Exponentially Weighted Moving Average Control Schemes for Assessing Hospital Organizational Performance


  • Michele Scagliarini Alma Mater Studiorum - Università di Bologna
  • Mariarosaria Apreda Alma Mater Studiorum - Università di Bologna
  • Ulrich Wienand Ospedale Universitario di Ferrara
  • Giorgia Valpiani Ospedale Universitario di Ferrara
  • Nicola Napoli Ospedale Universitario di Ferrara




Perioperative System Performance, Statistical Process Control, Exponentially Moving Average Control Charts, Organizational Indicator, Healthcare Institutions


Exponentially weighted moving average (EWMA) control charts have been successfully used in recent years in several areas of healthcare. Most of these applications have concentrated on the problem of detecting shifts in the mean level of a process. The EWMA chart for monitoring the variability has received, in general, less attention than its counterpart for the mean, although equally important and, to the best of our knowledge, it has never been used in the healthcare framework. In this work, EWMA control charts were applied retrospectively for monitoring the mean and variability of a hospital organizational performance indicator. The aim was to determine whether EWMA control charts can be used as a comprehensive approach for assessing the steady-state behaviour of the process and for early detection of changes indicating either improvement or deterioration in the performance of healthcare organizations. The results showed that the EWMA control schemes generate easy-to-read data displays that reflect process performance allowing a continuous monitoring and prompt detection of changes in process performance. Currently, hospital managers are designing an operating room dashboard which also includes the EWMA control charts.


J. C. BENNEYAN, R. C. LLOYD, P. E. PLSEK (2003). Statistical process control as a tool for research and healthcare improvement. Quality and Safety in Health Care, 12(6), pp. 458-464.

R. G. CAREY (2003). Improving healthcare with control charts. Basic and advanced SPC methods and case studies. ASQ-Quality Press, Milwaukee.

R. J. CARROLL, D. RUPPERT (1988). Transformation and Weighting in Regression. Chapman and Hall, New York.

P. CASTAGLIOLA (2005). A new S2-EWMA control chart for monitoring the process variance. Quality and Reliability Engineering International, 21(8), pp. 781-794.

S. V. CROWDER (1989). Design of Exponentially Weighted Moving Average Schemes. Journal of Quality Technology, 21(2), pp. 155-162.

S. CROWDER, M. HAMILTON (1992). An EWMA for monitoring standard deviation. Journal of Quality Technology 24(1), pp.12-21.

Y. DONG, A. S. HEDAYAT, B. K. SINHA (2008). Surveillance Strategies for Detecting Changepoint in Incidence Rate Based on Exponentially Weighted Moving Average Methods. Journal of the American Statistical Association, 103(482), pp. 843-853.

F. FALTIN, R. KENETT, F. RUGGERI (2012). Statistical Methods in Healthcare. John Wiley and Sons Ltd, Chichester.

J. FOX, S. WEISBERG (2011). An R Companion to Applied Regression, Second Edition. Sage, Thousand Oaks.

I. C. GOMES, S. A. MINGOTI, C. DI LORENZO OLIVEIRA (2011). A novel experience in the use of control charts for the detection of nosocomial infection outbreaks. Clinics 66(10), pp. 1681-1689.

F. HARROU, Y. SUN, F. KADRI, S. CHAABANE, C. TAHON (2015). Early detection of abnormal patient arrivals at hospital emergency department. 2015 International Conference on Industrial Engineering and Systems Management (IESM), pp. 221-227, IEEE Seville.

L. JONES, C. CHAMP, S. RIGDON (2001). The performance of exponentially weighted moving average charts with estimated parameters. Technometrics, 43(2), pp. 156-167.

J. LUCAS, M. SACCUCCI (1990). Exponentially weighted moving average control schemes: Properties and enhancements. Technometrics ,32(1), pp.1-12.

P. E. MARAVELAKIS, P. CASTAGLIOLA (2009). An EWMA chart for monitoring the process standard deviation when parameters are estimated. Computational Statistics and Data Analysis, 53(7) pp. 2653-2664.

