Conceptual models for scale-up | Major constructs influencing scale up | Reference to time sensitivity |
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Yamey G (2011) | Identifies following factors • Choose a simple intervention that is considered valuable. • Develop strong leadership • Ensure active engagement of range of stakeholders, including the target community • Incorporate research into implementation | Identifies 5 factors associated with faster diffusion of an innovation: • Relative advantage • Compatibility • Simplicity • Trialability • Observability Plus, • Integrate into existing health systems • Generation of timely evidence. • Timely feedback of monitoring data to implementers |
Spicer N, et al. (2014) | Identifies multiple steps to catalyse scale up. • Design scalable innovations • Embed scale up in programme design • Build implementer capacity • Advocate on an on-going basis • Generate strong evidence • Involve government throughout project • Invoke policy champions and network of allies • Align with policy and targets • Promote community acceptance and uptake. | • Stresses the need for longer donor timelines and commitment for scale up, as it takes time for programmes to mature and for implementers to advocate and support government. Typical 2–3 year donor funding cycles are too short. |
Subramanium S, et al. (2011) | • Tailor scale-up to fit the particular context. • Adopt a “learning by doing” approach, linking knowledge building with action. • Take into consideration the political, social, and economic environment. • Forge strong partnerships and adopt a participatory approach to foster ownership and sustainability • Focus on problem solving, and draw on a variety of quantitative and qualitative monitoring and evaluation methods. Don’t over rely on the randomised control trial approach. | • Acknowledges that successful scale up of pilot projects requires a medium to long term timeframe. • Slower, phased implementation, usually from the bottom up, which allows for systematic learning to emerge through incremental expansion based on concurrent, participatory research and adaptation |
WHO ExpandNet: 1. Beginning with the end in mind, Planning Pilot Projects and other Programmatic Research for Successful Scale Up (2011) 2. Nine Steps for developing a Scaling Up Strategy (2010) | • Adopt a participatory process for innovation testing (including stakeholder involvement in the design, regular provision of feedback on implementation, nurture policy champions and wider networks). • Reach consensus on scaling up expectations • Tailor innovation to prevailing socio-cultural and institutional environment and test innovation under routine operating conditions and within existing resource constraints of the health system • Test ways to strengthen health-systems capacity as part of the project, for example (human or technical) • Advocate to donors and other funding sources for financial support for scale up once innovation proven to have impact • Search and test for sustainable finance • Prepare to advocate for necessary changes in policy regulation, and other health system context. • Promote learning and disseminate information. • Increase the capacity of the user organization to implement scale up. • Increase the capacity of the user team to support scaling up process • Prove support to vertical (institutionalization) and horizontal scale up (expansion/replication) scale up. | • No explicit reference to rapidity but Includes recommendation on advocacy with donors and other funding sources for financial support for scale up once innovation is proven to be successful. This will potentially expedite scale-up. Similarly, participatory process for innovation testing will potentially lead to rapid adoption. |
Barker P. M, et al. (2016) | • Identifies 4 step sequential scale up process: o Set up (prepare ground and test intervention) o Develop scalable unit o Test scale up in different settings o Go to full scale • Enabling factors include: o Develop and engage leaders in their key role of guiding and supporting large scale change. o Accommodate context into design by starting with a deep dive situational analysis with key stakeholders. o Maintain a culture of urgency and persistence, and will to stay the course in proving an innovation and bringing it to scale. o Adoption of a learning approach which includes the continuous feedback of data to identify and close gaps in performance. o Communicate real time data and results on a regular basis. | • Although a linear scale up process is presented, the paper highlights it can be organic and iterative, with streams of work initiated at different times and progressing at different rates. Though not explicitly stated, this would be time saving. • Stresses rapid scale up will not occur in an unreceptive environment. • Country case studies suggest it can take up to 6 years to go from develop scalable unit to full scale. |
Paina L and Peter D, (2012) | • Examines characteristics of scale up using an alternative model drawing on an understanding of complex adaptive systems (CAS): o Scale up occurs within complex and dynamic health systems, and the lens of CAS allows for better planning, implementation, monitoring and evaluation of scale up. o Lessons from CAS suggest giving more attention to local context, incentives, institutions, and paying greater attention to unintended consequences undermining scale up. o Includes adopting an approach that engages key stakeholders, through the transparent use of data on an on-going problem solving and adaption. | • CAS is a slow and deliberate approach. However, it recognises that a small stimulus can create a large or rapid change. • Phase transitions or tipping points can lead to rapid scale up. Acknowledges the importance of identifying the conditions under which rapid transitions can occur. |