Evaluating Case Notes with AI | Camden, NJ
This presentation from the Camden Coalition describes a validated methodology for turning narrative case notes into structured evaluation data using AI. Developed through their Peer Support Reentry Program in Camden County, New Jersey, the approach treats AI prompts as coding instruments anchored to single, predefined constructs rather than as summarization tools. The resource covers the full workflow and includes honest reporting on where the method worked and where it did not.
How to use it
Programs can use this presentation as a methodological reference when designing AI-assisted data extraction workflows. The seven-step process and two core design principles can be adapted to other program types, note-taking systems, and evaluation contexts.
Who might use it
This resource is useful for program evaluators, researchers, and data analysts working with peer support, reentry, or case management programs who want to extract structured, analyzable data from narrative documentation and are exploring responsible uses of AI in evaluation.