title: Predicting the cost of hospital stay for stroke patients: the use of diagnosis related groups.
abstract: In order to provide tailor-made care, governments are considering the implementation of output-pricing based on hospital case-mix measures, such as diagnosis related groups (DRG). The question is whether the current DRG classification system can provide a satisfactory prediction of the variance of costs in stroke patients and if not, in what way other variables may enhance this prediction. In this study, data from 731 stroke patients hospitalized at University Hospital Maastricht during 1996-1998 are used in the cost analysis. The DRG classification for this group uses information--in addition to the DRG classification operation or no operation--on the patient's age combined with discharge status. The results of regression analysis show that using DRGs, the variance explained in the costs amounts to 34%. Adding other variables to the DRGs, the variance explained increases to about 61%. Additional factors highly correlating with inpatient costs are the level of functioning after stroke, comorbidity, complications, and 'days of stay for non-medical reasons'. Costs decreased for stroke patients discharged during the latter part of the years studied, and if stroke patients happened to die during their hospital stay. The results do suggest that future implementation of output-pricing based on the DRG case-mix measures is feasible for stroke patients only if it is enhanced with information on complications and the level of functioning.
authors.affiliation: Department of Health Organization Policy and Economics, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands. s.evers@beoz.unimaas.nl
authors.forename: Silvia
authors.initials: S
authors.lastname: Evers
authors.forename: Gemma
authors.initials: G
authors.lastname: Voss
authors.forename: Fred
authors.initials: F
authors.lastname: Nieman
authors.forename: André
authors.initials: A
authors.lastname: Ament
authors.forename: Tom
authors.initials: T
authors.lastname: Groot
authors.forename: Jan
authors.initials: J
authors.lastname: Lodder
authors.forename: Anita
authors.initials: A
authors.lastname: Boreas
authors.forename: Gerhard
authors.initials: G
authors.lastname: Blaauw
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003953:Diagnosis-Related Groups / Q000145:classification / Q000191:economics*; D005260:Female; D005544:Forecasting; D006302:Health Services Research; D017721:Hospital Costs; D006785:Hospitals, University / Q000191:economics* / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics*; D008297:Male; D008875:Middle Aged; D009426:Netherlands; D012044:Regression Analysis; D020521:Stroke / Q000145:classification / Q000191:economics*