Welcome

Bridgeframe is a practical toolkit for professionals who work at the intersection of information technology and public health. Whether you are a business analyst stepping into your first health department project, or a public health professional learning to collaborate with software teams, this book provides the translation layer you need.

About This Toolkit

Bridgeframe is a work in progress, not an authoritative guide. The scenarios and examples throughout (including the CancerSurv case study) are illustrative and fictitious, designed to help professionals relate to common challenges in health IT projects.

The goal is educational: to spark discussion, point readers toward established frameworks (BABOK, CDC methodologies, CFIR, and others), and provide a starting point for teams navigating this intersection. Feedback and contributions are welcome as this resource continues to evolve.

0.1 The Challenge

Two disciplines. Two languages. One shared goal: building systems that improve health outcomes.

Business analysts speak of user stories, sprints, and requirements traceability. Public health professionals speak of logic models, PDSA cycles, and program evaluation. Both are trying to define problems, design solutions, and measure success, yet their terminology creates friction rather than collaboration.

0.2 The Solution

Logic Model Components Mapped to Requirements Bridgeframe provides:

A terminology dictionary mapping IT/Agile concepts to their public health equivalents
Phase-by-phase guidance aligning the BABOK lifecycle with CDC frameworks
A running case study (CancerSurv) demonstrating concepts in practice
Templates and tools for hybrid teams

0.3 Who This Book Is For

IT Business Analysts entering the public health sector
Public Health Informaticians collaborating with software vendors
Project Managers overseeing health IT implementations
Data Scientists working with epidemiological systems
Students in health informatics or public health programs

0.4 How to Use This Book

This book is organized into three parts:

Foundations: Core concepts, terminology mapping, and the CancerSurv case study
The Analysis Process: Phase-by-phase guidance from planning through evaluation
Putting It Into Practice: Tools comparison and implementation science frameworks

Each chapter includes CancerSurv examples in callout boxes, making abstract concepts concrete.

Getting Started

If you are new to this intersection, start with Chapter 1: Introduction and the Terminology Dictionary. If you are already working on a project, jump to the relevant phase chapter.

0.5 About the Author

André van Zyl, MPH is an epidemiologist and data science professional with close to two decades of experience spanning public health, health informatics, and technical system development. His career has taken him across local, state, federal, tribal, and international health systems, from helping establish global surveillance systems at the CDC to implementing health interventions in resource-constrained settings.

As a Health Scientist at CDC’s National Center for Emerging and Zoonotic Infectious Diseases, André led data acquisition and reporting systems for global antimicrobial resistance surveillance spanning multiple continents. He pioneered the integration of artificial intelligence into public health workflows and modernized data processes using R, Python, Azure Databricks, and platforms like REDCap and DHIS2. A consistent theme throughout his work has been technical translation: bridging communication gaps between laboratory scientists, clinical teams, and technical developers.

André holds a Master of Public Health from the University of Pretoria and a BA Honors in Psychology from Nelson Mandela University. This combination of behavioral science and technical expertise enables him to understand both user needs and system requirements when implementing solutions across diverse communities.

He is the founder of Intersect Collaborations LLC, a consultancy helping public health organizations transform data systems and analytics capabilities for improved decision-making and community health outcomes.

--- title: "Bridgeframe" subtitle: "Bridging Business Analysis and Public Health" --- # Welcome {.unnumbered} **Bridgeframe** is a practical toolkit for professionals who work at the intersection of information technology and public health. Whether you are a business analyst stepping into your first health department project, or a public health professional learning to collaborate with software teams, this book provides the translation layer you need. ::: {.callout-note title="About This Toolkit"} Bridgeframe is a work in progress, not an authoritative guide. The scenarios and examples throughout (including the CancerSurv case study) are illustrative and fictitious, designed to help professionals relate to common challenges in health IT projects. The goal is educational: to spark discussion, point readers toward established frameworks (BABOK, CDC methodologies, CFIR, and others), and provide a starting point for teams navigating this intersection. Feedback and contributions are welcome as this resource continues to evolve. ::: ## The Challenge Two disciplines. Two languages. One shared goal: building systems that improve health outcomes. **Business analysts** speak of user stories, sprints, and requirements traceability. **Public health professionals** speak of logic models, PDSA cycles, and program evaluation. Both are trying to define problems, design solutions, and measure success, yet their terminology creates friction rather than collaboration. ## The Solution Logic Model Components Mapped to Requirements Bridgeframe provides: - **A terminology dictionary** mapping IT/Agile concepts to their public health equivalents - **Phase-by-phase guidance** aligning the BABOK lifecycle with CDC frameworks - **A running case study** (CancerSurv) demonstrating concepts in practice - **Templates and tools** for hybrid teams ## Who This Book Is For - **IT Business Analysts** entering the public health sector - **Public Health Informaticians** collaborating with software vendors - **Project Managers** overseeing health IT implementations - **Data Scientists** working with epidemiological systems - **Students** in health informatics or public health programs ## How to Use This Book This book is organized into three parts: 1. **Foundations**: Core concepts, terminology mapping, and the CancerSurv case study 2. **The Analysis Process**: Phase-by-phase guidance from planning through evaluation 3. **Putting It Into Practice**: Tools comparison and implementation science frameworks Each chapter includes CancerSurv examples in callout boxes, making abstract concepts concrete. ::: {.callout-tip title="Getting Started"} If you are new to this intersection, start with [Chapter 1: Introduction](chapters/01-introduction.qmd) and the [Terminology Dictionary](chapters/03-terminology.qmd). If you are already working on a project, jump to the relevant phase chapter. ::: ## About the Author **[André van Zyl, MPH](https://www.linkedin.com/in/andre-van-zyl/)** is an epidemiologist and data science professional with close to two decades of experience spanning public health, health informatics, and technical system development. His career has taken him across local, state, federal, tribal, and international health systems, from helping establish global surveillance systems at the CDC to implementing health interventions in resource-constrained settings. As a Health Scientist at CDC's National Center for Emerging and Zoonotic Infectious Diseases, André led data acquisition and reporting systems for global antimicrobial resistance surveillance spanning multiple continents. He pioneered the integration of artificial intelligence into public health workflows and modernized data processes using R, Python, Azure Databricks, and platforms like REDCap and DHIS2. A consistent theme throughout his work has been technical translation: bridging communication gaps between laboratory scientists, clinical teams, and technical developers. André holds a Master of Public Health from the University of Pretoria and a BA Honors in Psychology from Nelson Mandela University. This combination of behavioral science and technical expertise enables him to understand both user needs and system requirements when implementing solutions across diverse communities. He is the founder of **[Intersect Collaborations LLC](https://www.linkedin.com/company/intersect-collaborations-llc/)**, a consultancy helping public health organizations transform data systems and analytics capabilities for improved decision-making and community health outcomes.