Demonstrating the use of process control charts: A powerful, practical visualization tool for quality improvement in residential care

As the regulatory landscape around residential care changes and agencies are required to serve children with higher levels of need, agencies will benefit from using systematic methods for monitoring key performance indicators and outcomes as they adapt to these changing conditions.

Managing quality requires awareness and curiosity – Awareness of what is going on, and curiosity about what contributes to quality and improvement. Collecting and monitoring meaningful indicators provides agencies with opportunities for learning, inquiry, and reflection – all of which can inform the process of improvement. Examples of important indicators in residential care include the frequency of physical restraints and episodes of aggression toward people or property. These kinds of events reflect moments when interactions among the children and adults in the milieu have broken down, and they represent missed opportunities for responsive care that promotes healthy developmental relationships. Analyzing these indicators can help agencies to identify significant events and trends, dig deeper to better understand contributing factors, and align their strategies more effectively. However, analysis takes effort and presents a challenge for resource-constrained agencies. User-friendly tools and methods that can assist with data management and support the analytic process are needed.

The purpose of the poster is to describe a set of quality improvement tools and methods known as statistical process control (SPC) and to demonstrate ways in which it can be applied to monitor key indicators in residential care (e.g., incidents, turnover, outcomes, satisfaction, utilization). The SPC methodology is a user-friendly approach for agencies to guide their own quality improvement efforts with rigor and with timely data that they find relevant. The ideas underlying SPC were originally used in the telephone industry and other manufacturing sectors, but their application has been extended and successfully applied in service settings such as healthcare (Berwick, 1989) and education (Bryk, 2015). A search of the literature indicates that SPC has not been used widely in residential care.

Through a collaboration between Cornell University and Hillside, a large human service organization based in central and western New York, the presenters will demonstrate how SPC methods can be applied to monitor key indicators in residential care and promote curiosity about improving quality. Using data from Hillside, we will introduce visualization tools known as process control charts and show how they can be used to describe indicators in terms of their average level and their variation over time. We will show how control charts can be used to distinguish between typical variation and instances of unusual, or special, variation. Using control charts, we can answer specific questions like “Why were the number of restraints last month higher than we would expect?” or larger system questions like “Have we reached a low threshold with the expected number of restraints that we see, or is it time to implement efforts that will improve how our system operates?”


Elliott G. Smith, Ph.D.

Research Associate , Residential Child Care Project at Cornell University


Laura Maggiulli

Director of Research and Business Intelligence, Hillside , Hillsides


Charles Izzo

Senior Research Associate , Residential Child Care Project at Cornell University