
The use of statistical process control methods in monitoring clinical performance
Author(s) -
Anthony Morton
Publication year - 2003
Publication title -
international journal for quality in health care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 94
eISSN - 1464-3677
pISSN - 1353-4505
DOI - 10.1093/intqhc/mzg053
Subject(s) - statistical process control , control chart , process (computing) , computer science , control (management) , statistics , reliability engineering , mathematics , artificial intelligence , engineering , operating system
To the Editor: The article by Spiegelhalter and colleagues [1] and the Counterpoint papers by Benneyan and Borgman [2], Lim [3], and Bolsin and Colson [4] deserve further comment. At least two issues should be raised, the first of which, the primacy of systems, is of crucial importance.Benneyan and Borgman state that ‘Fostering greater and more widespread use of these methods remains a significant challenge’. In Australia, statistical process control (SPC) methods were implemented with enthusiasm in the mid-1980s, as the Australian Council on Healthcare Standards (ACHS) embarked on widespread hospital accreditation. They quickly fell into disuse because they were found not to be useful. This occurred because the role of SPC was not understood. Thus we have waited nearly 20 years for their resurrection in hospitals, albeit with much improved methods. Unless we learn from the mistakes of the mid-1980s, these very valuable methods will once again be found wanting and they will once again fall into disuse.The problem is that processes must be brought into statistical control before SPC is useful; the message that control limits are useless unless the process is in control is so fundamental that it seems easily to be forgotten. It can, of course, be argued …