The use of control charts in monitoring endophthalmitis

Abstract

Editor, The frequency of occurrence of acute infectious endophthalmitis is a good indicator of the quality of care given after cataract surgery, which is of increasing importance to both the users and providers of health care. We used quality control charts to plot the variability in the rate of endophthalmitis. These charts represent a monitoring system that sorts out ‘signals’ from ‘background noise’ (Adab et al. 2002). The method uses continuous monitoring of process variation and categorizes it into common cause or special cause variation. Successful monitoring involves identifying particular causes and then taking appropriate action against them once they have been identified. It has been effectively used in monitoring outcomes in cardiothoracic and gastro-oesophageal cancer surgery (Poloniecki et al. 1998; Tekkis et al. 2003). This is the first study demonstrating the use of control charts in ophthalmology. Data were collected retrospectively on the number of cases of acute presumed infectious endophthalmitis (PIE) that occurred after cataract surgery at two hospitals in South Wales, UK between April 2000 and March 2004. Acute PIE was defined as any clinical suspicion of endophthalmitis in a patient presenting within 3 months of cataract surgery (Desai et al. 1999). During the study period, 11 616 cataract operations were performed and 21 cases of endophthalmitis were recorded. The rates of endophthalmitis during the 4 years were 1.48, 1.49, 3.96 and 0.66 per 1000 cataract operations, respectively. Figure 1 shows that the mean rate of endophthalmitis over the 4 years of the study was 1.9 per 1000 cataract operations. The upper control limit, based on 3 standard deviations (SDs) from the mean, was six per 1000. The lower control limit, 3 SDs below the mean, was taken to be zero as it has a negative value. A control chart was constructed to plot the degree of deviation of our rate of endophthalmitis from the UK national rate, as shown in Fig. 2 (Kamalarajah et al. 2004). Control chart showing our endophthalmitis rates over 4 years. The centre line represents 1.9, the upper control limit (UCL) is 6 and the lower control limit (LCL) is 0. Three instances of special cause variations are seen as outliers above the UCL. Control chart comparing our rate of endophthalmitis against the national rate. The centre line represents the national average rate of endophthalmitis, which is plotted to be 1.4 per 1000 cataract operations. The upper control limit (UCL) is 4.9. The upper and lower control limits are 3 SDs above and below the given mean, respectively. Our hospital data for the 4 years of our study are superimposed on the plot for comparison against the national standard. Explanations were sought for the three events where the rate of endophthalmitis exceeded the upper control limit (Fig. 1) because they were special cause variations that occurred within the process. In May 2000, although fewer cataract operations were performed relative to the number of endophthalmitis cases that occurred during the same period, a special cause variation showed up on the graph as an outlier. This is an example of an outlier with a simple explanation. The second instance of special cause variation coincided with the relocation of the surgical site to a new building. In February and March 2003, a third unnatural variation required a clinical explanation and a full-blown multidisciplinary investigation was undertaken. The control chart (Fig. 1) showed signals within the existing background noise that represented a warning about the increase in the rate of endophthalmitis. Most units will experience a spurious outbreak of endophthalmitis from time to time. Control charts can predict when concern should give way to action by determining the level at which the limits are set and therefore when intervention may be indicated. More prospective studies on both regional and national levels are needed to set control limits and a national registry of endophthalmitis would enable individual units to compare outcomes. It would also identify models of good practice in surgical units where rates are low.