Routine health data module-5-session-2.pptx

1
MODULE 5:
RHIS Data Analysis
SESSION 2:
Overview of Steps 1-4 of Data Analysis
ROUTINE HEALTH INFORMATION SYSTEMS
A Curriculum on Basic Concepts and Practice
The complete RHIS curriculum is available here:
https://www.measureevaluation.org/our-work/ routine-health-information-systems/rhis-curriculum

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Learning Objectives and Topics Covered
Objectives
By the end of this session, participants will be able to:
• Select appropriate indicators for data analysis
• Conduct a basic desk review of data quality and adjust data if necessary
• Select appropriate denominators
• Compare findings from routine data with findings from other data sources
• Analyze routine data to produce information products (tables, graphs,
and maps)
Topics Covered
• Selection of indicators for analysis
• Desk review of data completeness and internal consistency
• Selection of appropriate denominators
• Comparison of findings from routine data with findings from other data
sources

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5 Steps of Data Analysis
1. Select a limited set of core indicators
2. Review data quality
3. Select appropriate denominators
4. Reconcile findings with estimates from
other data sources
5. Communicate key findings (to be
discussed in Module 5, Session 3)

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S1: First Step
Select a Limited Set of Core Indicators

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What Makes an Indicator “SMART”?
(Characteristics of Good Indicators)
• Specific: Indicator is concrete, detailed, focused, and
well-defined
• Measurable: Indicator tells how many or how much and
can be measured with identified measurement sources
• Agreed upon: Stakeholders vested in a specific M&E
question should agree that indicator is relevant
• Relevant: Indicator generates data that can answer
the question of interest
• Time-bound: Indicator specifies time frame of what it is
measuring

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S1: Select a Limited Set of Core Indicators
Core indicators should:
• Be based on M&E framework for the national
health sector strategy
• Be programmatically relevant, and facilitate
program management
• Reliably and comprehensively assess the
performance of the health system (whether
national or subnational levels)
• Be clearly defined
• Have numerators that are measurable with
routine health data

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S1: Core Indicator with 2 Data Sources: DTP3
Routine health
information systems
Numerator: Number of infants
immunized with DTP3 by 12 months
of age in a given year
Denominator: Total number of
surviving infants <12 months of age
in same year
Population-based
survey
Numerator: Number of children
ages 12–23 months who received
three doses of DTP3 vaccine by age
12 months
Denominator: Total number of
children ages 12–23 months
surveyed

8
S1: Core Indicators Measured Reliably with One
Data Source
Antiretroviral therapy
(ART) retention rate
Source: Routine health
information systems
Numerator: Number of adults and
children with HIV, alive and on
antiretroviral therapy (ART) 12, 24, 36
months (etc.) after initiating treatment
Denominator: Total number of patients
initiating ART during a specific period
Fully-immunized child
Source: Population-
based survey
Numerator: Number of children ages
12–23 months who received 3 doses of
OPV, 3 doses of DTP, and 1 dose each
of BCG and measles vaccine before
age 12 months
Denominator: Total number of children
ages 12–23 months surveyed

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Some Indicators Are Not Clearly Defined or
Cannot Be Reliably Measured with Routine Data
Some indicators are not clearly defined:
• Percentage of health facilities with a skilled provider
• Percentage of health facilities with an adequate supply of
drugs
Some health indicators can be reliably measured with a
household survey or health-facility survey but not with data
reported routinely by health facilities:
• Proportion of population using an improved drinking water
source
• Proportion of health facilities with treatment guidelines
• Infant mortality rate
Some indicators are not clearly defined and usually cannot be
reliably measured with data reported routinely by health facilities:
• % of health facilities with health equipment

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Practicing the First Step
Exercise: Part 1
• Review the list of core health indicators (on the
next slide (Handout 5.2.1)
• Identify which indicators can/cannot be reliably
measured with routine data
o Can the numerator be defined with routine
data?
o Do you need additional data sources to
measure the indicator?

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List of Health Indicators
1. Percentage of pregnant women
attending antenatal clinics who
are screened for syphilis
2. Neonatal mortality rate
3. Number of neonatal tetanus cases
4. Cost of one month’s supply of
contraception as a percentage of
monthly wages
5. Percentage of infants born
protected against neonatal
tetanus in a specified period
6. Measles vaccine coverage rate
7. Percentage of registered new and
relapse tuberculosis (TB) patients
with documented HIV status
8. Percentage of children ages 12–59
months who were dewormed in
the past six months
9. Percentage of HIV-positive infants
born to HIV-positive women
10. Maternal mortality ratio
11. Number of health facilities
providing comprehensive
emergency obstetric care
functions per 500,000 population
12. Exclusive breastfeeding rate
13. TB treatment success rate
14. Percentage of health facilities with
systems that support quality service
delivery
15. Percentage of districts with current
trend analysis for selected priority
diseases at a given time (e.g.,
month)

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S1: Practicing the First Step
• Exercise, Part 2
• Review the WHO’s Global Reference List of Core
Health Indicators (Handout 5.2.3) or the list of
standard indicators in Handout 5.2.2.
• Select five indicators from the list.
• For each indicator:
o Specify the numerator
o Specify the denominator
o What is the data source for the numerator?
o What is the data source for the denominator?
o How can the indicator be interpreted?

