Practical risk-adjusted quality control charts for infection control

被引:48
作者
Gustafson, TL [1 ]
机构
[1] Infect Control & Prevent Analysts Inc, Austin, TX 78735 USA
关键词
D O I
10.1067/mic.2000.109883
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Control chart methodology has been widely touted for monitoring and improving quality in the health care setting. P charts and U charts are frequently recommended for rate and ratio statistics, but their practical value in infection control may be limited because they (1) are not risk-adjusted, and (2) perform poorly with small denominators. The Standardized Infection Ratio is a statistic that overcomes both these obstacles. It is risk-adjusted, and it effectively increases denominators by combining data from multiple risk strata into a single value. Setting: The AICE National Database Initiative is a voluntary consortium of US hospitals ranging in size from 50 to 900 beds. The infection control professional submits monthly risk-stratified data for surgical site infections, ventilator-associated pneumonia, and central line-associated bacteremia. Methods: Run charts were constructed for 51 hospitals submitting data between 1996 and 1998. Traditional hypothesis tests (P values < .05) flagged 128 suspicious points, and participating infection control professionals investigated and categorized each flag as a "real problem" or "background variation." This gold standard was used to compare the performance of 5 unadjusted and 11 risk-adjusted control charts. Results: Unadjusted control charts (C, P, and U charts) performed poorly. Flags based on traditional 3-sigma limits suffered From sensitivity < 50%, whereas 2-sigma limits suffered from specificity < 50%. Risk-adjusted charts based on the Standardized Infection Ratio performed much better The most consistent and useful control chart was the mXmR chart. Under optimal conditions, this chart achieved a sensitivity and specificity > 80%, and a receiver operating characteristic area of 0.84 (P < .00001). Conclusions: These findings suggest a specific statistic (the Standardized Infection Ratio) and specific techniques that could make control charts valuable and practical tools for infection control.
引用
收藏
页码:406 / 414
页数:9
相关论文
共 17 条
[1]   Risk-adjusted control charts for health care assessment [J].
Alemi, F ;
Rom, W ;
Eisenstein, E .
ANNALS OF OPERATIONS RESEARCH, 1996, 67 :45-60
[2]  
Benneyan JC, 1998, INFECT CONT HOSP EP, V19, P265
[3]  
Benneyan JC, 1998, INFECT CONT HOSP EP, V19, P194
[4]   ANALYSIS OF HOSPITAL INFECTION SURVEILLANCE DATA [J].
BIRNBAUM, D .
INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, 1984, 5 (07) :332-338
[5]  
Birnbaum D, 1996, INFECT CONT HOSP EP, V17, P348
[6]  
CAREY RG, 1995, MEASURING QUALITY IM, P42
[7]  
Finison L J, 1993, J Healthc Qual, V15, P9
[8]   THE EFFICACY OF INFECTION SURVEILLANCE AND CONTROL PROGRAMS IN PREVENTING NOSOCOMIAL INFECTIONS IN UNITED-STATES HOSPITALS [J].
HALEY, RW ;
CULVER, DH ;
WHITE, JW ;
MORGAN, WM ;
EMORI, TG ;
MUNN, VP ;
HOOTON, TM .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 1985, 121 (02) :182-205
[9]  
Humble C, 1998, INFECT CONT HOSP EP, V19, P865
[10]   Using laboratory-based surveillance data for prevention: An algorithm for detecting Salmonella outbreaks [J].
Hutwagner, LC ;
Maloney, EK ;
Bean, NH ;
Slutsker, L ;
Martin, SM .
EMERGING INFECTIOUS DISEASES, 1997, 3 (03) :395-400