Predicting in-hospital deaths from coronary artery bypass graft surgery - Do different severity measures give different predictions?

被引:54
作者
Iezzoni, LI
Ash, AS
Shwartz, M
Landon, BE
Mackiernan, YD
机构
[1] Harvard Univ, Sch Med, Beth Israel Med Ctr, Div Gen Med & Primary Care,Dept Med, Boston, MA 02215 USA
[2] Charles A Dana Res Inst, Boston, MA 02215 USA
[3] Harvard Thorndike Lab, Boston, MA USA
[4] Boston Univ, Med Ctr, Evans Mem Dept Clin Res & Med, Sect Gen Internal Med,Hlth Care Res Unit, Boston, MA 02215 USA
[5] Boston Univ, Sch Management, Dept Management, Hlth Care Management Program & Operat, Boston, MA 02215 USA
[6] Harvard Univ, Brigham & Womens Hosp, Sch Med,Div Gen Internal Med,Dept Med, Dept Healthcare Policy,Sect Hlth Policy & Res, Boston, MA 02115 USA
关键词
severity; coronary artery bypass graft surgery; hospital mortality; administrative data;
D O I
10.1097/00005650-199801000-00005
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
OBJECTIVES. Severity-adjusted death rates for coronary artery bypass graft (CABG) surgery by provider are published throughout the country. Whether five severity measures rated severity differently for identical patients was examined in this study. METHODS. Two severity measures rate patients using clinical data taken from the first two hospital days (MedisGroups, physiology scores); three use diagnoses and other information coded on standard, computerized hospital discharge abstracts (Disease Staging, Patient Management Categories, all patient refined diagnosis related groups). The database contained 7,764 coronary artery bypass graft patients from 38 hospitals with 3.2% in-hospital deaths. Logistic regression was performed to predict deaths from age, age squared, sex, and severity scores, and c statistics from these regressions were used to indicate model discrimination. Odds ratios of death predicted by different severity measures were compared. RESULTS. Code-based measures had better c statistics than clinical measures: all patient refined diagnosis related groups, c = 0.83 (95% C.I. 0.81, 0.86) versus MedisGroups, c = 0.73 (95% C.I. 0.70, 0.76). Code-based measures predicted very different odds of dying than clinical measures for more than 30% of patients. Diagnosis codes indicting postoperative, life-threatening conditions may contribute to the superior predictive power of code-basedmeasures. CONCLUSIONS. Clinical and code-based severity measures predicted different odds of dying for many coronary artery bypass graft patients. Although code-based measures had better statistical performance, this may reflect their reliance on diagnosis codes for life-threatening conditions occurring rate in the hospitalization, possibly as complications of care. This compromises their utility for drawing inferences about quality of care based on severity-adjusted coronary artery bypass graft death rates.
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页码:28 / 39
页数:12
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