What we help you build
We work with county health departments, state agencies, health system consortia, researchers, and community organizations on the data problems that sit between raw sources and usable insight — linkage, mapping, reporting, visualization, and grant-ready technical design.
Capability areas
Scannable overview of what we do. Most engagements follow a build sequence — see our approach. Each area below links to a case study where we have a working example on this site.
Timely, geographically detailed condition estimates for community health needs assessments.
Small-area mapping and stratified analysis to document where burden concentrates.
Connect clinical, administrative, and program data without centralizing identifiable records.
Interactive maps, charts, and exports for program staff and leadership — not just analysts.
Data infrastructure plans, evaluation design, and technical components for federal and state RFPs.
Stratified, geographically granular estimates from linked clinical and administrative sources.
Developing community health needs assessments, surveillance infrastructure, or data systems to support equity-focused program evaluation.
Multi-site collaborations that need shared data standards, federated analytic pipelines, quality processes, or translation of results into accessible data products.
Studying population health outcomes where linked administrative data, geospatial analysis, or public dashboards are needed.
From CDC, NIH, HRSA, or state health departments who need a technically credible partner for data infrastructure and evaluation design components.
In detail
01
Hospitals and local health departments conducting CHNAs frequently lack access to condition prevalence data with sufficient timeliness, geographic resolution, or coverage of priority populations. We provide CHNA-ready data packages that include standardized prevalence estimates broken down by demographic group and geography.
02
We translate aggregated analytical results into publicly accessible dashboards, structured data exports, and interactive visualizations designed for use by public health practitioners, policymakers, and community organizations. We prioritize clarity, equity framing, and usability by non-technical audiences.
03
Small-area mapping that joins health outcomes with geographic, demographic, or historical policy data — census tracts, counties, custom boundaries — to support equity reporting and community-facing communication.
04
Linking clinical data to administrative sources health systems do not control — program enrollment, vital statistics, immunization registries, and agency records. We design privacy-preserving record linkage pipelines using hash-based algorithms that allow cross-source matching without transmitting personally identifiable information.
05
Directly standardized, age- and sex-adjusted prevalence estimates for physical health, mental health, and substance use conditions — stratified by race and ethnicity, geography, and social determinants. Estimates at state, county, zip code, and census tract level.
06
We support grant applications as a technical subcontractor or consultant, contributing data infrastructure plans, analytic frameworks, evaluation designs, and public health surveillance justifications. Familiar with CDC public health infrastructure grants, HRSA community health center programs, NIH observational research mechanisms, and state Medicaid evaluation frameworks.
07
For health systems and research networks operating on common clinical data standards, we support ETL pipeline development, vocabulary mapping, codeset validation, federated query architecture, and governance frameworks that keep patient-level data at contributing sites while enabling multi-site analysis.
Engagements typically begin with a scoping conversation covering your existing data environment, governance structure, near-term analytic priorities, and available funding mechanisms. From there, work is scoped as a project-based engagement, a multi-year grant subcontract, or an ongoing technical assistance retainer.
Next step
Tell us what data challenge you're working on. We'll talk through whether there's a fit and what a first phase could look like.