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Big Cities Health Coalition · Data Modernization Workgroup

Reuse what other health departments have already built

Browse projects from member health departments, from data pipelines and dashboards to analysis code, applications and AI tools. Each entry shows what was built, what it took, and what another city can take away.

4 use cases 2 stages 4 with source code

  • Map of Travis County ZIP codes shaded red to green by life expectancy, from 75.3 to 86.8 years.
    Open source

    Austin Health Pulse — life expectancy explorer by ZIP code

    Result in one line: Built in about 12 staff hours, against a typical agency estimate of 6–8 weeks

    An interactive map and calculator showing how life expectancy and health indicators differ across Travis County's 63 ZIP codes, with an 11.6-year gap between the longest- and shortest-lived.

    • Dashboard or visualization
    • Data pipeline or integration
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Public data only Who sees the output: Public-facing
  • Landing page headline with a Get Started button and a note not to share names or ID numbers.
    Open source

    Austin Service Guide — AI-assisted service navigation

    Residents describe their situation in a short chat and get a ranked plan of local services they may qualify for, with hours, documents to bring, and a map.

    • Application or software
    • Generative AI tool
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Public data only2 more
  • Choice between voice and text chat; the voice option says audio is sent to OpenAI.
    Open source

    Voice intake assistant for service navigation

    Residents can talk instead of type: a realtime voice assistant asks the intake questions, matches services from the catalog, and builds the same service plan as the text chat.

    • Generative AI tool
    • Application or software
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Personal information (PII) Who sees the output: Public-facing
  • Machine learning record linkage

    Efficient and accurate way to link identities across datasets

    • AI/ML model
    Skills needed to set it up: Analyst or data scientist Readiness: Needs customization Data it touches: Personal information (PII) Who sees the output: Internal staff

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Browse all 4 use cases
  • Map of Travis County ZIP codes shaded red to green by life expectancy, from 75.3 to 86.8 years.
    Open source

    Austin Health Pulse — life expectancy explorer by ZIP code

    Result in one line: Built in about 12 staff hours, against a typical agency estimate of 6–8 weeks

    An interactive map and calculator showing how life expectancy and health indicators differ across Travis County's 63 ZIP codes, with an 11.6-year gap between the longest- and shortest-lived.

    • Dashboard or visualization
    • Data pipeline or integration
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Public data only Who sees the output: Public-facing
  • Landing page headline with a Get Started button and a note not to share names or ID numbers.
    Open source

    Austin Service Guide — AI-assisted service navigation

    Residents describe their situation in a short chat and get a ranked plan of local services they may qualify for, with hours, documents to bring, and a map.

    • Application or software
    • Generative AI tool
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Public data only2 more
  • Choice between voice and text chat; the voice option says audio is sent to OpenAI.
    Open source

    Voice intake assistant for service navigation

    Residents can talk instead of type: a realtime voice assistant asks the intake questions, matches services from the catalog, and builds the same service plan as the text chat.

    • Generative AI tool
    • Application or software
    Skills needed to set it up: Developer Readiness: Needs customization Data it touches: Personal information (PII) Who sees the output: Public-facing
  • Machine learning record linkage

    Efficient and accurate way to link identities across datasets

    • AI/ML model
    Skills needed to set it up: Analyst or data scientist Readiness: Needs customization Data it touches: Personal information (PII) Who sees the output: Internal staff

Reuse over reinvention

Each entry says what another health department can take away: open-source code, code on request, templates, or a plain account of the work.

Honest notes on what it took

Entries record data sources, tools, staffing, cost and lessons learned, not just a project description.

One form, one review, then it's live

A short form opens a GitHub issue. A maintainer reviews it in a pull request and the entry publishes when it merges.

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