TY - JOUR T1 - Using statistical process control to improve the quality of health care JF - Quality and Safety in Health Care JO - Qual Saf Health Care SP - 243 LP - 245 DO - 10.1136/qshc.2004.011650 VL - 13 IS - 4 AU - M A Mohammed Y1 - 2004/08/01 UR - http://qualitysafety.bmj.com/content/13/4/243.abstract N2 - To achieve continuous quality improvement “it is not enough to do your best …” Continuous improvement in health care and elsewhere is not a contentious issue—but the means by which this may be achieved is the subject of much debate. A key aspect of continuous improvement is the measurement, analysis, and interpretation of variation. Consider, for example, the data in table 1 which shows surgeon specific mortality rates after colorectal cancer surgery.1 Ranking the mortality rates or the adjusted hazard ratios, with or without statistical tests, invites the interpretation that some surgeons are better than others. Furthermore, since a hazard ratio of 1 is defined as neutral, surgeons with a hazard ratio above 1 are considered a hazard to their patients. So, by categorising the hazard ratio as either acceptable or unacceptable, the study concludes that “some surgeons perform less than optimal surgery; some are less competent technically than their colleagues…” To improve outcomes the next logical step is to stop the less competent surgeons from operating and transfer their patients to the more competent surgeons. Surprisingly, perhaps, there is another way of analysing these data using statistical process control (SPC) which leads to very different conclusions.View this table:In this windowIn a new window Table 1  Surgeon specific mortality rates following colorectal cancer surgery In the 1920s Walter A Shewhart, a physicist, was charged with improving the quality of telephones in Bell Laboratories, USA. His work there won him the accolade of the “father of modern quality control”.2 Shewhart developed a theory of variation3 which forms the basis of SPC. His theory is easily illustrated. Consider the first five “QSHC” signatures in fig 1. Two important observations can be made: (1) despite being produced by the same process, they show variation; and (2) the variation is controlled—it lies within certain limits. If nothing is … ER -