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Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework

Overview of attention for article published in BMC Medicine, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

blogs
1 blog
policy
2 policy sources
twitter
106 tweeters

Citations

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62 Dimensions

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182 Mendeley
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Title
Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework
Published in
BMC Medicine, May 2018
DOI 10.1186/s12916-018-1050-6
Pubmed ID
Authors

Trisha Greenhalgh, Joe Wherton, Chrysanthi Papoutsi, Jenni Lynch, Gemma Hughes, Christine A’Court, Sue Hinder, Rob Procter, Sara Shaw

Abstract

Failures and partial successes are common in technology-supported innovation programmes in health and social care. Complexity theory can help explain why. Phenomena may be simple (straightforward, predictable, few components), complicated (multiple interacting components or issues) or complex (dynamic, unpredictable, not easily disaggregated into constituent components). The recently published NASSS framework applies this taxonomy to explain Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability. This paper reports the first empirical application of the NASSS framework. Six technology-supported programmes were studied using ethnography and action research for up to 3 years across 20 health and care organisations and 10 national-level bodies. They comprised video outpatient consultations, GPS tracking technology for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organising software and integrated case management via data warehousing. Data were collected at three levels: micro (individual technology users), meso (organisational processes and systems) and macro (national policy and wider context). Data analysis and synthesis were guided by socio-technical theories and organised around the seven NASSS domains: (1) the condition or illness, (2) the technology, (3) the value proposition, (4) the adopter system (professional staff, patients and lay carers), (5) the organisation(s), (6) the wider (institutional and societal) system and (7) interaction and mutual adaptation among all these domains over time. The study generated more than 400 h of ethnographic observation, 165 semi-structured interviews and 200 documents. The six case studies raised multiple challenges across all seven domains. Complexity was a common feature of all programmes. In particular, individuals' health and care needs were often complex and hence unpredictable and 'off algorithm'. Programmes in which multiple domains were complicated proved difficult, slow and expensive to implement. Those in which multiple domains were complex did not become mainstreamed (or, if mainstreamed, did not deliver key intended outputs). The NASSS framework helped explain the successes, failures and changing fortunes of this diverse sample of technology-supported programmes. Since failure is often linked to complexity across multiple NASSS domains, further research should systematically address ways to reduce complexity and/or manage programme implementation to take account of it.

Twitter Demographics

The data shown below were collected from the profiles of 106 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 182 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 21%
Student > Ph. D. Student 28 15%
Student > Master 26 14%
Student > Doctoral Student 14 8%
Other 14 8%
Other 33 18%
Unknown 28 15%
Readers by discipline Count As %
Medicine and Dentistry 46 25%
Social Sciences 22 12%
Nursing and Health Professions 21 12%
Computer Science 18 10%
Business, Management and Accounting 10 5%
Other 29 16%
Unknown 36 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 77. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 January 2021.
All research outputs
#312,259
of 16,650,712 outputs
Outputs from BMC Medicine
#268
of 2,633 outputs
Outputs of similar age
#10,314
of 283,202 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 16,650,712 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,633 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.1. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 283,202 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them