Estimating the quality of care in hospitals using instrumental variables.


Mortality rates are a widely used measure of hospital quality. A central problem with this measure is selection bias: simply put, severely ill patients may choose high quality hospitals. We control for severity of illness with an instrumental variables (IV) framework using geographic location data. We use IV to examine the quality of pneumonia care in Southern California from 1989 to 1994. We find that the IV quality estimates are markedly different from traditional GLS estimates, and that IV reveals different determinants of quality. Econometric tests suggest that the IV model is appropriately specified, that the GLS model is inconsistent.

Extracted Key Phrases

5 Figures and Tables

Showing 1-10 of 27 references

Instrumental variables regression

  • D Staiger, J H Stock
  • 1997
Highly Influential
3 Excerpts

The marginal cost-effectiveness of medical technology: A panel instrumental-variables approach

  • M Mcclellan, J Newhouse
  • 1997

On the validity of using census geocode characteristics to proxy individual socioeconomic characteristics

  • A Geronimus, J Bound, L Neidert
  • 1996

Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak

  • J Bound, D A Jaeger, R Baker
  • 1995
Showing 1-10 of 38 extracted citations


Citations per Year

120 Citations

Semantic Scholar estimates that this publication has received between 57 and 232 citations based on the available data.

See our FAQ for additional information.