# Digital Health Innovation by Design: A Logic Model Scaffold for Rural, Regional, and Remote Settings

## TL;DR

This paper introduces a new logic model scaffold to better design digital health innovations for rural, regional, and remote healthcare settings.

## Contribution

A four-step iterative logic model scaffold tailored for the unique challenges of rural, regional, and remote health systems.

## Key findings

- Conventional logic models are insufficient for capturing the adaptive nature of RRR health systems.
- The proposed scaffold improves methodological rigor and responsiveness to local healthcare priorities.
- The scaffold was successfully illustrated through a case example in Northern Australia.

## Abstract

Digital health innovations (DHIs) have the potential to transform access, continuity, and quality of healthcare in rural, regional, and remote (RRR) settings, yet they often fall short in practice. Barriers extend beyond infrastructure and technology to include workforce challenges and the complex realities of delivering care across diverse geographic, cultural, and social contexts. Effective DHIs must therefore be designed with local needs and systemic constraints in mind. Conventional logic models can align inputs and activities with intended outcomes, but their linear and static assumptions often fail to capture the adaptive, relational, and place-based nature of RRR health systems. This paper presents a logic model scaffold—an iterative, four-step process for planning, implementing, and evaluating DHIs in RRR settings. Informed by program theory and implementation science, the scaffold is illustrated through a case example from the Northern Australian Regional Digital Health Collaborative. The process involves understanding context and needs, aligning interventions with system enablers, translating these into targeted activities and outputs, and embedding reflexivity and iterative adaptation. Applying the scaffold from the earliest stages of planning enhances methodological rigor, transparency, and responsiveness to local priorities, workforce realities, and system-level enablers in RRR healthcare.