PMID- 1518993
OWN - NLM
STAT- MEDLINE
DCOM- 19921008
LR  - 20190827
IS  - 0277-6715 (Print)
IS  - 0277-6715 (Linking)
VI  - 11
IP  - 10
DP  - 1992 Jul
TI  - Comparing in-patient classification systems: a problem of non-nested regression 
      models.
PG  - 1321-31
AB  - Since 1983, hospitals in the United States have been receiving prospective 
      payment for their in-hospital patient admissions covered under Medicare. Under 
      such schemes each patient is placed in a group by a classification system, known 
      as the Diagnosis Related Groups (DRG), and the hospital is reimbursed by the 
      Health Care Financing Administration according to some predetermined group 
      average, adjusted for hospital level characteristics, such as size, location and 
      teaching activity. Recent interest has focused on refining the DRG system or 
      considering totally different systems of classification. Studies designed to 
      compare the ability of different systems to account for between-patient 
      variability in resource consumption in the same dataset lead to the problem of 
      model selection between large non-nested regressions, where resource consumption, 
      measured by length of hospital stay or costs, is regressed on dummy-indicator 
      variables representing different patient groups. We use a simple measure of fit 
      to develop a symmetric test of the null hypothesis that the two systems account 
      equally well for variability in resource consumption. With this method, unlike 
      methods such as Akaike's AIC criterion, we can quantify the probability of a 
      false positive, and thereby limit the probability of choosing one system over 
      another when it is no better at accounting for variability in resource 
      consumption.
FAU - Willan, A R
AU  - Willan AR
AD  - Department of Clinical Epidemiology and Biostatistics, McMaster University, 
      Hamilton, Ontario, Canada.
FAU - Ross, W
AU  - Ross W
FAU - Mackenzie, T A
AU  - Mackenzie TA
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PL  - England
TA  - Stat Med
JT  - Statistics in medicine
JID - 8215016
SB  - IM
MH  - Diagnosis-Related Groups
MH  - Humans
MH  - Inpatients/*classification
MH  - *Linear Models
MH  - United States
EDAT- 1992/07/01 00:00
MHDA- 1992/07/01 00:01
CRDT- 1992/07/01 00:00
PHST- 1992/07/01 00:00 [pubmed]
PHST- 1992/07/01 00:01 [medline]
PHST- 1992/07/01 00:00 [entrez]
AID - 10.1002/sim.4780111006 [doi]
PST - ppublish
SO  - Stat Med. 1992 Jul;11(10):1321-31. doi: 10.1002/sim.4780111006.