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Quality Improvement Papers

Statistical Process Control for Health Care Quality Improvement Using SAS/QC® Software—Revised 2010
Robert N. Rodriguez and Bucky Ransdell

Abstract

Across the country, significant issues threaten the ability of hospitals to meet their commitments to their communities. These issues include the problems of retaining qualified staff and identifying incompetent staff, increasing costs of staff and supplies, and public pressure. Institute of Medicine studies show that over half of medical deaths in hospitals are preventable, and statewide data reveal variability in hospital quality.

The health care industry generates large amounts of patient-specific data. However, few hospitals can use the data to identify unusual variability in staff and physician performance, cost of care, and preventable incidents that affect the outcome of a patient’s care. SAS® Performance Management for Healthcare provides the ability to access multiple data sources and create analysis-ready data. As illustrated in this paper, statistical process control (SPC) can then be used to identify variability due to special causes and focus further study to reduce variability. These techniques lead to improvements in quality of care, reduction of costs, opportunities to grow market share, and negotiation of better third-party payment.

This paper provides examples that explain the use of SAS® statistical software to analyze health care data with u charts, p charts, control charts for individual measurements, methods for discovering trends over time, basic forecasting methods, comparative histograms, analysis of means for rates and proportions, and model-based adjustments of mortality rates.

NOTE: This paper is an updated version of a SUGI 29 paper by Rodriguez and Lewellen (2004). In particular, the examples have been revised to illustrate ODS Statistical Graphics functionality in SAS/QC® 9.2.