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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme

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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
Journal Article

The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme

2019
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Overview
Background Evaluation of health technology programmes should be theoretically informed, interdisciplinary, and generate in-depth explanations. The NASSS (non-adoption, abandonment, scale-up, spread, sustainability) framework was developed to study unfolding technology programmes in real time—and in particular to identify and manage their emergent uncertainties and interdependencies. In this paper, we offer a worked example of how NASSS can also inform ex post (i.e. retrospective) evaluation. Methods We studied the TORPEDO (Treatment of Cardiovascular Risk in Primary Care using Electronic Decision Support) research programme, a multi-faceted computerised quality improvement intervention for cardiovascular disease prevention in Australian general practice. The technology ( HealthTracker ) had shown promise in a cluster randomised controlled trial (RCT), but its uptake and sustainability in a real-world implementation phase was patchy. To explain this variation, we used NASSS to undertake secondary analysis of the multi-modal TORPEDO dataset (results and process evaluation of the RCT, survey responses, in-depth professional interviews, videotaped consultations) as well as a sample of new, in-depth narrative interviews with TORPEDO researchers. Results Ex post analysis revealed multiple areas of complexity whose influence and interdependencies helped explain the wide variation in uptake and sustained use of the HealthTracker technology: the nature of cardiovascular risk in different populations, the material properties and functionality of the technology, how value (financial and non-financial) was distributed across stakeholders in the system, clinicians’ experiences and concerns, organisational preconditions and challenges, extra-organisational influences (e.g. policy incentives), and how interactions between all these influences unfolded over time. Conclusion The NASSS framework can be applied retrospectively to generate a rich, contextualised narrative of technology-supported change efforts and the numerous interacting influences that help explain its successes, failures, and unexpected events. A NASSS-informed ex post analysis can supplement earlier, contemporaneous evaluations to uncover factors that were not apparent or predictable at the time but dynamic and emergent.