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Everyday Program Evaluation

Everyday Program Evaluation. Sheena Cretella MSPH SC DHEC Diabetes Division Program Evaluator . Today’s Objectives. Planning Programs Logic Models Evaluation Standards of Evaluation Steps to Evaluation Indicators Moderators Success Stories Data Types Collection Management.

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Everyday Program Evaluation

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  1. Everyday Program Evaluation Sheena Cretella MSPH SC DHEC Diabetes Division Program Evaluator

  2. Today’s Objectives • Planning Programs • Logic Models • Evaluation • Standards of Evaluation • Steps to Evaluation • Indicators • Moderators • Success Stories • Data • Types • Collection • Management

  3. PLANLike Your Program Depends On It! A Logic Model is like a road map Plan your route: START where you are now FINISH where you intend to be after the program How Do We get From Start To Finish?

  4. Logic Model Pieces

  5. Logic Model

  6. Logic Model

  7. Program Planning

  8. STOP: Check List for Program Planning • Do you and the stakeholders know what is going to be done, with whom, to whom/what? • Is the goal statement outcome oriented? • Are the expectations of stakeholders known to all? • Can the pieces of the logic model be measured? • Are there missing pieces or “gaps” in the logic model/plan? • Is the impact of the program important? Is there evidence?

  9. Keep In Mind • Key Questions Grantees Need to Answer About their Programs: • What role, if any, did my program play in the results? • What role, if any, did the moderators play? • Were there any unintended outcomes? • What will happen if I do not do something?

  10. The Steps to Good Program Evaluation

  11. Moderators

  12. Logic Model Moderators: Weather (drought, heat advisory, snow), safety (snakes/dogs), cost of gas (less volunteers/low attendance), neighborhood safety, inexperienced personnel, local habitat policies.

  13. Measures Each activity and outcome should have a measure. A good measure is: • Specific • Observable • Measurable • When choosing measures consider the following: • Quality of data • Quantity of data • Logistics • Sources of data collection • Primary vs. Secondary

  14. Data Management

  15. Data Sources Primary Secondary Existing data sources Before using Secondary data ensure that they will meet the evaluation needs Large ongoing surveillance systems Routinely collected Not flexible • Collecting new data • Data is from the people you work with • Common forms: • Group discussions • Observation • Document review: logs, journals, meeting minutes, sign-in sheets, etc. • Surveys: telephone, e-mail, personal, etc.

  16. Data Sources

  17. Success Story

  18. Success Story • Content • Contact Information • Photos and Logos • Quotes • Format • Brief • One Page • Bullets • Possible Inclusions: • Testimonials • Promising practices • Lessons Learned • Partner Success • New Partners Make it your own!

  19. Issue Title Impact Program Photo Contact

  20. Types of data • Make sure you are choosing the right kind of data for your specific evaluation questions. • Qualitative • Quantitative • Continuous • Categorical • Ordinal • Nominal

  21. Data Management • Physical Records • De-identify records whenever possible • Store records in a safe locked place • Shred personal data upon completion of evaluation • Electronic Records • Use unique identification numbers whenever possible • Use a password on your computer • Erase (not delete) personal data upon completion of evaluation. • Back up data.

  22. Data Management

  23. Everyday Program EvaluationThank You! Sheena Cretella MSPH SC DHEC Diabetes Division Program Evaluator cretels@dhec.sc.gov 803-545-4488

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