>Lauren Chaplinski
← all projects

Public Health Prevalence Reporting

2026

Built a reproducible analytics and reporting workflow that compares published mental health condition and substance use prevalence estimates across age cohorts, giving public-sector stakeholders a clearer, methodologically documented view of trends and benchmarks.

SASPythonPower BIDevOpsclient work: described in general, non-identifying terms

Problem

A public-sector healthcare organization needed to compare published behavioral health prevalence estimates across its service area and broader benchmarks. Source releases used different periods, geographies, estimation methods, and formats, making a direct trend view potentially misleading without documented selection and comparability rules.

Approach

Built a reproducible data preparation workflow that filters and standardizes published estimates, maps comparable measures across releases, preserves survey-period labels, and separates non-comparable periods rather than interpolating them. Produced both a portable interactive reporting model and presentation-ready comparison views, with validation checks for source and output schemas, keys, row counts, ranges, and selected value equivalence.

Outcome

Deployed the interactive report through testing and production environments for stakeholder review and public access. The reporting capability brings historical, current, and benchmark prevalence estimates into a single documented analytical structure with transparent methodology, source traceability, and explicit caveats for methodological breaks and non-comparable estimates. Stakeholder review also prompted a follow up request for presentation-ready time-series comparisons.