Authors:
Steven M. Zimmerman Ph.D., Professor of Quality and System Management, University
of South Alabama, Mobile, Alabama. Published:46th Annual Quality Control Congress Transactions May 18-20, 1992 p903-908.
Lonnie D. Brown, Biomedical Engineering, University of South Alabama Medical Center, Mobile, AL
Shannon S. Brown, Quality Assurance, University of South Alabama Medical Center, Mobile, AL
Robert N. Zimmerman, Administrator, Biomedical Quality Control of America, Inc. Mobile, AL
Significance:The theory of runs provides us to a list of alternative rules for determining when a BiomedQC chart indicates a change. The problem is that event when the probability of an outlier is low,. the data collection rate of vital sign data results in outliers. Constant false outliers are indicated due to chance alone.
Simulation analysis assuming a stable system indicated that the system was unstable. BiomedQC charts do not use the theory of runs.
