We consider the problem of monitoring and comparing medical outcomes, such as surgical performance, over time. Performance is subject to change due to a variety of reasons including patient heterogeneity, learning, deteriorating skills due to aging, etc. For instance, we expect inexperienced surgeons to improve their skills with practice. We propose a graphical method to monitor surgical performance that incorporates risk adjustment to account for patient heterogeneity. The procedure gives more weight to recent outcomes and down-weights the influence of outcomes further in the past. The chart is clinically interpretable as it plots an estimate of the failure rate for a "standard" patient. The chart also includes a measure of uncertainty in this estimate. We can implement the method using historical data or start from scratch. As the monitoring proceeds, we can base the estimated failure rate on a known risk model or use the observed outcomes to update the risk model as time passes. We illustrate the proposed method with an example from cardiac surgery.
Keywords: Exponentially weighted moving average; Likelihood; Score function; Weighted estimating equation.
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