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pessimistic about this particular technology’s potential for surviving into the future, but the same service could be delivered on a substituted technology. In summary, the main complexities in the SUPPORT-HF example are the condition itself (heart failure is serious, unpredictable, heterogeneous, associated with multiple comorbidities and occurs more commonly in patients who are poor and from minority ethnic groups), untested assumptions in the value proposition (such as predicted uptake and the cost of processing remote data), the intended adopters (neither staff nor patients view the technology with unqualified enthusiasm, and a key staff group may perceive a threat to their scope of practice and job security), and the disruptive implications of the technology for organisational (and especially inter-organisational) routines. Furthermore, lack of broadband access in rural and remote parts of the UK currently preclude this technological model as a solution in the very geographical regions where it could potentially be most useful. 3. Discussion The NASSS framework has been developed relatively recently; whilst many teams around the world are currently exploring its potential, published studies of its application are limited. Indeed, we are still at the stage of formulating hypotheses which we encourage others to test. At the most broad-brush level, for example, we hypothesise that: when most or all of the NASSS domains can be classified as simple, the programme is likely to be easy to implement and to be achieved on time and within budget; when many domains are classified as complicated, the programme will be achievable but it will be difficult and likely exceed its timescale and budget; when multiple domains are complex, the chances of the programme succeeding at all are limited. The reality is that almost no technology projects in health and social care are simple. Therefore, to maximise a programme’s chances of success, efforts must be made to reduce complexity in as many NASSS domains as possible. That said, the temptation to address an oversimplified, abstracted version of the problem (in any domain) should be resisted. Bounded rationality (delineating the problem as a simple set of algorithmic decisions and defining various complicating factors as out of scope, for example) is sometimes a necessary tactic for policymakers – but it is unlikely to work in practice. Rather than oversimplifying, we suggest that the approach to the problem should incorporate acknowledging and exploring complexity in all its richness across the multiple domains of the NASSS framework – including the condition or illness, the technology, the value proposition, the intended adopters, the organisation(s), the wider context and likely evolution of the technology and the programme-in-context over time. Next, seek to identify any sub-domains in which this complexity might be reduced. This is likely to mean scaling back on the kinds of illness or condition for which the technology is claimed to be useful; reducing the technology’s interconnections (and other complex features); sharpening the value proposition; reducing the demands made on staff and patients, and proactively addressing national regulatory and policy barriers. In each of these areas for potential complexity reduction, specific theories (some of which are described above) may be relevant. T.GreenhalghandS.Abimbola /TheNASSSFramework–ASynthesisofMultipleTheories202