District administrators can use data to diagnose problems and improve socioeconomic wellbeing. IDinsight collects high-frequency district data through its Data on Demand platform to help measure performance and identify areas for improvement. The document discusses using administrative data, surveys, and comparisons over time to validate data and understand issues. It also provides an example of using different data sources to analyze low rates of antenatal care visits and determine potential causes and solutions.

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STRATEGIC PLANNING FOR HEALTH AND NUTRITION
USING DATA FOR INFORMED ACTION
Stepping up to India’s Nutrition Challenge: The Critical Role of District
Administrators • February 14th, 2019

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High-frequency tracking of key
socioeconomic indicators at the
district level
Learnings to help improve
socioeconomic wellbeing using
responsive research services
Measurement:
Track district performance
Learning:
Support performance
improvements
IDinsight Objectives IDinsight approach
Data on Demand
High frequency data collection
infrastructure to support
measurement and learning
IDinsight works with NITI Aayog on the Aspirational
Districts program with a three-pronged approach

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Key messages from this session
Data can help diagnose the problem in the chain from inputs to
outcomes and impact
Comparisons, checks and time trends can help you validate the data
that you see
MIS is the main source of data at the district. National and third-party
surveys can sometimes complement this data

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Diagnosing the problem - example
The World Health Organization recommends all pregnant women have at
least 4 antenatal care checkups. However, in District A the percentage of
pregnant women who had at least 4 antenatal visits is only 16% (HMIS). What
is going on?

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What are potential reasons for this problem?
Lack of awareness of importance of 4 antenatal check-ups
Lack of ability (time, support, money) for pregnant women to get check-ups
Lack of functional health centres
What are the main problems?
Other?

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Some relevant data for the problem
Categories Indicators Data Source Value for District A
Inputs
Percentage of sub-centres out of total needed
Percentage of ANMs out of total needed
Interventions
Percentage of pregnant women registered for antenatal care
Percentage of pregnant women registered for antenatal care
within first trimester
Percentage of pregnant women who had at least 4 antenatal
visits by delivery
Outcomes
Percentage of mothers who consumed iron folic acid for 100
days or more when pregnant
Percentage of institutional deliveries to total reported
deliveries
ANCs can also improve calcium and deworming consumption, protection against neonatal tetanus, anemia testing, dietary
diversity, increase child birth weight, and decrease the Maternal Mortality Rate
Where do we get this
data from?

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How would you normally get
information on nutrition
activities and outcomes in your
district?
Discussion Question (data sources)

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Admin Data (MIS)
● National scale
● Self-reported through
program staff
● Available at fairly high
frequencies
● E.g. HMIS, ICDS-CAS
Third Party Surveys
● Scale depends on demand
● Collected by surveyors from
a sample of the population
● Frequency depends on scale
and operational efficiency of
surveys
● Eg: TSU CBTS, Aspirational
Districts Survey
National Surveys
Let us look at three district data sources
● National scale
● Collected by surveyors from
a sample of the population
● Frequency typically every few
years
● Eg: NFHS, NSS, Multiple
Indicator Cluster Surveys

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Admin Data (MIS)
● National scale
● Self-reported through
program staff
● Available at fairly high
frequencies
● E.g. HMIS, ICDS-CAS
Third Party Surveys
● Scale depends on demand
● Collected by surveyors from
a sample of the population
● Frequency depends on scale
and operational efficiency of
surveys
● Eg: TSU CBTS, Aspirational
Districts Survey
National Surveys
Let us look at three district data sources
● National scale
● Collected by surveyors from
a sample of the population
● Frequency typically every few
years
● Eg: NFHS, NSS, Multiple
Indicator Cluster Surveys
We will focus mostly
on admin data

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Some features of administrative (MIS) data
Who collects the data?
Who is represented in
the data?
People who access government
services
Data is mostly reported by front
line workers
What indicators do we
normally see?
Data on inputs and interventions
What indicators are
commonly not seen?
Data on knowledge, attitudes,
practices
ANMs and ASHAs
Pregnant women on ANMs and
ASHAs lists
ANC registration, 4+ ANC, IFA
tablet distribution
Knowledge of ANC, consumption
of IFA
Example: Antenatal check-upsFeatures

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How do we explain differences between MIS and
survey data?
Different coverage
Different
reference periods
Sample surveys cover entire population, MIS data limited to those who access
government services
Survey questions may ask about different reference periods than MIS data
Outdated
denominators
Denominators in MIS data may need updating, e.g. estimates of pregnant women in
the district
Inaccurate reporting
Key Takeaway: MIS data is very useful, but be aware of its limitations!
Self-reported MIS data may be inflated to display desirable results

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Checks
Facility inventory, spotchecks, personal
interviews, backchecks, phone audits
So how do we know if the MIS data is accurate?
Comparisons
Different data sources, neighbouring districts,
investigate extreme values
Time trends
Does the rate of change seem sensible?

