JMIR Publications

ABSTRACT

Background:

Cardiovascular disease remains the leading global cause of mortality, driven by interrelated behavioral, biological, and psychosocial risk factors despite the availability of effective prevention and treatment strategies. Persistent policy inertia, systemic fragmentation, and adverse social and commercial determinants have limited national responses. Addressing these gaps necessitates place-based, systems-oriented approaches that mobilize local assets, engage multi-sector stakeholders, and incorporate adaptive evaluation. The Springfield Healthy Hearts initiative exemplifies such an approach by positioning Greater Springfield as a “living laboratory” for coordinated cardiovascular health action through a comprehensive data framework, providing a replicable model for other communities.

Objective:

This protocol outlines the Springfield Healthy Hearts Data Framework; a multi-component system for dynamically guiding, implementing and evaluating coordinated action for heart health.

Methods:

The Data Framework was developed through a structured co-design process involving community members, expert researchers, health professionals, and representatives from local implementation partners. The framework comprises four integrated components: (1) Project Evaluations, applying pragmatic frameworks to assess coordinated action projects; (2) Community Evaluation, a repeated cross-sectional evaluation of Springfield residents, workers and regular visitors to capture individual-level behavioural, biological and psychosocial CVD risk factors, as well as engagement with coordinated action projects; and (3) City Evaluation, ongoing monitoring of suburb- and city-level indicators across four domains: sociodemographic characteristics, built environment, food and commercial environment and health services. (4) Data Synthesis, to utilise data across all levels to inform a continuous learning system. Project evaluations will use both quantitative and qualitative methods, including realist evaluation where appropriate. Community evaluation will be analysed using descriptive statistics, mixed-effects models and subgroup analyses, with missing data addressed via multiple imputation. City-level data will be analysed descriptively and dynamically to detect temporal trends and contextual changes.

Results:

As of February 2026, we have held two Data Framework co-design workshops with 15 community members. Their input, priorities and needs have informed our framework’s components.

Conclusions:

The Springfield Healthy Hearts Data Framework is a replicable model for other communities aiming to implement city-wide, coordinated approaches to heart health action. Findings will be disseminated through peer-reviewed publications, community reports, interactive dashboards, and policy briefs.