As countries continue to invest and make strides toward achieving the SDGs and universal health coverage, strong routine health information systems (RHIS) are fundamental to the effort. Well-functioning RHIS provide a wealth of data on a country’s health system, including service delivery, availability of a trained workforce, and reach of interventions, that can be harnessed to identify gaps and support evidence-based decision making. Yet, while many low-to-middle income (LMIC) countries have established a national RHIS structure, there are existing challenges related to the availability, analysis, and use of the data that have yet to be addressed.

1. Routine Health Information Network
AchievingUniversalHealthCoverage:
RoleofRoutineHealthInformationSystems
Theo Lippeveld, MD, MPH
Senior HIS Adviser
John Snow Inc
RHINO Forum January 15, 2019

2. Universal Health Coverage and the
Measurement Challenge
 Currently major investments in Low and Middle Income
Countries (LMIC) to achieve Universal Health Coverage
(UHC), as well as the Sustainable Development Goals
(SDG)
 UHC means “the delivery of high-quality essential
health services that are accessible to all without the
risk of financial hardship”
 Data are critical for monitoring progress, identifying
areas of improvement, and implementing practical
solutions (JLN and Bloom et all, 2018)
 Routine Health Information Systems (RHIS) can
provide many of the data required for measuring the
delivery and cost of high-quality health services
(Lippeveld, 2017)

3. The role and importance of decentralized
Routine Health Information System (RHIS)
 Facility-based and ideally also community-
based
 Main data source for (daily) planning and
management of quality health services at
district level and below
 Coverage and quality of health interventions
 Disease surveillance
 Commodity security
 Human resource management
 Financial information systems
 Ideal support to integrated management of
health interventions

4. Administrative
records systems
(NHA, FMIS, LMIS)
Services records
systems
(HMIS, IDSR)
Individual
Records systems
(paper-based – EMR)
Pop based
surveys
Vital
registration
Census
Population-based
data sources
Health Institution
(including community) based
data sources (RHIS)
Routine Health Information System (RHIS)

5. RHIS in most LMICs
are woefully
inadequate to
provide the needed
information support...
But We All Know

6. What is wrong with existing routine
health information systems?
 Irrelevance, plethora, and poor quality of
the data collected
 Fragmentation into “program- oriented”
information systems: duplication and
waste
 Poor and inadequately used HIS and ICT
infrastructure and resources
MOST OF ALL
 Absence of information culture where data
are valued and used for decision making

7. RHIS Reform and strengthening:
Achievements and Way Forward
 Advocacy: growing demand in the past decade for
strong RHIS in the global health community
 RHIS performance has improved in many countries
thanks to technical interventions such as
 Better measurement of RHIS performance: PRISM
tools
 Data quality assurance systems
 Better use of Information and Communication
Technology
 eHealth Architecture establishment
 Improved data visualization
 But use of information for DM lagging behind
Need for broader “system” thinking : PRISM framework
Need for behavioral interventions at individual and
organizational level including communities

8. Behavioral
Determinants
Knowledge/ skills, attitudes,
values, motivation
2008: PRISM Logical Framework for Understanding
Routine Health Information System (RHIS) Performance
Improved Health System
Performance
Improved Health
Outcomes
Technical
Determinants
Data generation architecture
Information/communication
technology
Desired Outputs
= RHIS performance
•good quality information
•appropriate use of information
Inputs
RHIS assessment,
RHIS strategies
RHIS interventions
Organizational
Determinants
Information culture, health system
structure, roles & responsibilities,
resources

9. This RHINO Forum:
Innovative approaches to better use of
RHIS data for improving service delivery
• Building an information culture
• Use of human-centered design (HCD) methodology to
help design an information system that accommodates
the needs of the users at all system levels
• Creating accountability in the community
• Providing innovative electronic tools for data
management and use at the community level

10. Need to Establish a “Culture of Information”
Operational definition
“The capacity and control to promote values
and beliefs among members of an organization
for collection, analysis and use of information
to accomplish its goals and mission.”

11. What drives Culture of Data Use? (JLN, 2018)
Enabling environment with a decentralized organizational
structure
Robust data feedback loops throughout the health system
Clear roles and responsibilities around decision making
No-blame environment with respect and promotion of
transparency
Mutual accountability and shared ownership within the
health system, and between the health system and the
community
Encouragement and incentives to motivate behavioral
change

12. Illustrative Interventions to Promote Data Culture
Role modeling by Senior Management for using collected
information
Dissemination of success stories on use of HIS
information
 Publication of district level indicators through media (Uganda)
 Allocation of resources based on HMIS indicators (Brazil)
Institutionalizing use of RHIS information
 Use of information as a criteria for annual performance appraisal
Health Services Performance Review meetings
 with focus on using RHIS data (problem solving methodology)
Creating data use incentives
 Performance based financing (PBF)
Human Centered Design (HCD) methodology

13. Human-centered Design (HCD)
methodology
 HIS design process that accommodates the needs of
the users at all health system levels by involving
users at the RHIS design stage
 HCD methods facilitate empathy among various
stakeholders, to help create an environment for
learning, idea generation, and developing effective
solutions (Gobee Group, 2017)
 Initially used by private sector, but recently also in
social projects (e.g. Data Use Partnership project in

14. Building Local Innovation
Capacity via HCD methodology
Establishment of Innovation Labs: groups of end-
users (policy level, district level, delivery of care level)
• Key to the creation of a culture of data use
• Meetings to solve problems using HCD
approach:

15. “Two years ago, we were the least
performing woreda in the zone. The training
we received on how to use our performance
data to make decisions and take action was
an eye opener. We knew very little about
using our own data to identify our own gaps
and propose solutions.
Now, we are completely data-driven. Soro
Woreda health office has witnessed a
growing interest in use of performance data
for DM, making it a cliché in the hearts and
minds of health workers and managers in the
woreda.
Abenezer Bekele, Head of Soro Woreda HO.
Case Study: Creating an information
culture in Soro woreda in
SNNPR/Ethiopia
(IHFP, Selected Stories from the Field, 2016)

16. Challenges and the way forward
 Creating an information culture is a behavioral
intervention: it will take time to see results!
 Measure information use for decision making based
on PRISM assessments (evidence-based)
 RHIS capacity building to improve data analysis,
problem solving and advocacy skills of district and
facility staff

17. Routine Health Information Network
THANK YOU
Theo Lippeveld, MD, MPH
Senior HIS Adviser
John Snow Inc.
tlippeveld@jsi.com

18. References
Bloom, D., Khoury A., and Subbaranam R.: The Promise and Peril of
Universal Health Care. Science, 361, 766, 2018
Bjorkman M, and Svensson, J.: Power to the people: evidence from a
randomized field experiment on community-based monitoring in Uganda.
Q.J. Economics, 2009.
Nutley T. and Reynolds H.: Improving the use of health data for health
system strengthening. Global Health Action, 2013
Lippeveld, T.: Routine Health Facility and Community Information Systems:
Creating and Information Use Culture. Editorial in GHSP, Vol 5 Nr 3, 2017
Measuring the Performance of Primary Health Care: A Toolkit for
Translating Data into Improvement. JL Network for UHC, 2018.
Ethiopia Data Use Partnership: Concept Note on Human Centered
Methodology (HCD)