Using Statistical Process Control to Make Data‐based Clinical Decisions

Abstract

Applied behavior analysis is based on an investigation of variability due to interrelationships among antecedents, behavior, and consequences. This permits testable hypotheses about the causes of behavior as well as for the course of treatment to be evaluated empirically. Such information provides corrective feedback for making data-based clinical decisions. This paper considers how a different approach to the analysis of variability based on the writings of Walter Shewart and W. Edwards Deming in the area of industrial quality control helps to achieve similar objectives. Statistical process control (SPC) was developed to implement a process of continual product improvement while achieving compliance with production standards and other requirements for promoting customer satisfaction. SPC involves the use of simple statistical tools, such as histograms and control charts, as well as problem-solving techniques, such as flow charts, cause-and-effect diagrams, and Pareto charts, to implement Deming's management philosophy. These data-analytic procedures can be incorporated into a human service organization to help to achieve its stated objectives in a manner that leads to continuous improvement in the functioning of the clients who are its customers. Examples are provided to illustrate how SPC procedures can be used to analyze behavioral data. Issues related to the application of these tools for making data-based clinical decisions and for creating an organizational climate that promotes their routine use in applied settings are also considered.

Effect of levetiracetam on human corticospinal excitability

“…21 To simplify the method, we modified it by using the statistical process control chart. 19,20 We calculated the means of rectified EMG amplitudes and consecutive difference of each point measurement during 100 milliseconds of the pretrigger period. From these values, the 95% limits of variability were derived from two sigma limits (1.77 ϫ mean consecutive deviation) below the mean value.…”

Temporal Distributions of Problem Behavior Based on Scatter Plot Analysis

“…Although visual inspection is the most common method for interpreting single-subject data, including those generated via scatter plots, it is possible that certain complex data arrays may contain patterns that escape visual detection. Therefore, in an attempt to apply precise quantitative rules to the process of interpretation, we constructed an aggregate ''control chart'' (Pfadt & Wheeler, 1995) for each scatter plot. Such charts are often used in statistical process control (SPC), which is a collection of statistical procedures typically applied to industrial manufacturing output to detect patterns of variation in production (see Wheeler & Chambers, 1992).…”

Probability and Visual Aids for Assessing Intervention Effectiveness in Single-Case Designs

“…Moreover, it was recently shown that trend may be present in SCED studies (Solomon, 2014). Given the focus on trend, we do not discuss proposals related to standard deviation bands (i.e., statistical process control; Fisher, Kelley, & Lomas, 2003;Pfadt & Wheeler, 1995) which are more appropriate for stable data. The option tested here is actually better-aligned with recent proposals intended to make dealing with trend a feasible endeavour for applied researchers with no statistical expertise (Parker, Vannest, & Davis, 2014).…”