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Measure Testing
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Through novel qualitative and quantitative measure testing methodologies, PCPI tests measures for feasibility and scientific acceptability. We initiate testing as early as possible during the measure development process and encourage measure developers to test early and test often. 

Measure testing demonstrates that:
Measures capture the intended data
There is no significant difference in the way measures are being captured for each data source
Providers and consumers can have increased confidence in measures and measure results
Measures can be implemented with a reasonable amount of effort
Measure results provide information about the quality and value of care

Key measure testing considerations are:
Data source
Data availability
Data accuracy
Required sample sizes
Test site availability
Data reliability & validity

In addition to feasibility and scientific acceptability testing, PCPI-stewarded measures are put through rigorous testing using the BONNIE tool, developed by MITRE Corporation. Applying our testing and specification expertise to the BONNIE tool, PCPI ensures that measure logic behaves as expected, through the development of synthetic patient data, when implemented in an electronic data source.

To support measure developer testing efforts, PCPI is currently developing a testing toolkit available to PCPI members that will guide users through each step of the testing process with accessible flowcharts, checklists, and templates. Leveraging this resource can streamline and standardize the testing process for developers and establish consistently accurate results for health care performance measures.

For more information on the decision-making criteria for measure development, check out the CMS Measures Management System Blueprint.

Find out more about the measure testing process

Click here for more information about our Measurement Science consulting services.

Our Members

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