Abstract
PurposeAdopting Privacy Enhancing Technologies (PETs) is key to accelerating digitisation of the healthcare sector while simultaneously upholding data protection rights and increasing cybersecurity. While such technologies are market-ready, the uptake of PETs in healthcare is lagging behind. In this study we explore how conflicting logics and disciplinary disparities impact PET adoption, and how transdisciplinary (TD) methods can facilitate collaboration and mutual learning to overcome these hurdles.MethodsA sequential mixed-methods case analysis is employed, focusing on a specific multidisciplinary partnership within the healthcare sector. TD methods are used to examine challenges and underlying value systems related to PET adoption.ResultsConflicting institutional logics in healthcare, driven by missions and value systems, hinder collaborative efforts. TD methods promote awareness of disciplinary disparities, fostering an appreciative attitude toward diverse viewpoints, with an active facilitator playing a crucial role. Mutual learning aids in identifying collective actions to address challenges but may lead to tensions when issues are framed differently. TD methods, however, fall short in guiding decision-making when preferences diverge.ConclusionsSustainable PET adoption in healthcare requires addressing underlying value systems, effective communication, interdisciplinary consciousness and mutual learning. Acknowledging and managing tensions, particularly in diverse data governance contexts, proves important for successful PET adoption. Our research highlights the complexity of multidisciplinary partnerships, urging additional research to guide decision-making and governmental interventions. Ultimately, understanding these dynamics is a constructive approach for improving healthcare practices and outcomes through PET adoption.
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