LESSON 3:II – WHAT ARE KEY CONCEPTS AND TERMS TO EXPLORE?
INTRODUCTION TO PLANNING WITH CQI
In this session we will continue to learn about CQI and explore how data assist us in our efforts to plan a new innovation, initiative, experiment or program. A data-informed CQI process provides us with an avenue to examine our program practice and community work. The focus is to improve outcomes for the children and families we seek to serve.
CQI helps a local office plan the entire innovation process — moving through assessment of a problem to planning a solution.
The more carefully thought out a plan, the better chance for conducting a successful local innovation.
In this session we will learn about evidence-based practice, policies, and programs in behavioral health, child welfare, public health, youth development, child development and education. We focus on research-based strategies. There are many sources for evidence-informed practice available through research on the Internet.
Policy analysis (the critical review of policy, procedures and programs) is a vital skill that helps us understand why certain strategies are called evidence-based while others may have little quality research to support them.
By using data and measurement, we are able to demonstrate how our practice, including the protocols we follow and the policies we work with, impacts outcomes for our children and families. The research conducted during this planning phase of CQI will play a vital role in informing the development of a local innovation.
In the planning phase, we also explore using logic models as a planning tool for our innovations and initiatives.
Our logic models, graphic representations of a project plan, create a shared vision for moving forward. Logic model components include:
Hypothesis: A statement that follows science-based thinking, “If we do A, then B will happen.”
Goal + Purpose: Identifying what you hope to achieve and why.
Inputs: What partners, resources and processes you need in place to achieve goals.
Activities: What data-driven activities you will implement to create change.
Outputs: What occurs or is created as a result of activities.
Outcomes: Short, intermediate and long-term measurable results. The planning phase prepares you to implement a science-based process with measurable and meaningful outcomes. The logical model guides the process.