jueves, 12 de noviembre de 2009

NQMC - Expert Resources - Expert Commentary


A Selection of Statistical Process Control Tools Used in Monitoring Health Care Performance
By: Stephen Schmaltz, PhD


Statistical Process Control (SPC) is a methodology used for the ongoing monitoring, control, and improvement of processes through the use of statistical tools (1). SPC contains a number of graphical methods that helps achieve several objectives: quantifying one or more measures of a process; determining whether the process is operating within an acceptable range of variability; identifying ways that the process can be improved to achieve its best target value; and eliminating unacceptable variability. An example of a health care process is the prevention of patient falls in a hospital. A measure of this process would quantify the number of patient falls in a given month per 100 patient days. One would expect some patient falls every month, but that the number of patient falls would vary from month to month due to natural variation.

The purpose of this article is to briefly outline some of the SPC tools available for monitoring a health care process with corresponding references to their application. Although variability is expected in any process, reducing this variation to the extent possible and operating the process at optimal levels are the main goals. Measurement is the first step, since only through measurement are we able to determine the stability of the process and whether it operates at an acceptable level. Furthermore, only through measurement can improvement efforts be undertaken to achieve their maximum effect.

Variation constitutes an expected component of any health care process. The challenge of monitoring a health care process lies in the ability to identify when it varies systematically from its controlled pattern of operation, or a normal part of a stable process. This variation is known as common causes of variation, while the systematic deviations from this stable pattern are known as special causes of variation. Once all special causes of variation are identified and eliminated, the process can be predictably characterized and efficiently improved through systematic redesign of hospital processes, thus eliminating needless waste (2). In the patient falls example given above, a common cause of variation would be monthly differences in the number of patients on high risk medications, which could impact a patient's risk of falling. An example of a special cause would be a new, inexperienced nurse added to a floor who has not yet been fully trained in fall prevention strategies.

Control charts are a primary tool used in SPC to quantify the amount of variation in a process, determine whether the process is operating predictably, and to distinguish between common and special causes of variation. The basic control chart consists of two parts: (1) a series of measurements, or a summary of measurements within a particular time, plotted in time order and connected with a line, called the center line, and (2) two lines that frame this center line, one drawn above the center line called the upper control limit (UCL), and one drawn below the center line called the lower control limit (LCL). The control limits are used to help determine common causes from special causes of variation (3). One way to determine these limits is to examine past years' measurements to provide some indication of the degree of natural variation. An example of a control chart for patient falls is given in Figure 1.

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