PT - JOURNAL ARTICLE AU - J C Benneyan AU - R C Lloyd AU - P E Plsek TI - Statistical process control as a tool for research and healthcare improvement AID - 10.1136/qhc.12.6.458 DP - 2003 Dec 01 TA - Quality and Safety in Health Care PG - 458--464 VI - 12 IP - 6 4099 - http://qualitysafety.bmj.com/content/12/6/458.short 4100 - http://qualitysafety.bmj.com/content/12/6/458.full SO - Qual Saf Health Care2003 Dec 01; 12 AB - Improvement of health care requires making changes in processes of care and service delivery. Although process performance is measured to determine if these changes are having the desired beneficial effects, this analysis is complicated by the existence of natural variation—that is, repeated measurements naturally yield different values and, even if nothing was done, a subsequent measurement might seem to indicate a better or worse performance. Traditional statistical analysis methods account for natural variation but require aggregation of measurements over time, which can delay decision making. Statistical process control (SPC) is a branch of statistics that combines rigorous time series analysis methods with graphical presentation of data, often yielding insights into the data more quickly and in a way more understandable to lay decision makers. SPC and its primary tool—the control chart—provide researchers and practitioners with a method of better understanding and communicating data from healthcare improvement efforts. This paper provides an overview of SPC and several practical examples of the healthcare applications of control charts.