Glance L G, Osler T, Shinozaki T
Department of Anesthesiology, University of Vermont Medical College, Burlington 05401, USA.
Crit Care Med. 1998 Nov;26(11):1842-9. doi: 10.1097/00003246-199811000-00026.
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 Acute Physiology and Chronic Health Evaluation (APACHE) III scores.
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 In the first strategy, patients receive ICU care until they were discharged, died, or had care withdrawn based on subjective clinical criteria. In the second strategy, patients remained in the ICU until they were either discharged, died, or had life-sustaining care withdrawn based on subjective criteria or if they were predicted to have a >90% risk of mortality after 48 hrs by a prognostic scoring system. Transition probabilities were based on a retrospective data analysis of 4,106 noncardiac ICU patients admitted to a tertiary surgical ICU over a 9-yr period. Cost estimates were based on daily Therapeutic Intervention Scoring System (TISS) scores from our database and using published data on the estimated production cost for a TISS point. The sensitivity (16.6%) and specificity (99.6%) of the mortality risk estimate at 48 hrs (using the >90% decision point) based on daily APACHE III scores were derived from published data.
In the base case analysis, we assumed that the sensitivity and specificity of the prognostic risk estimate are unchanged when exported to a new environment. Not using a prognostic scoring system as the basis for withdrawing care resulted in a slightly higher survival rate (87.2% vs. 86.85%) at a cost-per-death prevented (CPDP) of $263,700. 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 the 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 point from ICU day 3 to day 7. Sensitivity analysis also indicates that CPDP increases rapidly with hospital death rate. For a death rate of 30%, the CPDP increases to $768,600 (in the base case, the death rate is 12.8%); when the specificity is decreased to .95, the CPDP drops to $62,100.
Unless daily mortality risk estimates based on APACHE III can be shown to retain the same level of predictive power in ICUs outside the development database, it is unlikely that the incremental cost-effectiveness gained by using them as the basis to withdraw care is sufficient to justify their use in this manner.
运用决策分析技术，评估基于每日急性生理学与慢性健康状况评估（APACHE）Ⅲ评分得出的死亡风险估计，对于预计48小时后死亡概率很高（>90%）的重症监护病房（ICU）患者停止治疗的成本效益。
构建决策树模型，比较两种临床策略的成本效益。在第一种策略中，患者接受ICU治疗，直至出院、死亡或根据主观临床标准停止治疗。在第二种策略中，患者留在ICU，直至出院、死亡，或根据主观标准停止维持生命的治疗，或者如果通过预后评分系统预测48小时后死亡风险>90%。转移概率基于对一家三级外科ICU在9年期间收治的4106例非心脏ICU患者的回顾性数据分析。成本估计基于我们数据库中的每日治疗干预评分系统（TISS）评分，并使用已发表的关于TISS分值估计生产成本的数据。基于每日APACHEⅢ评分得出的48小时（使用>90%决策点）死亡风险估计的敏感性（16.6%）和特异性（99.6%）来自已发表的数据。
在基础病例分析中，我们假定预后风险估计的敏感性和特异性在应用于新环境时不变。不使用预后评分系统作为停止治疗的依据，生存率略高（87.2%对86.85%），每预防一例死亡的成本（CPDP）为263,700美元。由于尚未证明预后评分系统在应用于新数据库时能保持相同的预测能力，我们选择探讨评分系统特异性变化对CPDP的影响。将特异性从0.996（基线）降至0.98会使CPDP降至53,300美元。将特异性变为0.95会使预防的CPDP为21,700美元。使用单向敏感性分析表明，CPDP对将决策点从ICU第3天推迟到第7天相对不敏感。敏感性分析还表明，CPDP随医院死亡率迅速增加。对于30%的死亡率，CPDP增至768,600美元（在基础病例中，死亡率为12.8%）；当特异性降至0.95时，CPDP降至62,100美元。
除非基于APACHEⅢ的每日死亡风险估计在开发数据库之外的ICU中能保持相同水平的预测能力，否则以其为依据停止治疗所获得的增量成本效益不太可能足以证明以这种方式使用它们是合理的。
