A data collection, tracking, and reporting system is required to report performance measure data. Performance measures reflect system, program, activity, and individual-level data. Data collection systems should focus on sharing data across systems and organizations and gathering information on individuals served.
Sharing data across systems and organizations requires a formal agreement or partnership to respect and adhere to data privacy laws. Examples include establishing memorandums of understanding/agreements, using parental consent forms, or applying court orders. Jurisdictions may also share data collection systems.
Individual-level data can come from professional or practitioner expertise or judgement, or it can be self-reported by individuals or their legal representative through pre- and post-assessments, surveys, exit interviews, and follow-up communication using various methods (i.e., in-person, telephone, text message, etc.).
Data can be tracked in a formal data collection system, case management system, or spread sheet. Data needs to be aggregated across the reporting period and reported across individuals served, and not per individual, to protect identities. The data reported needs to match the definitions and data requested for each performance measure.
Logic models to provide a graphic illustration of how a project’s planned activities will lead to the desired results. A logic model can help establish data collection methods by explaining the theory behind how a program or initiative works. Logic models offer the following benefits:
- Clearly identify the program or initiative’s goals, objectives, activities, and desired results.
- Clarify assumptions and relationships between the program or initiative’s efforts and expected outcomes.
- Communicate key elements of the program or initiative.
- Identify what to focus on in a program or initiative evaluation.
- Guide assessment of underlying project assumptions and promotes self-correction.
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