Krahe, Michelle A., Adams, Nico, and Larkins, Sarah L. (2025) Digital Health Innovation by Design: A Logic Model Scaffold for Rural, Regional, and Remote Settings. International Journal of Environmental Research and Public Health, 32 (11). 1743.

Preview

PDF (Published Version) - Published Version Available under License Creative Commons Attribution. Download (498kB) | Preview

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.

Item ID:	89705
Item Type:	Article (Research - C1)
ISSN:	1660-4601
Copyright Information:	© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)
Date Deposited:	24 Nov 2025 23:13
	More Statistics