An Alternative Approach to Estimating Medical Costs: The Case of Bariatric Surgery
- Presenter:
Chair: F. Reed Johnson; Discussant: TBA Mon June 5, 2006 17:15-18:45 Room 225
Rationale: Traditional cost accounting data are not always a good measure of resource costs for economic evaluations in health care because the fixed component of total costs is large.
Background: Price is likely to be a major factor determining the demand for discretionary medical procedures that require high out-of-pocket payments. This context allows us to evaluate firm behavior using standard economic theory.
Objectives: We estimate a cost function for Bariatric surgery without using traditional cost data.
Methodology: Our approach provides an alternative method for deriving costs when accounting data may be an unreliable estimate of true opportunity costs. We assume the market for Bariatric surgery is imperfectly competitive and that medical institutions are profit maximizers. Rosse (1970) shows how to empirically fit a cost function under these assumptions using data on price, quantity and institutional features. We estimate the cost function for Bariatric surgery using data from the National Inpatient Sample for 2003. We derive our measure of price from the reported expected payer source.
Results: Preliminary analysis reveals a mildly positively sloped marginal cost curve. This is robust to a variety of linear specifications. We find an inverse marginal cost elasticity of 0.14.
Conclusions: Rising marginal costs may be evidence of capacity constraints. However, a lack of data precludes us from controlling for other potentially important determinants of demand such as advertising, reputation effects and principal-agent issues. These may modify the estimated relationship. Typically, U-shaped marginal costs are considered evidence of large fixed costs. These are likely to be observed in time-series data for an individual firm or in a panel of firms. They may also be observed in a context where firms have different levels of “experience” in production. Our on-going analysis will use panel data from 1997-2003 to further study these factors. We believe the approach we take in this study provides a useful alternative to more commonly used techniques that may not be as appropriate in the health care industry.
