Data disaggregation for disability-inclusive development

The U.K. Department for International Development published Wednesday its first-ever Disability Framework, which reflects its ambitious vision to deliver disability-inclusive development. It signals the first step in DfID’s commitment to making its programs systematically inclusive of and accessible to people with disabilities.

It identifies a number of practical steps and actions which will help change the way the agency operates, strengthening its capacity to work on disability inclusion. Specifically, the framework sets out a clear process of accountability with the commitment to carry out an “annual stocktake to assess the extent to which DfID programs are including disability.” The department will also track which programs are collecting data on disability, and whether this is increasing.

This is alongside DfID’s commitment to advocating for the use of the U.N. Washington Group’s questions on disability in DfID-supported surveys, and influencing partners to do the same. In October, the department hosted a conference to encourage a shared understanding among bilateral and multilateral donors, civil society organizations and academics, and discussed what integrating a disability component into broader statistical data collection efforts would look like.

Detailed analysis is critical if we are to ensure development programs are accessible to all, including people with disabilities, and measure and demonstrate the effectiveness of such programs.

DfID has acknowledged that achieving its ambition will be a learning process, and in some areas it needs to build evidence and learning of what works, before adapting and strengthening their approach. There is also a shortage of evidence from development programs on how to measure disability in program data collection exercises, including by disaggregation.

To support this area of work, Sightsavers is running a pilot project to disaggregate data by disability. The aim is to help us better understand how development programs can include those most in need and are delivering demonstrable results.

For this to be successful, it is critical that policymakers, health workers and grass-roots communities engage the process and take ownership. However, through our work we have identified a number of barriers that can prevent people from engaging with providing and collecting data on disability. These include a lack of awareness around access for people with disabilities at community level, where there was a lack of knowledge that people with disabilities can and should be able to access mainstream services; and at health services level, where there was a lack of awareness of the staff working in the facilities and at a government level, with partners feeling there was a lack of support and that the inclusion of people with disabilities is not a high priority.

Ensuring understanding and creating a sense of ownership of the process starts with training.  Training is essential to sensitize staff on issues of disability and accessibility and appreciating that not all disability can be seen. In our experience, these factors are key to the process:

● Carry out training in local languages.
● Translation questionnaires and pilot testing of questionnaires as part of the training.
● Adapt the training content to the local context and national definition of disability.
● Limit references to disability, and instead refer to difficulty in functioning to reinforce the link between accessibility and functional limitations.
● Develop a clear advocacy plan to promote the project to the government.

Finally, to ensure reliable data collection, it’s essential that we show the the benefit of piloting disability disaggregation. Policymakers, data collectors and project partners need to understand what the data can tell them, how it will be used and what the benefits are for their work.

Having collected the data, it must be made use of in order to make the process meaningful. As such, Sightsavers has a responsibility to understand where we can initiate change ourselves using the data to design and monitor our programs. As a starting point, the data will tell us whether our theory that people with disabilities are currently not accessing programs supported by us proportionally is true or not, and to what extent any exclusion exists. This is a critical first step in defining the problem.

Similarly, the learning gathered during this project is crucial for policy/advocacy activities with the government, where our ability to raise awareness of the problem will be greatly enhanced by accurate data.

Inclusion is no easy task and these are some of the challenges both governments and development agencies face in trying to ensure all those in need of health and other services can and are accessing them. We hope that by sharing our learning as we go, we can play a role in meeting these challenges, and in assisting others to do the same.

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