This planning tool helps CQI teams guide and track their CQI efforts.
Analyze and plan next step
Tip sheet covers considerations for developing learning questions to frame a road test and how to use them to reflect on road test results after the road test.
Tip sheet covers questions to help your team make decisions about next steps at two critical decision points in the CQI cycle – after the road test and at the end of a CQI cycle. It includes different paths based on how your team responds to key questions.
Tip sheet covers considerations for scaling and/or sustaining an improvement strategy after a CQI cycle concludes. It includes recommendations for reflecting on the key aspects of the strategy; formalizing the strategy to share with others; and creating a plan for scaling and sustainability.
Webinar covered considerations for sustaining gains from a successful CQI effort. It presents three steps that support sustaining outcomes post-testing. These steps include reflecting on learning; formalizing your improvement strategy; and planning for scaling and sustainability.
Tip sheet shares a tool that grantees can use to synthesize findings across data sources in a road test. This matrix tool is useful for organizing insights by key learning questions.
Webinar covered considerations for monitoring improvement following the implementation of a strategy. It covers the three types of measures that are helpful for assessing the success of a strategy, and introduces run charts as a useful visualization tool for monitoring improvement.
Presents one grantee’s approach to sharing survey data with staff in an accessible way. Part of a series of CQI tip sheets focusing on promising grantee practices.
Offers tips on the use of focus groups to gather detailed, action-oriented feedback from clients. Part of a series of CQI tip sheets focusing on promising grantee practices.
Webinar provided guidance and examples for how to use nFORM to support program monitoring and CQI. Featured key reports and tools in nFORM that support using and learning from programmatic data.