Spreading and scaling up innovation and improvement
BMJ 2019; 365 doi: https://doi.org/10.1136/bmj.l2068 (Published 10 May 2019) Cite this as: BMJ 2019;365:l2068Read the full collection
- Trisha Greenhalgh, professor,
- Chrysanthi Papoutsi, postdoctoral researcher
- Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
- Correspondence to T Greenhalgh trish.greenhalgh{at}phc.ox.ac.uk
Key messages
Spread (replicating an intervention) and scale-up (building infrastructure to support full scale implementation) are difficult
Implementation science takes a structured and phased approach to developing, replicating, and evaluating an intervention in multiple sites
Complexity science encourages a flexible and adaptive approach to change in a dynamic, self organising system
Social science approaches consider why people act in the way they do, especially the organisational and wider social forces that shape and constrain people’s actions
These approaches may be used in combination to tackle the challenges of spread and scale-up
The general practitioner in the surgery, the nurse manager on the ward, and the policy maker in the boardroom would be forgiven for losing track of all the new technologies, care pathways, and service models that could potentially improve the quality, safety, or efficiency of care. Yet we know that innovations rarely achieve widespread uptake even when there is robust evidence of their benefits (and especially when such evidence is absent or contested).1 The NHS Long Term Plan points out that every approach prioritised in the plan is already happening somewhere in the NHS but has not yet been widely adopted.2
There are common sense reasons why spreading an innovation across an entire health system is hard. Achieving any change takes work, and it usually also involves—in various combinations—spending money, diverting staff from their daily work, shifting deeply held cultural or professional norms, and taking risks. Simplistic metaphors (“blueprint,” “pipeline,” “multiplier”) aside, there is no simple or universally replicable way of implementing change at scale in a complex system. A technology or pathway that works smoothly in setting A will operate awkwardly (or not at …