Rating the quality of intensive care units: Is it a function of the intensive care unit scoring system?

被引:88
作者
Glance, LG
Osler, TM
Dick, A
机构
[1] Univ Rochester, Sch Med & Dent, Dept Anesthesiol, Rochester, NY 14642 USA
[2] Univ Rochester, Sch Med & Dent, Dept Community & Prevent Med, Rochester, NY USA
[3] Univ Vermont, Coll Med, Dept Surg, Burlington, VT USA
关键词
intensive care units; quality; standardized mortality ratio; Acute Physiology and Chronic Health Evaluation (APACHE) II; Simplified Acute Physiology Score II; Mortality Probability Model II0;
D O I
10.1097/00003246-200209000-00005
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Objective. Intensive care units (ICUs) use severity-adjusted mortality measures such as the standardized mortality ratio to benchmark their performance. Prognostic scoring systems such as Acute Physiology and Chronic Health Evaluation (APACHE) 11, Simplified Acute Physiology Score 11, and Mortality Probability Model 110 permit performance-based comparisons of ICUs by adjusting for severity of disease and case mix. Whether different risk-adjustment methods agree on the identity of ICU quality outliers within a single database has not been previously investigated. The objective of this study was to determine whether the identity of ICU quality outliers depends on the ICU scoring system used to calculate the standardized mortality ratio. Design, Setting, Patients: Retrospective cohort study of 16,604 patients from 32 hospitals based on the outcomes database (Project IMPACT) created by the Society of Critical Care Medicine. The ICUs were a mixture of medical, surgical, and mixed medical-surgical ICUs in urban and nonurban settings. Standardized mortality ratios for each ICU were calculated using APACHE 11, Simplified Acute Physiology Score 11, and Mortality Probability Model II0. ICU quality outliers were defined as ICUs whose standardized mortality ratio was statistically different from 1. Kappa analysis was used to determine the extent of agreement between the scoring systems on the identity of hospital quality outliers. The intraclass correlation coefficient was calculated to estimate the reliability of standardized mortality ratios obtained using the three risk-adjustment methods. Measurements and Main Results., Kappa analysis showed fair to moderate agreement among the three scoring systems in identifying ICU quality outliers; the intraclass correlation coefficient suggested moderate to substantial agreement between the scoring systems. The majority of ICUs were classified as high-performance INS by all three scoring systems. All three scoring systems exhibited good discrimination and poor calibration in this data set. Conclusion: APACHE 11, Simplified Acute Physiology Score 11, and Mortality Probability Model 110 exhibit fair to moderate agreement in identifying quality outliers. However, the finding that most ICUs in this database were judged to be high-performing units limits the usefulness of these models in their present form for benchmarking.
引用
收藏
页码:1976 / 1982
页数:7
相关论文
共 36 条
[1]   Quality and the medical marketplace - Following elephants [J].
Angell, M ;
Kassirer, JP .
NEW ENGLAND JOURNAL OF MEDICINE, 1996, 335 (12) :883-885
[2]  
[Anonymous], 1990, MEDICARE STRATEGY QU
[3]   Prediction of outcome from intensive care: A prospective cohort study comparing acute physiology and chronic health evaluation II and III prognostic systems in a United Kingdom intensive care unit [J].
Beck, DH ;
Taylor, BL ;
Millar, B ;
Smith, GB .
CRITICAL CARE MEDICINE, 1997, 25 (01) :9-15
[4]   Predicting outcome in the intensive care unit using scoring systems - Is new better? A comparison of SAPS and SAPS II in a cohort of 1,393 patients [J].
Bertolini, G ;
D'Amico, R ;
Apolone, G ;
Cattaneo, A ;
Ravizza, A ;
Iapichino, G ;
Brazzi, L ;
Melotti, RM .
MEDICAL CARE, 1998, 36 (09) :1371-1382
[5]   Quality of health care .4. The origins of the quality-of-care debate [J].
Blumenthal, D .
NEW ENGLAND JOURNAL OF MEDICINE, 1996, 335 (15) :1146-1149
[6]   Quality of health care .2. Measuring quality of care [J].
Brook, RH ;
McGlynn, EA ;
Cleary, PD .
NEW ENGLAND JOURNAL OF MEDICINE, 1996, 335 (13) :966-970
[7]   Project impact: Preliminary results from a pilot validity study of a new observational database [J].
Cook, SF ;
Visscher, WA ;
Hobbs, CL ;
Williams, RL .
CRITICAL CARE MEDICINE, 1999, 27 (01) :A36-A36
[8]  
DALEY J, 1997, RISK ADJUSTMENT MEAS
[9]  
Efron B., 1993, INTRO BOOTSTRAP, V1st ed., DOI DOI 10.1201/9780429246593
[10]  
Fleiss J., 1986, Reliability of measurement: the design and analysis of clinical experiments