Organizing for Innovation: Strategic Approaches to Accelerating Digital Health and AI Innovation in a U.S. Hospital and Healthcare System Context

Abstract

Digital health and AI technologies are reshaping care delivery, presenting hospitals with both a mandate and an opportunity to lead innovation that is high-impact, effective, and scalable. However, many lack the integrated organizational strategy, ecosystem collaboration, and product-level support needed to turn ideas into real-world impact. This doctoral project investigates how hospitals, using Boston Children’s Hospital (BCH) as a case study, can strengthen their capacity to incubate, validate, and scale digital health innovations. Guided by Open Innovation, the study addressed: (1) the challenges and opportunities within the external digital health innovation ecosystem; (2) hospital-based strategies for enhancing digital health innovation throughout its lifecycle; and (3) the critical elements required for an Innovator's Toolkit enabling incubation, scaling, and commercialization within the BCH context. This mixed-methods study combined a qualitative BCH case study with design-based research (DBR) to prototype a Digital Health Innovation Toolkit. Data included immersive fieldwork (BCH), document analysis, and 15 semi-structured interviews with diverse stakeholders (hospital, product, ecosystem, industry). Thematic analysis, grounded in Open Innovation theory, was conducted, utilizing generative AI tools to augment qualitative coding and explore thematic relationships within the data. Findings highlight key external ecosystem dynamics: barriers (e.g., regulatory complexity, adoption resistance) and opportunities (e.g., strategic partnerships, patient-centered innovation). Internally, success hinges on leadership support, a culture of experimentation, and robust early validation infrastructure. A resulting five-phase innovation strategy framework, OI-aligned, guides hospital-led innovation from opportunity identification through scaling. Additionally, a modular Innovation Toolkit was produced, addressing a critical support gap by equipping staff with practical tools for product development, market analysis, and business modeling. This research contributes to theory (adapting Open Innovation for hospitals and health systems) and practice (actionable strategies/tools integrating product design, organizational capacity-building, and ecosystem collaboration). Furthermore, this research advanced hybrid methodological approaches by demonstrating the potential for generative AI to rigorously integrate qualitative thematic analysis with exploratory quantitative analysis and data visualization, as detailed in supplementary analysis. The developed framework, toolkit, AI-assisted methods offer practical guidance and a systematic approach for hospitals, researchers, and practitioners seeking to strengthen innovation capacity and accelerate digital health innovation.