Not every mHealth project is appropriate to scale up—small mHealth deployments often serve a specific short-term function. However, some mHealth projects could make a significant social impact if scaled. This section of the Guide summarizes best practices for ensuring scalability, focusing on nine best practices for ensuring scalability of an mHealth project, drawn from case studies and expert interviews. Many of these practices are discussed in depth throughout the Guide, and they are paraphrased on the next page.
In November 2013, the mHealth Working Group hosted a meeting on the topic of scaling up mHealth. The presentations, given by JSI and The World Bank, are available for download and provide scale-up considerations based on the case examples of cStock and Programme Mwana.
Key scale-up considerations, many of which are also explored elsewhere in this Guide, are discussed below. Some of these questions have been adapted from Expandnet’s Beginning with the end in mind: Planning pilot projects and other programmatic research for successful scaling up, which provides a checklist for assessing the scalability of a pilot project. Others were adapted from the article Applying a framework for assessing the health system challenges to scaling up mHealth in South Africa. (Full references are at the bottom of the page.)
Feasibility of the mHealth solution
- Does the mHealth solution effectively and efficiently address a persistent health or service delivery challenge, and is it feasible in the settings in which it will be scaled up?
- Does the mHealth solution embody community, cultural, language, gender, institutional, and other factors that might help or hinder scale-up, and what adjustments will be necessary to adapt the program to new contexts?
- Has the mHealth solution been tested in the kinds of sociocultural, geographic, and institutional settings in which it will be replicated?
- Does the implementation plan allow enough flexibility to incorporate new knowledge, lessons learned, and technological developments into the process as needed? For example, can the mHealth application be adapted to continually changing technological reality?
- How will the particular types of M&E data you plan to collect inform the decision of whether to scale up the program?
- Is there evidence that the mHealth solution is cost-effective?
Support for scale-up at the systems level
- Is the leadership thinking strategically about the place of mHealth in the health system, fostering a supportive culture, and willing to allocate the resources necessary for scale-up?
- Is the mHealth solution integrated into existing systems? Are there clear, universal standards for usability, interoperability, and privacy and security that can be applied at scale?
- Has a strategy been developed to advocate for any necessary changes in policies, regulations, and procedures in order to institutionalize the mHealth solution?
- Does the mHealth program have sustainable access to human and financial resources, and does the health system have the capacity to implement the solution at a larger scale?
- Do the existing local technological partners have the capacity to support the technological requirements of scaling up the program?
Benefits of scale-up
- If the mHealth solution is offered on a larger scale, what are the potential cost efficiencies? In other words, what are the estimated cost savings or increases that could occur at scale?
- How could the mHealth program to contribute to additional health and/or development issues as well as broader national mHealth goals?
Beginning with the end in mind: Planning pilot projects and other programmatic research for successful scaling up. World Health Organization and ExpandNet. 2011.
Lemaire J. Scaling up Mobile Health: Elements Necessary for the Successful Scale-up of mHealth in Developing Countries. Advanced Development for Africa and Actevis Consulting Group. 2011.
Leon N, Schneider H, Daviad E. Applying a framework for assessing the health system challenges to scaling up mHealth in South Africa. BMC Medical Informatics and Decision Making. 2012;12;123.