Comunicação em evento científico
REVEALING THEMES AND TRENDS IN BUSINESS MODELS IN DIGITAL HEALTH: A TEXT MINING ANALYSIS
kimia Bajelan (Bajelan, K.); Raul M. S. Laureano (Laureano, Raul M. S.); André Loureaço (Loureaço, André );
Título Evento
66th World Continuous Auditing and Reporting Symposium
Ano (publicação definitiva)
2025
Língua
Inglês
País
Portugal
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Abstract/Resumo
Digital health interventions (DHIs) are revolutionizing the healthcare sector by offering innovative solutions that can reduce costs, improve patient outcomes, facilitate access to services, and provide real-time data. To fully unlock its potential, a sustainable business model (BM) is essential. Although new medical technologies enter the market, their BMs often lack innovation. This study seeks to identify prevailing themes and emerging trends in DHI BMs, intending to provide a roadmap for future research. This study employed text mining techniques, specifically Term frequency inverse document frequency (TF-IDF) and Latent Semantic Analysis (LSA), to uncover thematic patterns in the titles and abstracts of literature (2020-2025). Topic Analysis (TA) with varimax rotation helped the identification of interpretable thematic clusters based on shared content. Eight clusters emerged, each highlighted by specific key terms: 1. AI and adoption, 2. patient service, 3. digital health, 4. digital health innovation,  5. business model, 6. market view, 7. telehealth and implementation, and 8. transformation and sustainability. The findings emphasize the central role of technology, patient empowerment, and sustainability in shaping future DHI strategies. Continued exploration is needed on how these innovations can be scaled and embedded within evolving healthcare ecosystems.
Agradecimentos/Acknowledgements
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Palavras-chave
Digital Health Interventions (DHIs) Business Models (BM) Healthcare Innovation Artificial Intelligence (AI) Patient Empowerment Telehealth Sustainability Text Mining TF-IDF Latent Semantic Analysis (LSA) Topic Analysis Healthcare Transformation Implementation Market Adoption