S. MELO, M. BECK (2014). Quality Management and Managerialism in Healthcare. Palgrave Macmillan, Basingstoke.

M. A. MOHAMMED, P. WORTHINGTON, W. WOODALL (2008). Tutorial notes on how to plot some basic control charts. Quality and Safety in Health Care, 17(2), pp. 137-145.

M. A. MOHAMMED, P. WORTHINGTON (2013). Why traditional statistical process control charts for attribute data should be viewed alongside an xmr-chart. BMJ Quality and Safety 22(3), pp. 263-269.

M. A. MOHAMMED, J. S. PANESAR, D. B. LANEY, R. WILSON (2013). Statistical process control charts for attribute data involving very large sample sizes: a review of problems and solutions. BMJ Quality and Safety 22(4), pp. 362-368.

D. C. MONTGOMERY (2012). Introduction to statistical quality control, 7th edn. John Wiley and Sons, New York.

A. MORTON, K. MENGERSEN, M. WHITBY, G. Playford (2013). Statistical Methods for Hospital Monitoring with R. John Wiley and Sons Ltd, Chichester.

L. NOYEZ (2009). Control charts, Cusum techniques and funnel plots. A review of methods for monitoring performance in healthcare. Interactive Cardiovascular and Thoracic Surgery, 9(3), pp. 494-499.

R CORE TEAM (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.

S. ROBERTS (1959). Control chart tests based on geometric moving averages. Technometrics 1(3), pp. 239-250.

SAS INSTITUTE INC. (2014). SAS/QC 13.2 User’s Guide. SAS Institute Inc., Cary.

L. SCRUCCA (2004). qcc: an R package for quality control charting and statistical process control. R News, 4(1), pp. 11-17.

I. R. SMITH, M. A. GARDNER, B. GARLICK, R. D. BRIGHOUSE, J. CAMERON, P.S. LAVERCOMBE, K. MENGERSEN, K. A. FOSTER, J. T. RIVERS (2013). Performance Monitoring in Cardiac Surgery: Application of Statistical Process Control to a Single-site Database. Heart, Lung and Circulation 22(8), pp. 634-641.

J. THOR, J. LUNDBERG, J. ASK, J. OLSSON, C. CARLI, K.P. HRENSTAM, M. BROMMELS (2007). Application of statistical process control in healthcare improvement: systematic review. Quality and Safety in Health Care, 16(5), pp.387-399.

J. VEILLARD, F. CHAMPAGNE,N. KLAZINGA, V. A. KAZANDJIAN, O. A. ARAH, A. L. GUISSET (2005). A performance assessment framework for hospitals: the WHO regional office for Europe PATH project. International Journal for Quality in Health Care, 17(6), pp. 487-496.

U. WIENAND, G. RINALDI, G. GIANESINI, A. FERROZZI, L. PORETTI, G. VALPIANI, A. VERZOLA (2014). Management of Healthcare Processes Based on Measurement and Evaluation: Changing the Policy in an Italian Teaching Hospital. International Journal of Reliable and Quality, 3(2), pp. 15-35.

P. WINKEL, N .F. ZHANG (2007). Statistical Development of Quality in Medicine. John Wiley and Sons Ltd., Chichester.

W. H. WOODALL (2006). The use of control charts in health-care and public-health surveillance (with discussion). Journal of Quality Technology 38(2), pp. 89-134.

W. H. WOODALL, B. M. ADAMS, J. C. BENNEYAN (2012). The Use of Control Charts in Healthcare. In Faltin, F., Kenett, R. Ruggeri, F. (Eds.) Statistical Methods in Healthcare, pp. 253-267, Wiley, New York.




How to Cite

Scagliarini, M., Apreda, M., Wienand, U., Valpiani, G., & Napoli, N. (2016). Exponentially Weighted Moving Average Control Schemes for Assessing Hospital Organizational Performance. Statistica, 76(2), 127–139. https://doi.org/10.6092/issn.1973-2201/6320