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Published on: January 16, 2019
Intensive care unit prognostic scoring systems to predict death: a cost-effectiveness analysis
L G Glance1, T Osler, T Shinozaki
1Department of Anesthesiology, University of Vermont Medical College, Burlington 05401, USA.
Critical Care Medicine
|November 21, 1998
Summary
Using the APACHE III score to withdraw ICU care for high-risk patients is not cost-effective unless its predictive power is validated in new settings. Further research is needed to justify this approach.
Area of Science:
- Critical Care Medicine
- Health Economics
- Medical Decision Making
Background:
- Withdrawing care in intensive care units (ICUs) involves complex clinical and ethical considerations.
- Prognostic scoring systems aim to objectively predict patient outcomes, but their generalizability can be limited.
Purpose of the Study:
- To assess the cost-effectiveness of using mortality risk estimates from the APACHE III score to guide decisions on withdrawing care in the ICU.
- To compare this strategy against traditional subjective clinical criteria.
Main Methods:
- A decision tree model was developed to compare two strategies: standard care withdrawal vs. care withdrawal based on APACHE III scores (>90% mortality risk at 48 hours).
- Data from 4,106 noncardiac ICU patients were analyzed for transition probabilities.
- Cost estimates were derived from Therapeutic Intervention Scoring System (TISS) scores and published production costs.
Main Results:
- The strategy using APACHE III scores resulted in a slightly lower survival rate (86.85% vs. 87.2%) compared to subjective criteria.
- The cost-per-death prevented (CPDP) was significantly higher ($263,700) without the scoring system in the base case.
- Decreasing the specificity of the APACHE III score significantly reduced CPDP, highlighting the impact of predictive accuracy.
Conclusions:
- The use of APACHE III scores for withdrawing ICU care is unlikely to be cost-effective unless validated in external databases.
- The incremental cost-effectiveness may not justify the use of these scores without proven external predictive power.
