INTENSIVE-CARE UNIT PROGNOSTIC SCORING SYSTEMS TO PREDICT DEATH - A COST-EFFECTIVENESS ANALYSIS

Objective: To evaluate the cost-effectiveness, using the technique of decision analysis, of withdrawing care from patients in the intensive care unit (ICU) who are predicted to have a high probability of death (>90%) after 48 hrs using a mortality risk estimate based on daily Acu te Physiology and Chronic Health Evaluation (APACHE) III scores. Mater ials and Methods: A decision tree model was constructed to compare the cost-effectiveness of two clinical strategies. In the first strategy, patients receive ICU care until they were discharged, died, or had ca re withdrawn based on subjective clinical criteria. In the second stra tegy, patients remained in the ICU until they were either discharged, died, or had life-sustaining care withdrawn based on subjective criter ia or if they were predicted to have a >90% risk of mortality after 48 hrs by a prognostic scoring system. Transition probabilities were bas ed on a retrospective data analysis of 4,106 noncardiac ICU patients a dmitted to a tertiary surgical ICU over a 9-yr period. Cost estimates were based on daily Therapeutic Intervention Scoring System (TISS) sco res from our database and using published data on the estimated produc tion cost for a TISS point, The sensitivity (16.6%) and specificity (9 9.6%) of the mortality risk estimate at 48 hrs (using the >90% decisio n point) based on daily APACHE III scores were derived from published data. Results: In the base case analysis, we assumed that the sensitiv ity and specificity of the prognostic risk estimate are unchanged when exported to a new environment. Hot using a prognostic scoring system as the basis for withdrawing care resulted in a slightly higher surviv al rate (87.2% vs. 86.85%) at a cost-per-death prevented (CPDP) of $26 3,700. Since prognostic scoring systems have not been shown to retain the same predictive power when exported to new databases, we chose to explore the effect of varying the specificity of the scoring system on CPDP. Decreasing the specificity from .996 (baseline) to .98 causes t he CPDP to drop to $53,300. Changing the specificity to .95 results in a CPDP prevented of $21,700. Using one-way sensitivity analysis, the CPDP is shown to be relatively insensitive to delaying the decision po int from ICU day 3 to day 7. Sensitivity analysis also indicates that CPDP increases rapidly with hospital death rate. For a death rate of 3 0%, the CPDP increases to $768,600 (in the base case, the death rate i s 12.8%); when the specificity is decreased to .95, the CPDP drops to $62,100. Conclusion: Unless daily mortality risk estimates based on AP ACHE III can be shown to retain the same level of predictive power in ICUs outside the development database, it is unlikely that the increme ntal cost-effectiveness gained by using them as the basis to withdraw care is sufficient to justify their use in this manner.