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Data on the percentage of pregnant women completing 4+ ANC check-ups varies by
source. For District A, HMIS data indicates 16%, ICDS-CAS indicates 20% and NFHS-4
indicates 7%. Why do you think this difference exists?
Discussion Question (Data Validation)

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Supportive culture around accurate reporting
can lead to better program performance
How would you encourage more truthful reporting by district and block officials during
the district review meetings?

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Admin Data (MIS)
● National scale
● Self-reported through
program staff
● Available at fairly high
frequencies
● E.g. HMIS, ICDS-CAS
Third Party SurveysNational Surveys
Let us briefly talk about the other two sources of
data at the district
● National scale
● Collected by surveyors from
a sample of the population
● Frequency typically every few
years
● Eg: NFHS, NSS, Multiple
Indicator Cluster Surveys
● Scale depends on demand
● Collected by surveyors from
a sample of the population
● Frequency depends on scale
and operational efficiency of
surveys
● Eg: TSU CBTS, Aspirational
Districts Survey

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If you would like to conduct a survey in your
district, these resources can be helpful
Local universities
Third party survey organizations

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Diagnosing the problem - example
The World Health Organization recommends all pregnant women have at
least 4 antenatal care checkups. However, in District A the percentage of
pregnant women who had at least 4 antenatal visits is only 16% (HMIS). What
is going on?

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Categories Indicators Data Source Value for District A
Inputs
Percentage of sub-centres out of total needed
Percentage of ANMs out of total needed
Interventions
Percentage of pregnant women registered for antenatal care
Percentage of pregnant women registered for antenatal care
within first trimester
Percentage of pregnant women who had at least 4 antenatal
visits by delivery
Outcomes
Percentage of mothers who consumed iron folic acid for 100
days or more when pregnant
Percentage of institutional deliveries to total reported
deliveries
Relevant data for the problem
Now we know the
sources and how to
validate them. What
next?

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Categories Indicators Data Source Value for District A
Inputs
Percentage of sub-centres out of total needed HMIS 88%
Percentage of ANMs out of total needed HMIS 90%
Interventions
Percentage of pregnant women registered for antenatal care HMIS 75%
Percentage of pregnant women registered for antenatal care
within first trimester
HMIS 50%
Percentage of pregnant women who had at least 4 antenatal
visits by delivery
HMIS 16%
Outcomes
Percentage of mothers who consumed iron folic acid for 100
days or more when pregnant
NFHS 5%
Percentage of institutional deliveries to total reported
deliveries
HMIS 78%
Relevant data for the problem

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Women are registering but not within the first
trimester
Messaging campaigns with key information about
registration within first trimester
Partner with a trusted community member to
introduce ASHAs and their role
Beneficiaries are unaware of the benefits of
registration within first trimester, or how many
ANCs they are supposed to do
Beneficiaries know what they are "supposed to
do," but they do not trust ASHAs
Problem
Beneficiaries do not think sub-centres will be
open regularly
Possible next step
Community meeting where the problem is
discussed and accountability is assured

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Key messages
Data can help diagnose the problem in the chain from inputs to
outcomes and impact
Comparisons, checks and time trends can help you validate the data
that you see
MIS is the main source of data at the district. National and third-party
surveys can sometimes complement this data

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Group Activity
Let’s divide ourselves into groups first

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3
Scenario Table 1
You will receive three documents
Instructions
1 2
A chart paper will also be provided later to help you create a presentation

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Steps
1
(10 minutes) Read through the scenarios individually. Your scenario may be about either
IFA tablet consumption, Exclusive breastfeeding, or Growth monitoring
2
(15 minutes) Please discuss the given questions in your group to identify the source of the
problem. The data presented in Table 1 may be useful. Is there any additional data that
would be helpful to know?
3
(15 minutes) What actions can you take to alleviate the problem? Are there some actions
that are not in your control, but would be helpful?
4
(20 minutes) Use the chart paper to create a 3-minute presentation on the following:
a) Causes of the problem
b) Actions that can be taken
Please remember to choose a presenter for your group

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Please start reading through the scenario

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Group presentations

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Questions?

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Key messages
Data can help diagnose the problem in the chain from inputs to
outcomes and impact
Comparisons, checks and time trends can help you validate the data
that you see
MIS is the main source of data at the district. National and third-party
surveys can sometimes complement this data

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APPENDIX

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IDinsight is
growing rapidly
with eight global
offices and a team
of 200

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WE HAVE WORKED ALL OVER INDIA ACROSS DIVERSE SECTORS
We have worked in 13 countries globally, and 14 Indian states including Delhi
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