Routine mortality monitoring for detecting mass murder in UK general practice: test of effectiveness using modelling

The Shipman Inquiry recommended mortality rate monitoring if it could be 'shown to be workable' in detecting a future mass murderer in general practice.

To examine the effectiveness of cumulative sum (CUSUM) charts, cross-sectional Shewhart charts, and exponentially-weighted, moving-average control charts in mortality monitoring at practice level.

Analysis of Scottish routine general practice data combined with estimation of control chart effectiveness in detecting a 'murderer' in a simulated dataset.

Practice stability was calculated from routine data to determine feasible lengths of monitoring. A simulated dataset of 405,000 'patients' was created, registered with 75 'practices' whose underlying mortality rates varied with the same distribution as case-mix-adjusted mortality in all Scottish practices. The sensitivity of each chart to detect five and 10 excess deaths was examined in repeated simulations. The sensitivity of control charts to excess deaths in simulated data, and the number of alarm signals when control charts were applied to routine data were estimated.

Practice instability limited the length of monitoring and modelling was consequently restricted to a 3-year period. Monitoring mortality over 3 years, CUSUM charts were most sensitive but only reliably achieved >50% successful detection for 10 excess deaths per year and generated multiple false alarms (>15%).

At best, mortality monitoring can act as a backstop to detect a particularly prolific serial killer when other means of detection have failed. Policy should focus on changes likely to improve detection of individual murders, such as reform of death certification and the coroner system.