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"A built bed is a filled bed?" An empirical re-examination
E K van Doorslaer1, R C van Vliet
1Department of Health Economics, University of Limburg, Maastricht, The Netherlands.
Social Science & Medicine (1982)
|January 1, 1989
Summary
This study re-examines hospital bed supply and care utilization. Findings show bed supply positively impacts hospital stay length, not admission rates, regardless of data aggregation level.
Area of Science:
- Health Services Research
- Health Economics
Background:
- Discrepancies exist in studies examining hospital bed supply and utilization, with differing results from individual-level (micro) and regional-level (macro) data.
- Potential causes for these discrepancies, such as aggregation and specification bias, have been hypothesized but not definitively proven.
Purpose of the Study:
- To empirically re-examine the relationship between regional hospital bed supply and hospital care utilization.
- To test the hypothesis that aggregation and specification bias explain divergent findings between micro- and macro-data studies.
Main Methods:
- Empirical re-examination of existing data on hospital bed supply and utilization.
- Analysis comparing micro-data (individual level) and macro-data (regional level) findings.
Main Results:
- Neither aggregation bias nor specification bias fully accounts for the observed differences in study findings.
- A consistent positive association was found between hospital bed supply and the length of hospital stay, irrespective of data aggregation level.
- No significant effect of hospital bed supply on hospital admission rates was observed.
Conclusions:
- The divergence in findings between micro- and macro-level studies on hospital bed supply and utilization cannot be solely attributed to aggregation or specification bias.
- The positive impact of bed supply on length of stay, independent of data aggregation, suggests other factors are at play.
- Changes in hospital service financing in the Netherlands over the past decade may influence the observed relationship between bed supply and hospital care utilization.