disaggregating routine monitoring data by disability – an example from eye health
TRANSCRIPT
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Disaggregating routine
monitoring data by disability
-an example from
eye health
Emma Jolley, Pauline Thivillier, Dominic Haslam & Archana
Bhambal
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Sightsavers
• Vision: a world where no one is blind from avoidable causes and where visually impaired people participate equally in society
• Two streams of work:• Eye health (includes NTDs)
• Inclusion, focusing on gender and disability
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Eye Health Programmes• Globally 285 million people with visual
impairments
• 80% of this is avoidable: cataract, uncorrected refractive error, trachoma…
• 90% live in developing countries
• Ultimate strategic aim for governments to ensure good quality eye care is available to all people as an integral part of wider health systems
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Monitoring equity of access
How inclusive are your eye health programmes in terms of gender?
In 2014: – 49% cataract operations were on females– 54% trachoma operations on females– 52% glasses dispensed to females
But >60% visual impairment found in females
What about people with disabilities?
• What is the prevalence of visual impairment in this group?
• How are they accessing services?
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Disability Disaggregation pilot project
The objectives of this project are to:
• Understand whether people with disabilities are accessing our services
• Build the evidence base on how to disaggregate routine data by disability
• Ultimately make Sightsavers projects more inclusive of people with disabilities.
The pilots are based in:• Eye Health Project in Bhopal, India • Neglected Tropical Disease (NTD) Projects in Tanzania and
Ghana
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Methods
• Data on disability integrated in to routine data collection tools at hospital and primary care level – paper and electronic systems
• Monthly reports developed and shared for analysis in excel and Stata
As this is a pilot we also collected data on:• Experiences of people involved in the project• Quality of the data collected
• Regular in-depth interviews and focus groups among staff involved in pilot, data quality audits and patient exit interviews [not addressed today]
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Washington Group Short Set“The next questions ask about difficulties you may have doing certain
activities because of a HEALTH PROBLEM:1. Do you have difficulty seeing, even if wearing glasses?2. Do you have difficulty hearing, even if using a hearing aid? 3. Do you have difficulty walking or climbing steps?4. Do you have difficulty remembering or concentrating?5. Do you have difficulty (with self-care such as) washing all over or
dressing?6. Using your usual (customary) language, do you have difficulty
communicating, (for example understanding or being understood by others)?”
Response categories:a) No, no difficulty, b) Yes, some difficulty, c) Yes, a lot of difficulty and d) Cannot do it at all.
7. Are you disabled? Yes/ No
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Results from Bhopal, India
Data
• 21,681 patients’ data collected in 15 months (until December 2015)
• 52% female, 48% male
• Mean (and median) age 45 years
• 58% at hospital, 42% at primary care
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Series1
0% 10% 20%
0.6%
9.0%
17.5%
Initial data from Bhopal, IndiaWhat proportion of our clients have a disability?
17.5% of project clients report severe or completely limiting difficulties in at least one domain.
9% when we exclude the sight domain.
0.6% when we ask them directly if they are disabled
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How does this compare?
2012 Census: Bhopal adults
Telengana*: Direct questioning
Pilot: Are you disabled?
Telengana*: WG severe or completely limiting difficulties
Pilot: severe or completely limiting difficulties (excluding seeing)
Pilot: severe or completely limiting difficulties
4.1%
3.8%
0.6%
7.5%
9.0%
17.5%
* International Centre for Evidence in Disability (ICED), The Telengana Disability Study, India Country Report, London School of Hygiene and Tropical Medicine (LSHTM) 2014 [available from http://disabilitycentre.lshtm.ac.uk]
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Which factors are associated with disability?
Variable Values WG severe difficulties (6Q)
WG severe difficulties (6Q) excluding seeing
Are you disabled?
Odds ratioSex Male - - -
Female 1.4*** 2.1*** 0.7* Age - binary <50 - - -
50+ 3.4*** 3.3*** 1.7** Location Hospital - - -
Primary centre 8.2*** 42.5*** 5.5***
* p-value < 0.05 ** p-value < 0.01***p-value < 0.001
Univariate associations with disability measures
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Which factors are associated with disability?
* p-value < 0.05 ** p-value < 0.01***p-value < 0.001
Variable Values WG severe difficulties (6Q)
WG severe difficulties (6Q) excluding seeing
Are you disabled?
Odds ratioSex Male - - Female 1.2*** 1.7*** 0.5*** Age - binary <50 - - -
50+ 3.6*** 3.5*** 1.5* Location Hospital - - - VC 8.4*** 40.8*** 5.8***
Multivariate associations with disability measures
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Lessons and next steps• A significant proportion of clients have functional difficulties
• The women attending our services are more likely to have difficulties functioning than men and are less likely than men to attend hospital services [not presented]
• People with disabilities, especially non-visual disabilities, are much less likely to go to hospital services.
• Services are being reviewed to improve the approach to be more gender and disability inclusive.
• Testing approaches to collecting disability data in other ways, e.g. occasional monitoring
• It is only the beginning of a fundamental shift to inclusive services
• The data collection process itself can awaken the need for inclusive services and stimulate the demand to provide them.
• Before investing in data systems, it is imperative to ensure that the data can and will be used by people with power to implement change.
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Further information:
http://www.sightsavers.org/everybodycounts/