Cost estimates for hospital inpatient care in Australia: evaluation of alternative sources.
OBJECTIVE
This paper presents a framework for evaluation of alternative sources of estimates of the costs of hospital inpatient care in Australia. It argues that the choice of costing methods depends on the decision-context and the sensitivity of the decision to estimation errors.


METHODS
Five criteria are proposed for evaluation of sources of hospital cost data, with detailed consideration of the way estimates are derived in two computerised approaches which use accounting data. Three broad approaches to cost estimation are evaluated against these criteria.


RESULTS
Choosing an estimation method entails an optimisation analysis for each decision context. 'Microcosting' techniques remains the most valid approach to cost estimation, but are costly and this may, in turn, limit the sample of patients or institutions. Protocol-based cost estimates vary widely in their validity, depending on source data, but there is little justification for continued use of crude per diem cost estimates in such protocols. When precision and resolution are important objectives, clinical costing approaches provide the most valid inpatient cost estimates at a reasonable data cost. When external validity is important, or where standardisation of hospital costs is desired, use of published national cost weights may be preferred.


CONCLUSIONS
Both primary and secondary sources of cost data must withstand challenges to internal and external validity. The 'resolution' (or precision) of cost estimates and the relative costs of collection must also be considered.


CONCLUSIONS
Studies using estimates of the costs of hospital care should defend the appropriateness of the costing approach and data source for the decision context.
Jackson
T
T
Monash University Health, Economics Unit, Heidelberg, VIC. Terri.Jackson@buseco.monash.edu.au
D000066:Accounting / Q000379:methods; D001315:Australia; D003361:Cost Allocation / Q000379:methods*; D005069:Evaluation Studies as Topic; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000191:economics*; D017059:Models, Econometric