Data allows us to see whether a process change is truly an improvement. Developing a data collection plan to evaluate progress is an important part of the PCC approach to process improvement.
A data collection plan should establish a baseline and identify measures to be tracked on a regular basis. Frequent tracking allows us to assess small tests of change and supports data driven decision-making.
Here are some examples of steps to include in a data collection plan:
- Work with clinic leadership to identify outcome measures and benchmarks
- Breast health measure examples: Mammogram referral rate, mammogram screening rate, clinical breast exam rate, cycle time from referral to screening date
- Establish baseline data for each measure. Baseline data can be collected through a sample of paper chart reviews or a data pull from an electronic health record
- Set and measure progress toward monthly goals.
- Work with the project team to report and review measures on a regular (monthly) basis, evaluate activities, and identify priority areas for continued improvement
- Perform data validity checks.