being slowly phased in and manual data abstraction from patient ch
 arts will still be used for some time (particularly in countries that are 
 not on the cutting edge in medical informatics)\, such "benefit-only" meth
 ods ignore the\nconsiderable differences among the sickness indicators in 
 cost of data collection. This issue is crucial when admission sickness is 
 used to drive programs (now implemented or under consideration in several 
 countries\, including the US and UK) that attempt to identify substandard 
 hospitals by comparing observed and expected mortality rates (given admiss
 ion sickness).  When both data-collection cost and accuracy of prediction 
 of 30-day mortality are considered\, a large variable-selection problem ar
 ises in which costly variables that do not predict well enough should be o
 mitted from the final scale.\n\nIn this talk I'll argue that there are thr
 ee main ways to solve this problem: (1) a decision-theoretic cost-benefit 
 approach based on maximizing expected\nutility\, (2) an alternative cost-b
 enefit approach based on posterior model odds\, and (3) a cost-restriction
 -benefit analysis that maximizes predictive accuracy subject to a bound on
  cost. I'll present details of as many of these methods as time permits\, 
 in the context of a large quality of care study of American patients hospi
 talized under the Medicare program. This is joint work with Dimitris Fousk
 akis and Ioannis Ntzoufras.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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