Measuring process improvement: Turn data haters into data fans

Collecting data is an essential part of the NIATx model, as it allows you to measure whether or not your improvement efforts are working.

Initially, staff may question the benefits of collecting and analyzing data. But a simple line graph showing positive results often transforms die-hard data skeptics into your biggest data fans. Many agencies using the NIATx model describe how initially data-averse change teams come to appreciate data because it shows that their efforts are getting results.   

Read some of their stories in the NIATx success story database.

Dr. Jay Ford, former director of research at NIATx, talks more about data (and how you can learn to love it) in a 2013 interview with the ATTC Messenger.

Dr. Ford says:

“Another significant barrier in some organizations is the perception among counselors that data takes away essential time for providing effective treatment. Organizations need to take steps to get counselors comfortable with using data and understanding why it’s important, and how it can actually increase efficiency, and how it relates to the overall mission of the organization.”

Organizations that have made the NIATx model part of their organizational culture rely on data to both make and sustain successful improvements.  

Jay Hanson, Executive Director of Prairie Ridge in Mason City, Iowa says,

 “Quality improvement efforts that rely on data are ingrained in the Prairie Ridge culture today,” says Hansen.  “A group of managers called “The Change Machine” meets regularly to collect and analyze data on different benchmarks such as wait times, length of stay, leaving against advice, and time to first treatment episode.”

(See related story: Prairie Ridge: Better tomorrow than we are today)

If you’re looking for more ideas on how to make data an integral part of your improvement projects, visit the NIATx Resource Center. Check out the six-step guide on How to Collect Data. Use the pre-formatted spreadsheets to track and measure data targeting wait times, no-show rates, and continuation.

By collecting data before, during, and after the change you implement in a NIATx change project, you can measure, evaluate, and compare your progress toward the goals you set.

Has your organization learned to love data? Have you converted a data hater into a data fan? To share your story with the NIATx E-news, send an e-mail to Maureen Fitzgerald at maureen.fitzgerald@wisc.edu