About the rrief
CIP’s Disability Policy Insights brief, Disability Data at Odds: A Path to Harmonization, explores why disability estimates differ across sources even within the same country. It explains how disability data harmonization can help researchers and policymakers compare results, understand exclusion, and inform inclusive policies. The brief recommends a common core of questions alongside the questions each source needs for its own purpose. Developed by Daniel Mont.
One source reports a disability prevalence rate of 5%. Another reports 15%. How can policymakers make sense of both? The answer starts with understanding what each source measures and whom it includes.
Disability data harmonization helps connect these sources. Policy Brief No. 6 in CIP’s Disability Policy Insights series explores how common questions can support comparisons and expand possible analyses, while preserving the detail each source needs.
Watch the accompanying video, then explore the policy brief for the detailed discussion, examples, and recommendations.
Why do disability estimates differ?
Censuses, household surveys, and administrative records serve different purposes. They may ask different questions, cover different populations, or use different methods. As a result, their estimates can differ without either source being wrong for the intended purpose.
What questions does each source ask?
Some sources ask about difficulties with activities such as seeing, hearing, or walking. Others ask whether people identify as having a disability or hold a disability certificate. These approaches can identify different groups.
Where does each source draw the line?
Even when sources use the same questions, they may apply different thresholds. One analysis may include people who report some functional difficulty. Another may focus on those who report a lot of difficulty or cannot do an activity.
These choices also affect how researchers measure exclusion. The threshold used can affect the number of people identified and their observed outcomes. Using a broad average can hide the barriers people with greater difficulties face, and a high threshold can hide the exclusion people with milder difficulties experience.
A household survey may exclude people living in institutions or people without housing. Administrative records only cover people who access a particular program. School records capture students, but leave out children who do not attend school.
Also, interviewer training, translations, and accessibility can affect responses. Results may also differ when one person answers for a whole household instead of each person answering for themselves.
What role can the Washington Group Short Set play?
The brief identifies the Washington Group Short Set as a strong candidate for this common core. Its short format makes it practical for different data tools. Its response options also allow researchers to examine different levels of difficulty.
However, the Short Set does not capture every disability equally well. For example, it under-identifies people with psychosocial disabilities. Some purposes therefore require additional questions or other identification methods.
How can disability data harmonization help?
The brief recommends adding a common core of disability questions across data sources. Each source can also retain questions that serve its specific purpose.
For example, a benefits program can keep its eligibility questions and add the Washington Group Short Set. If population data use the same questions, researchers can compare participants’ functional characteristics with those of the wider population.
What steps can improve disability data?
Well, we’ve already mentioned that a common core of questions is a starting point. Watch the video or download the policy brief to explore the practical steps and challenges of disability data harmonization.
