title: Should there be an age split for stroke DRGs? Analysing a large clinical data set of a principal teaching hospital over a five-year period.
abstract: The aim of this study was to analyse the inpatient statistics collection relating to stroke patients admitted to a major teaching hospital, with particular reference to length of stay, and to assess the adequacy of the diagnosis related group (DRG) as a predictor of length of stay. The study subjects were selected by DRG to identify all stroke inpatients admitted and discharged between 1 July 1995 and 30 June 2000. There were 1365 stroke discharges (half of whom were over 75 years of age at discharge) over the period of the study. The median length of stay was 8 days, and 67% of the subjects experienced complications and/or comorbidities. Age was significantly associated with increased length of stay of stroke patients, independent of complications or comorbidities. These findings raise the question of whether casemix-based funding should be based solely on DRGs for complicated conditions such as stroke, or whether additional measures such as age should be used for funding allocation. This study provides a model that health information managers and other researchers could use to analyse inpatient statistics collections at state, territory or national levels.
authors.affiliation: Prince of Wales Hospital, Randwick, NSW. jgmnr@hotmail.com
authors.forename: Monique
authors.initials: M
authors.lastname: Royle
authors.forename: Joanne
authors.initials: J
authors.lastname: Callen
authors.forename: Maria
authors.initials: M
authors.lastname: Craig
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D003361:Cost Allocation; D066264:Datasets as Topic; D003953:Diagnosis-Related Groups / Q000706:statistics & numerical data*; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006784:Hospitals, Teaching; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010351:Patient Discharge / Q000706:statistics & numerical data; D017678:Sex Distribution; D020521:Stroke / Q000145:classification / Q000175:diagnosis*; D055815:Young Adult