Likely variations in perioperative mortality associated with cardiac surgery: when does high mortality reflect bad practice?
- aClinical Operational Research Unit, Department of Mathematics, University College London, 4 Taviton Street, London WC1H 0BT, UK, bCardiological Sciences, St George's Hospital Medical School, Cranmer Terrace, London SW17 0RE, UK
- C Sherlaw-Johnson
- Accepted 6 January 2000
OBJECTIVE Several methods exist for estimating the risk of perioperative mortality based on preoperative risk factors; graphical methods such as the variable life adjusted display (VLAD) can be used to examine how an individual surgeon's performance for a series of operations fares against what would be expected, given the case mix. This study aimed to devise a method for assessing the natural variation in outcome in order to assist with making judgements about individual performance, in particular whether seemingly poor performance could have occurred by chance.
METHOD The risk scoring system has been derived and validated locally for cardiac surgery. A method is described for calculating the probability that an observed number of deaths occurs within a sequence of operations if perioperative mortality is regarded as a chance event with an expected value derived from the risk score. To illustrate this method, nested prediction intervals are superimposed onto VLAD plots for a series of 393 isolated coronary artery bypass and isolated valve operations performed by a single surgeon.
RESULTS Using the locally derived risk score, the VLAD plot for the individual surgeon shows a net life gain of about 6 over the predicted number of survivors, which is observed to be within the 90% prediction interval. If the Parsonnet scoring system is used instead of the locally derived risk score, the net life gain is considerably overestimated.
CONCLUSIONS The nested prediction intervals are straightforward to generate and can be integrated into a visually informative display. As an indication of the inherent variability in outcome, they have a valuable role in the monitoring of surgical performance.