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The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme
Open accessAbstract
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.
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“The NASSS framework has been widely used across a range of settings for evaluating and explaining the fortunes of various kinds of health technology projects [see for example (18–20)] and draws on complexity theory (21).”
From Planning and Evaluating Remote Consultation Services: A New Conceptual Framework Incorporating Complexity and Practical Ethics (2021) · cites this paper as [19]
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“Empirical work to develop NASSS and subsequent applications has been conducted entirely in high-income settings [14, 33]; this study was the first to test its utility in a low-income setting.”
From Scale-up of a novel vital signs alert device to improve maternity care in Sierra Leone: a mixed methods evaluation of adoption (2023) · cites this paper as [33]
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2 of the 51 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Patel B, Usherwood T, Harris M, Patel A, Panaretto K, SZwar N, Peiris D: What drives adoption of computerised quality improvement tools by primary healthcare providers? An application of Normalisation Process Theory. Submitted to Implementation Science [?] 2018.
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Greenhalgh, T., Rosen, R., Shaw, S. E., Byng, R., Faulkner, S., Finlay, T., Grundy, E., Husain, L., Hughes, G., Leone, C., et al. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.726095 · Cited by 173
“19 We provide support or signposting (e.g., to community provision) for patients who wish to increase their digital skills and confidence with a view to consulting remotely.”
BackgroundSelf-citationMeunier, P.-Y., Raynaud, C., Guimaraes, E., Gueyffier, F., & Letrilliart, L. (2023) · The Annals of Family Medicine · doi:10.1370/afm.2908 · Cited by 149
Abell, B., Naicker, S., Rodwell, D., Donovan, T., Tariq, A., Baysari, M., Blythe, R., Parsons, R., & McPhail, S. M. (2023) · Implementation Science · doi:10.1186/s13012-023-01287-y · Cited by 131
Dyb, K., Berntsen, G. R., & Kvam, L. (2021) · BMC Health Services Research · doi:10.1186/s12913-021-06262-1 · Cited by 67
Chen, W., O’Bryan, C. M., Gorham, G., Howard, K., Balasubramanya, B., Coffey, P., Abeyaratne, A., & Cass, A. (2022) · Implementation Science Communications · doi:10.1186/s43058-022-00326-x · Cited by 69
Metadata
- Authors
- Abimbola, S., Patel, B., Peiris, D., Patel, A., Harris, M., Usherwood, T., & Greenhalgh, T.
- Affiliations
- UNSW Sydney (AU)
- The University of Sydney (AU)
- Corresponding author
- Greenhalgh, Trisha
- Venue
- BMC Medicine
- Published
- 2019-12
- Volume
- 17
- Issue
- 1
- Pages
- 233-233
- ISSN
- 1741-7015 (ISSN-L)
- PMC
- PMC6937726
- OpenAlex
- W2997344043
- Cited by
- 102
- References
- 51
- Citations by year
- 2026: 15 · 2025: 16 · 2024: 24 · 2023: 19 · 2022: 18 · 2021: 6 · 2020: 4
- FWCI
- 9.53
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Institute for Health Research (BRC-1215-2008)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Social Sciences › Public Administration › Evaluation and Performance Assessment
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- NASSS framework, ex-post evaluation, implementation evaluation, cardiovascular risk management, electronic decision support, general practice, clinician experience, policy incentives, process evaluation
- MeSH terms
- Cardiovascular Diseases, Humans, Retrospective Studies, Technology Assessment, Biomedical, Randomized Controlled Trials as Topic, Disease Management, Decision Support Systems, Clinical, Biomedical Technology, Quality Improvement
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