This was presented by Fabrizio Scrollini from the Latin American Open Data Initiative (ILDA) at the Impacts of Civic Technology Conference (TICTeC 2017) in Florence on 25th April. You can find out more information about the conference here: http://tictec.mysociety.org

1. Fabrizio Scrollini, Ph.D
Executive coordinator
@fscrollini
@idatosabiertos
Keeping health on Check :Open Data for Health
Service Delivery

2. Research question:
• Does open data lead to better health service delivery?
• Does data help me ,my family and my community to get a
decent health service?
Scope &methodology:
• Three case studies: Peru, Mexico and Uruguay
• Mexico and Uruguay: Action research with local partners
• Peru: documentation of existing case

3. Health Service delivery and accountability
Type of initiative Examples
Information dissemination Citizen Charters
Consultation/ Participation Health or users groups
Citizens scorecards
Third party monitoring
Citizen empowerment Health clinics management
committee

4. T/A Interventions and Impact
Expected Impact
Problems defining impact
Initiatives will expose corruption Transparency and Accountability might
not be linked (Fox 2007)
Initiatives will increase
government responsiveness
There is a set of assumptions about how
the exposure of information might
unchain responsiveness. This causal
inference is not often explicit
Exercise of rights by poor and
marginalised groups, building a new
citizenship
It is not very clear how these initiatives
end up in a different way of exercising
citizenship and how and if they include
poor voices. Often this new citizenship is
poorly defined

5. Go Digital!

6. Open Data as….
A project/problem solving/ strategic
approach
The use of open data to solve social
issues. It includes a set of methods or
activities such as data dives and
hackathons, with the aim to contribute
towards the solution of an issue. (Davies,
2016)

7. Peru: Citizen Control
Aim: Check on health service delivery in Peru and expose
potential corruption issues through the dissemination of public
information
Context: Lack of dialogue mechanisms and low levels of
transparency in the health sector
Open Data infrastructure: Low to non-existent. Data obtained
through several methods including scrapping
Results Raised awareness of the issue

8. Mexico: Engaging
Aim: Provide an online- offline venue to express citizens
grievances with Mexico’s health system
Context: Complex, non-transparent and potentially corrupt
areas of the health system
Open Data infrastructure: Existent but not structured in ways
it can be used. Several methods used to gather data including
FOI requests
Results: Raised awareness of the issue combined with strong
offline campaign which delivered changes in the provision of
health service delivery in Sonora

9. Uruguay: Coproduction
• Aim: Provide an online tool to inform users about their choices
at a critical opportunity
Context: Open Government process structuring dialogue for
joint initiatives. Complex health system
Open Data Infrastructure: Existent but poor. Willingness of
actors to produce and structure public data
Results: Significant use by health systems users, improvement
of the open data infrastructure (better data available as a result
of use) and improvement of public debate, as the app was
used by key public figures to debate health policies (Scrollini,
2016, Sangakoya et al, 2016)

10. Capacity and Willingness
Willingness/Capacity High Low
High Willing and capable government
Added value: New tools add
value to several policy realms.
Coproduction process likely
Willing government with low
capacity
Added value: Performative
effect of open data approach
shed lights on capacities to
develop and help to improve
public services. Co production
process possible
Low Not willing but capable
government
Added value: An open data
approach could help to
persuade government officials
about the value of releasing data
and creating meaningful uses for
government and citizen use. Co-
production process possible
Unwilling and with low capacity
Added value: An open data
approach can enhance
transparency and accountability
interventions. Co production
process unlikely

11. On Co-production:
4 key dimensions to consider:
• Enabling environment
• Shared policy objectives
• Partner’s Capacity
• Positive feedback loop

12. What can we learn?
ØControl, Engagement and Co-production are three different
types of working in an open data approach
ØWe should assess initiatives based on what they are seeking to
achieve, thus the hypothesis behind these initiatives should be
clearly established
ØCo-production is not a panacea. Hard work in terms of
transactions costs and not clear engagement processes. It does
have the potential to alter public sector behavior

13. What do we need?
• Limited PR: there is limited evidence about the impact of
this approach.
• We need to refine our hypotheses behind these initiatives
and evaluate accordingly. Beware of the “I” word.
• Standards are not a prerequisite to drive use. Use can
show the need for better data standards (if it make sense
to local users)
• Open it and they will build it not enough: a more
“Keynesian” approach is needed.

14. Thank you/Gracias
www.idatosabiertos.org
@fscrollini
@idatosabiertos