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S2: Second Step
Review Data Quality

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• Completeness and timeliness
o Completeness of reports
o Completeness of data
o Timeliness of reports
• Internal consistency
o Accuracy
o Outliers
o Trends
o Consistency among indicators
• External consistency
o Data triangulation
o Comparison with data surveys
o Consistency of population trends
• External comparisons (population denominators)
Step 2: Review Data Quality (see also Module 4)

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S2: Demonstration, Excel
How to use Excel to:
• Create a chart
Participants are invited to practice simultaneously.
Here are two websites with 5-minute videos explaining how
to create a chart using Excel:
https://www.youtube.com/watch?v=BcsDnRClzCY
http
://excelcentral.com/excel2007/essential/lessons/05010-cre
ate-a-simple-chart-with-two-clicks.html

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S2: Demonstration DHIS 2
How to use DHIS 2 to:
• Verify the definition of an indicator
o Numerator and denominator
• Create a pivot table
• Create a chart
Participants are invited to practice simultaneously.

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S3: Third Step
Select Appropriate Denominators

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S3: How Do We Get Coverage Denominators?
• First, estimate the size of the target population.
• Common target populations for health-facility-based indicators:
o Total population, children< 5 years, infants, pregnancies,
women of reproductive age, live births at health facilities
• Size of target populations is often estimated (such as
projections/modeled estimates from national population census).
• Limitations of estimates:
o Reliability declines with years since last census
o Internal migration may make estimates of populations of
regions and districts unreliable
• Some programs may use their own denominators.

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How Do We Get Denominators?
• Document how the denominator value was obtained:
o Methods and assumptions used to calculate the
denominator
o Annual rate of growth if denominators are based on
projections of census figures
o Present these along with rest of analysis
• If service coverage >= 95% and data are of high quality, use
ANC1 or DTP1 to estimate the number of surviving infants.
o Use of service statistics to estimate size of target population
can modify conclusions reached about which districts are
strong performers and which are weak performers.

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Estimating Denominators
Estimating the number of surviving infants:
Total population: 5,500,000
Crude birth rate (CBR): 30/1,000
Infant mortality rate (IMR): 80/1,000
Number of surviving infants
Total population x crude birth rate x (1 - IMR)
= 5,500,000 x 30/1000 x (1 - 0.080)
= 5,500,000 x 0.030 x 0.920
= 151,800

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Data Quality Check for Denominators
• Pregnancies = births + pregnancy loss (2% to 10%);
• Surviving infants = births – infant mortality
Pregnancies,
early
Pregnancies,
late
Deliveries Live births Infants
0
2000
4000
6000
8000
10000
12000
14000
12415
11512 11286 11400 11058
Number of pregnancies, deliveries, live births, infants
Tanzania district example, 2014

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S4: Fourth Step
Reconcile Findings with Estimates from Other Data Sources

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S4: Reconcile Findings with Estimates from Other
Data Sources
• Compare data from parallel systems that
routinely report the same health events.
• Compare estimates from routine health-facility
data with estimates from household surveys at
the national and regional levels.
• Compare available data with statistics that
have been officially reported to WHO.

S4: Estimates from Two Sources of Routine Health
Facility Data
40% 60% 80% 100% 120% 140%
40%
60%
80%
100%
120%
140%
DTP3 - EPI (JRF)
DTP3
--
HMIS
(DHIS)
Administrative estimates of 2014 DTP3 coverage, by district,
DPI/JRF versus HMIS/DHIS data
Note: Red marks are for districts with a negative dropout rate, according to EPI/JRF data.
.

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S4: Compare Estimates from Household Surveys
DTP3 immunization coverage, Tanzania, 2009–2012
Sources: Routine EPI facility data, 2010 DHS, and 2011 Immunization Coverage Survey

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Reconciling with Survey Findings Is Not Always Easy
2014 WHO-UNICEF report on trends in DTP3 coverage in Ethiopia
Administrative/official estimates (red stars and circles) versus surveys
(vertical red lines) versus WHO-UNICEF estimate (blue line)

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Reconciling with Survey Findings Is Not Always Easy
2014 WHO-UNICEF report on trends in DTP3 coverage in India
Administrative/official estimates (red stars and circles) versus surveys
(vertical red lines) versus WHO-UNICEF estimate (blue line)

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Small Group Exercise (Steps 1-4 )
• Distribute Handouts 5.2.4a and b.
• Form small groups of 4–5 participants.
• Using Excel and the spreadsheet provided (Penta, 2014 data from
Tanzania, Handout 5.2.4B), calculate indicator values by region for:
o Penta1 coverage rate
o Penta3 coverage rate
o Penta1-Penta3 dropout rate
• For each region, specify whether access is good or poor.
• For each region, specify whether utilization is good or poor.
• Categorize the immunization problem in each region (if any).
• Brainstorm the differences in coverage between regions.
• Discuss what action managers can take if coverage and dropout
rates indicate problems.

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P2: Small Group Exercise, Option B (DHIS 2)
• Distribute Handout 5.2.6.
• Form small groups of 4–5 participants.
• Choose either ANC4 or DTP3 as your indicator.
• Using DHIS 2, verify the definition of the indicator.
• Create a pivot table with indicator values by district.
• Graph trends in the completeness of reporting by year
for the past four years by:
o Facility (hospital versus health center) and
o Managing authority (public versus private)
• Discuss how the trend in completeness would affect the
apparent trend in the indicator.

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ROUTINE HEALTH INFORMATION SYSTEMS
A Curriculum on Basic Concepts and Practice
This presentation was produced with the support of the United States Agency for
International Development (USAID) under the terms of MEASURE Evaluation
cooperative agreement AID-OAA-L-14-00004. MEASURE Evaluation is implemented by
the Carolina Population Center, University of North Carolina at Chapel Hill in
partnership with ICF International; John Snow, Inc.; Management Sciences for Health;
Palladium; and Tulane University. The views expressed in this presentation do not
necessarily reflect the views of USAID or the United States government.

Routine health data module-5-session-2.pptx

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