Experiences disaggregating project data by disability in Tanzania and India

© Sightsavers

Why disaggregate data?

Access is a complex issue.

Need to understand provider and user side barriers…and the bits in-between

Our theory to test: Not all of our programmes are currently accessible to people with disabilities.

First step: measure current access to see if disabled people use our services, and at what rate, relative to the non-disabled population?

Further enquiry to follow…

How are Sightsavers’ eye health and NTD programmes serving people with disabilities?

04/13/23

© Sightsavers

Disaggregation by disability

•Which definition of disability?

•Which data to disaggregate?

•Which projects to test?

•How to analyse the data?

•How do we know what proportion of our clients we would ‘expect’ to report disability?

•Practical implications for our country offices, partners and data collection staff – time, money, experience, skills, knowledge,…….

Disaggregating data in our projects

04/13/23

© Sightsavers

Pilot projects

• New eye health programme

• Urban slums• Translate WG in to Hindi• Partners: local

community development organisation and an eye hospital

• India Census 2011: 2.1% prevalence of disability in MP (Q: ‘is X disabled?’)

• Legal definition (medical certification) of disability can confer benefits

India: Bhopal

04/13/23

© Sightsavers

Pilot projects

• Neglected tropical disease project (trachoma surgeries, mass drug administration)

• Rural area• Partners: MoH

(NTD dept) and Tanzania League of the Blind

• National definition of disability similar to CRPD

Tanzania: Songea

04/13/23

2012 census•WG questions already translated (partially…)•In Ruvuma the prevalence of disability is as follows:

Albinism: 0.04% Seeing: 1.5%Hearing: 0.9% Walking: 1.2%Remembering: 1% Self-Care: 1%Other disabilities: 0.3%

© Sightsavers

Evaluation methodology

•Heavy emphasis on testing, learning and documenting

•Less emphasis on the ‘results’ during the pilot phase

•Freedom to innovate and learn through failure

•Qualitative evaluation embedded from the outset

•Share the lived experience with others

How can data disaggregated by disability be collected on a project level in a resource-efficient way that is useful to policy and decision makers?

Examples:How do programme managers understand accessibility issues within their programmes?

How time-consuming is it for receptionists to ask the questions?

Are the questions acceptable to the patients attending services?

Is the data making its way through the system accurately?

04/13/23

© Sightsavers

Early lessons

Project managers and policy makers say they don’t currently know if their programmes are accessed by people with disabilities as there is no data.

But they have many ideas about what they would do with data:

“For me in the NTD programme I would use that information to think about how many people need support and what support do they need? For example if many people are blind why would I use my resources for posters? It will help make tailored materials to make sure I deliver my messages to the right people with the right communication methods.”

“Disaggregating the data by disability will help me identify how many blind people I have in my area and then I can organise them and improve my services to them, or organise them in to self-help groups for self-development including economically.”

04/13/23

© Sightsavers

More early lessons

The WG questions provide useful data…but also have limitations.

“It is clear …it is about limitations that people experience…I think talking about limitations makes it easier for individuals to respond, as it avoids giving potentially stigmatising labels.”

“Sensitisation is again important... in [India] there is more stress on the medical definition, it’s a fact. Some people try to make the benefits by using the certificate and applying.”

“WG definition is useful as this complements the idea of knowing how people are disabled and how people face barriers to our programmes...this throws light on other aspects that may create barriers - general health conditions, sanitation conditions, faced by these people.”

04/13/23

© Sightsavers

More early lessons

“The tools will require a lot of changes and for the MDA in particular. It was easy for TT, but it will be more complicated for the MDA registers - just the tool and the understanding and the timing because it’s an addition.”

04/13/23

Changing health management information systems is hard

© Sightsavers 04/13/23

© Sightsavers

Even more early lessons

• Translation is key – 2 official languages, but 100+ in reality

“People in this region are from Ndendeule and Makua tribes, when you know Ndendeule language is fair but Makuo is very difficult to understand, it requires finding a person who can elaborate in their language.”

“For example the issue of stairs many people do not understand because village stairs are conceived as ladders to climb into the ceiling store but not stairs to go inside.”

• Additional workload

“We take long time to ask question and the patients we targeting for TT take long time instead of doing it fast to get TT patients treated in time. But for long term impact it has advantage because we get to know other problems which we did not target to solve during TT surgeries.”

04/13/23

© Sightsavers

Next steps

Future data disaggregation projects:

•Larger scale

•Data plus…

•Data disaggregation vs sentinel surveillance?

•Mhealth (EHMIS)

•What’s needed to effect change?

Measuring interaction between impairment and environment

•Model disability survey?

Continue with pilots, documenting, evaluating and sharing

04/13/23