Monitoring hospital trauma mortality using statistical process control methods

被引:21
|
作者
Clark, DE [1 ]
Cushing, BM [1 ]
Bredenberg, CE [1 ]
机构
[1] Maine Med Ctr, Dept Surg, Portland, ME 04102 USA
关键词
D O I
10.1016/S1072-7515(98)00109-4
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background: We sought to develop a simple and effective way to monitor trends in trauma mortality, using objective clinical categories and methods of statistical process control. Study Design: Control charts and Pareto analysis were applied to trauma mortality data at the Maine Medical Center. We collected data prospectively on patients who died in our hospital after acute injury during 1985-1996 land retrospectively for 1975-1984) to identify cases requiring medical quality review We excluded from this study patients older than 80 years, those whose Glasgow Coma Scale motor component was never >3 at any time after admission, and those with pathologic fractures, carcinomatosis, high quadriplegia, or severe burns. The remaining deaths were classified as resulting from inability to resuscitate (mostly hemorrhage), neurologic deterioration, or organ failure. The annual numbers in each of these categories were evaluated under the hypothesis of stationary Poisson processes with mean values equal to those seen from 1975-1984. Results: After the exclusions, annual mortality from trauma has remained within control limits consistent with the Poisson model. Death from neurologic deterioration has shown a trend consistent with significant improvement in the process mean. Transient peaks in the other categories did not exceed control limits, but Pareto analysis prompted detailed studies of aortic and liver trauma. Conclusions: Process control methodology is easy to apply and potentially useful in monitoring hospital trauma mortality. (C) 1998 by the American College of Surgeons.
引用
收藏
页码:630 / 635
页数:6
相关论文
共 50 条
  • [21] Statistical process control and model monitoring
    Harrison, PJ
    Lai, ICH
    JOURNAL OF APPLIED STATISTICS, 1999, 26 (02) : 273 - 292
  • [22] Survey on recursive statistical process monitoring methods
    Wang, Youqing
    Qin, Yihao
    Lou, Zhijiang
    Ma, Xin
    CANADIAN JOURNAL OF CHEMICAL ENGINEERING, 2022, 100 (09): : 2093 - 2103
  • [23] INDUSTRIAL PROCESS CONTROL BY STATISTICAL METHODS
    Freeman, H. A.
    JOURNAL OF MARKETING, 1953, 17 (03) : 336 - 336
  • [24] Statistical methods for industrial process control
    Liu, ST
    QUALITY PROGRESS, 1998, 31 (03) : 107 - 107
  • [25] STATISTICAL PROCESS-CONTROL - THE ROUTE TO QUALITY IMPROVEMENT USING STATISTICAL-METHODS
    不详
    JOCCA-SURFACE COATINGS INTERNATIONAL, 1992, 75 (03): : 113 - 113
  • [26] Quality monitoring of soybean seed tests using Statistical Process Control
    Alcantara, Aline S.
    do Prado, Jessica P.
    Correa, Rafael de G.
    da Silva, Rouverson P.
    Voltarelli, Murilo A.
    Vieira, Roberval D.
    REVISTA BRASILEIRA DE ENGENHARIA AGRICOLA E AMBIENTAL, 2018, 22 (10): : 689 - 695
  • [27] Multivariate statistical process control and process performance monitoring
    Martin, EB
    Morris, AJ
    Kiparissides, C
    DYNAMICS & CONTROL OF PROCESS SYSTEMS 1998, VOLUMES 1 AND 2, 1999, : 347 - 356
  • [28] Assessment of feeder voltage regulation using statistical process control methods
    Mago, Nitika V.
    Santoso, Surya
    McGranaghan, Mark F.
    IEEE TRANSACTIONS ON POWER DELIVERY, 2008, 23 (01) : 380 - 388
  • [29] A statistical process control procedure with adjustments and monitoring
    Park, C
    NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 2001, 47 (03) : 2061 - 2072
  • [30] Statistical process control for monitoring stepper overlay
    Flores, Gary E.
    Flack, Warren W.
    Aylakeotes, Susan
    Merrill, Mark
    Microlithography World, 4 (02):