Monitoring medical procedures by exponential smoothing

A new exponentially weighted moving average (EWMA) control chart well suited for 'online' routine surveillance of medical procedures is introduced. The chart is based on inter-event counts for failures recorded when the failures occur. The method can be used for many types of hospital procedures and activities, such as problems or errors in surgery, hospital-acquired infections, erroneous handling or prescription of medicine, deviations from scheduled treatments causing inconveniences for patients. The construction, the use and the effectiveness of the control chart are demonstrated by two well-known examples about wound infection in orthopaedic surgery and neonatal arterial switch surgery. The method is easy to implement and apply, it illustrates, estimates and tests the current failure rate. Comparisons with two examples from the literature indicate that its ability to quickly detect an increased failure rate is comparable to that of other well-established methods.

[1]  Noor Azina Ismail,et al.  ‘Online’ monitoring and retrospective analysis of hospital outcomes based on a scan statistic , 2003, Statistics in medicine.

[2]  J C Benneyan,et al.  Number-Between g-Type Statistical Quality Control Charts for Monitoring Adverse Events , 2001, Health care management science.

[3]  Nozer D. Singpurwalla,et al.  Understanding the Kalman Filter , 1983 .

[4]  Lloyd S. Nelson,et al.  A Control Chart for Parts-Per-Million Nonconforming Items , 1994 .

[5]  Peter R. Winters,et al.  Forecasting Sales by Exponentially Weighted Moving Averages , 1960 .

[6]  M R de Leval,et al.  Analysis of a cluster of surgical failures. Application to a series of neonatal arterial switch operations. , 1994, The Journal of thoracic and cardiovascular surgery.

[7]  J. Ord,et al.  A New Look at Models For Exponential Smoothing , 2001 .

[8]  R J Cook,et al.  Monitoring paired binary surgical outcomes using cumulative sum charts. , 1999, Statistics in medicine.

[9]  C. Holt Author's retrospective on ‘Forecasting seasonals and trends by exponentially weighted moving averages’ , 2004 .

[10]  A. Morton,et al.  Cumulative sum control charts for assessing performance in arterial surgery , 2004, ANZ journal of surgery.

[11]  Rina Chen,et al.  A Survillance System for Congenital Malformations , 1978 .

[12]  Peter A Lachenbruch,et al.  POTENTIAL USE OF THE SCAN STATISTIC FOR QUALITY CONTROL IN BLOOD PRODUCT MANUFACTURING , 2005, Journal of biopharmaceutical statistics.

[13]  John I. McCool,et al.  Control Charts Applicable When the Fraction Nonconforming is Small , 1998 .

[14]  J. Fu,et al.  Distribution of the scan statistic for a sequence of bistate trials , 2001, Journal of Applied Probability.

[15]  James M. Lucas,et al.  Exponentially weighted moving average control schemes: Properties and enhancements , 1990 .

[16]  Richard S. Leavenworth,et al.  Statistical Quality Control (5th ed.). , 1981 .

[17]  M. Caputo,et al.  Control chart methods for monitoring cardiac surgical performance and their interpretation. , 2004, The Journal of thoracic and cardiovascular surgery.

[18]  Vern T. Farewell,et al.  An overview of risk‐adjusted charts , 2004 .

[19]  Tom Treasure,et al.  Risk-adjusted sequential probability ratio tests: applications to Bristol, Shipman and adult cardiac surgery. , 2003, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[20]  I. Tager,et al.  Application of exponential smoothing for nosocomial infection surveillance. , 1996, American journal of epidemiology.

[21]  R. Brown Statistical forecasting for inventory control , 1960 .

[22]  G Gallus,et al.  On surveillance methods for congenital malformations. , 1986, Statistics in medicine.

[23]  J. Naus The Distribution of the Size of the Maximum Cluster of Points on a Line , 1965 .

[24]  Alicia D. Borgman,et al.  Risk-adjusted sequential probability ratio tests and longitudinal surveillance methods. , 2003, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[25]  S. W. Roberts Control chart tests based on geometric moving averages , 2000 .

[26]  S. Crowder A simple method for studying run-length distribution of exponentially weighted moving average charts , 1987 .

[27]  S. Steiner,et al.  Monitoring surgical performance using risk-adjusted cumulative sum charts. , 2000, Biostatistics.

[28]  F. J. Anscombe,et al.  THE TRANSFORMATION OF POISSON, BINOMIAL AND NEGATIVE-BINOMIAL DATA , 1948 .