title: Modelling strategies for reducing pharmaceutical costs in hospital.
abstract: OBJECTIVE
  To describe drug utilization and cost in a large hospital and to compare the impact of different strategies on cost associated with drug prescribing.
  
  
  METHODS
  Retrospective data on drug utilization and cost, linked to patient clinical data and prescriber data from November 1998 were analyzed and modelled.
  
  
  METHODS
  Impact of different strategies for cost control.
  
  
  METHODS
  A large hospital in Sydney, Australia.
  
  
  RESULTS
  The mean cost of drugs per episode of care was 28 Australian dollars. Of all drug costs, 79% was incurred by medical units and 14% by surgical units. Oncology accounted for 42% and inpatients for 91% of drug costs. Although section-100 (S-100) drugs incurred a high cost (640 dollars) per episode of care, there were only 41 episodes where S-100 drugs (expensive, restricted drugs) were used, and the total cost of S-100 drugs was only 3.7% of the total cost to the hospital. Antibiotics were the most commonly prescribed drug category, prescribed in 14% of all hospital episodes, and accounting for 14% of total drug costs. Anti-ulcer drugs were the next most costly group, accounting for 7% of total drug costs. A 20% reduction in use of antibiotics would save four times that (233,832 dollars pa) of a 20% reduction in use of S-100 drugs (61,392 dollars pa).
  
  
  CONCLUSIONS
  Our study suggests that reducing inappropriate use of high volume drugs such as antibiotics could be more effective in optimising health facility drug budgets than attempts concentrating solely on reducing use of high cost drugs alone. Moreover our study suggests that systematic measurement of drug utilisation patterns is a key element of drug cost control strategies.
authors.affiliation: Department of Public Health & Community Medicine, Westmead Hospital, New South Wales, Australia. RainaM@chw.edu.au
authors.forename: C R
authors.initials: CR
authors.lastname: MacIntyre
authors.forename: D
authors.initials: D
authors.lastname: Sindhusake
authors.forename: G
authors.initials: G
authors.lastname: Rubin
mesh_terms: D003361:Cost Allocation / Q000379:methods; D003363:Cost Control / Q000379:methods; D003430:Cross-Sectional Studies; D020000:Decision Support Systems, Clinical; D003953:Diagnosis-Related Groups; D016527:Drug Costs / Q000145:classification / Q000706:statistics & numerical data*; D017723:Drug Utilization Review / Q000191:economics*; D017050:Episode of Care; D006746:Hospital Bed Capacity, 500 and over; D017721:Hospital Costs / Q000145:classification / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D017059:Models, Econometric; D009517:New South Wales; D004364:Pharmaceutical Preparations / Q000145:classification*; D010607:Pharmacy Service, Hospital / Q000191:economics*; D010818:Practice Patterns, Physicians' / Q000145:classification* / Q000191:economics* / Q000706:statistics & numerical data; D012189:Retrospective Studies
chemical_list: D004364:Pharmaceutical Preparations