ABSTRACT:

Some statistical issues related to the monitoring of surgical outcome quality will be reviewed in this presentation. The important role of risk-adjustment in healthcare, used to account for variations in the health conditions of patients, will be described. Several of the methods for monitoring outcome quality over time, including a new one, will be outlined and illustrated with examples. The advantages of using the conditional false alarm rate metric will be emphasized.
 
References:
Steiner, S. H. and Woodall, W. H. (2016). “Debate: What is the Best Method to Monitor Surgical Performance?”, BMC Surgery. 16:15 DOI 10.1186/s12893-016-0131-8.
Woodall, W. H., Fogel, S. L., and Steiner, S. H. (2015). “The Monitoring and Improvement of Surgical Outcome Quality”. Journal of Quality Technology 47(4), 383-399.
Zhang, X. and Woodall, W. H. (2015). “Dynamic Probability Control Limits for Risk-adjusted Bernoulli CUSUM Charts”. Statistics in Medicine 34, 3336-3348.

Bio:

William H. Woodall, Professor of Statistics at Virginia Tech, is a former editor of the Journal of Quality Technology (2001–2003) and Associate Editor of Technometrics (1987–1995; 2013). He has published well over 140 papers, most on aspects of process monitoring and health-related surveillance. He is the recipient of the ASQ Shewhart Medal (2002), ENBIS Box Medal (2012), Jack Youden Prize (1995, 2003), ASQ Brumbaugh Award (2000, 2006), Ellis Ott Foundation Award (1987), Soren Bisgaard Award (2012), Lloyd S. Nelson Award (2014), and a best paper award from IIE Transactions on Quality and Reliability Engineering (1997). He is a Fellow of the American Statistical Association, a Fellow of the American Society for Quality, and an elected member of the International Statistical Institute.