calculating coverage indicators 2010 student

7/31/2019 Calculating Coverage Indicators 2010 Student

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MONITORING AND

EVALUATION: CALCULATING

AND INTERPRETING

COVERAGE INDICATORS

BY

DR JOHN P OYORE



Learning Objectives

By the end of the session, participants will be able to:

Identify sources of data for calculating coverage indicators

Estimate denominators for routine coverage estimates Calculate and interpret coverage indicators from

routine data

Use online resources for estimating coverage indicators

Assess the quality of relevant data sources

Reconcile coverage estimates from different

data sources



Maternal Health Coverage Indicators

Proportion of pregnant women who received at least

two antenatal care visits

Proportion of deliveries occurring in a health facility

Proportion of deliveries with skilled attendant

at birth

Proportion of women attended at least once during

postpartum period (42 days after delivery) by skilled

health personnel for reasons related to childbirth



Why Coverage Indicators

Are Important

Understand how effective program is

See if one target group is reached more

effectively than another Identify underserved area/regions



Child Health Coverage Indicators

Immunization ProgramsDTP3 vaccine coverage

Measles vaccine coverage

BCG vaccine coverageOPV3 coverage

HepB3 coverage

Fully immunized child

Nutrition programs? Control of diarrheal disease programs?



Coverage Indicators for HIV/AIDS Care& Treatment Programs

Number of clients receiving public/NGO

VCT services

Number of clients provided with ARVs Percent of children in need receiving

cotrimoxazole prophylaxis

Percent of HIV patients receiving DOTS Coverage of PMTCT programs?



Where Do We Get the Data? Censuses

Surveys

Registrations Health management information systems

Program statistics

Patient registers



ESTIMATING COVERAGE

FROM ROUTINE DATA



Indicators From Program

Statistics: Numerators

HMIS and routine reports give information on

numerators

Numerators: number of deliveries in healthfacilities, measles vaccinations, pills

distributed, voluntary counseling and testing

clients etc.

Denominators: ?



Example:

Importance of denominator

Town A vaccinated

200 infants

Town B vaccinated400 infants

Town C vaccinated

600 infants

Population size:

Town A= 10,000

Town B= 30,000

Town C= 60,000



Indicators From Program Statistics:What Denominators Are Needed?

Denominators: population composition

Population composition

How many women are of childbearing ages?

How many children are under five?

How many adolescents? 15-19? 20-24?

How many men are 15-59 years?

How many children are of school going age?How many infants are there?

How many babies are born each year?



How Do We Get Denominators?

Population registers

Censuses

Population projections

Population growth rate (r)

Rate of natural increase = crude birth rate (CBR)minus the crude death rate (CDR)

Net migration rate: inmigration - outmigrants per1000 population

CBR: no. of births per 1000 population in 1 year CDR: no. of deaths per 1000 population in 1 yr

Population growth = rate of natural increase + netmigration rate



Spectrum Model

DemProj: projects population of country/regionby age and sex based on assumptions about

fertility, mortality, and migration

Urban and rural population projections can also beprepared

EasyProj: supplies data needed to make a

population projection from estimates providedby the Population Division of the UN

www.tfgi.com



Spectrum



Calculating Denominators

Population at time t: P(t) = P(0) * exp(r*t),where:

P(t) is the population size after t years

P(0) is the population size at the last census

Example:

300,000 people at census

Growth rate = 3% (0.03),

What is the population after 10 years?

404,958 people



Estimating Number of Live Births

Where data on the number of live births areunavailable:

Total expected births = Total population x crude birth rate

Where the crude birth rate (CBR) is unknown:

Total expected births = Total population x 0.035



Estimating Number of Surviving

Infants

Target population for childhood immunization:

Surviving infants <12 months of age in a year

Where data on the number of surviving infants areunavailable:

Total expected number of surviving infants =

Total population x CBR x (1 –

infant mortality rate)



Estimating Number of

Surviving Infants: CBR Known

Total population: 5,500,000

CBR: 30/1000

Infant mortality rate (IMR): 80/1000 Number of surviving infants =

Total population x CBR x (1 – IMR)

= 5,500,000 x 30/1000 x (1 - 0.080)= 5,500,000 x 0.030 x 0.920

= 151,800



Estimating Number of Surviving

Infants: CBR Unknown

Where data on the number of surviving infants, CBRor IMR are unavailable, multiply total population by4%:

Expected no. of surviving children < 12 months =

Total population x .04

If the total population is 30,000, then the number of children under one year = 30,000 x 4/100 = 1200

Source: WHO, 2002



Estimating the Monthly Target

Population

Monitoring immunization and vitamin A coverage should

be done monthly at the facility and district levels,

requiring estimations of the monthly target population

Monthly target population = Estimated number of childrenunder 1 year of age divided by 12

Example: Annual target population of children < 12 months = 1200

Monthly target = 1200/12 = 100



Example: Immunization

Coverage From Routine Data Total population of district in 1990 = 99,000

CBR = 40 per thousand

IMR = 80 per thousand

Population growth (r) = 3% per year 3,000 measles vaccinations were given to infants in district

in 1998

What is the measles coverage rate for 1998?

Numerator: No. immunized by 12 months in a given yearDenominator: Total no. of surviving infants < 12 months

in same year



Immunization Coverage From

Routine Data: Answer

Estimate district total population in 1998

Pop1998 = 99,000 * exp(.03*8) = 125,410

Estimate number of surviving infants in 1998

125,410 x (40/1000) x (1 - .080) = 4615

Estimate measles coverage rate

Measles coverage = 3000/4615 x 100 = 65%



Case Study 1: Immunization Coverage

from Facility Data Estimate total population in 2003 Calculate coverage for DTP1, DPT3, and measles vaccine

in 2003

Evaluate trends in coverage

Estimate drop-out rates Analyze the problems in 2003

Is coverage low or falling?

What are possible causes?

What are the differences in coverage in different areas? What action can managers take if coverage

data indicate problems?



Challenges in Estimating

Coverage from Routine Data

Limited knowledge of target pop/denominators

Low timeliness & completeness of reporting

Poor data quality

Lack of written standard reporting procedures

No systematic supervision on data management

Dual reporting systems (EPI, HMIS)

Inclusion of data from private sector



Assessing Reliability of Routine

Coverage Indicators

Understand how denominators are derived

Understand the process of collecting the

information Look for inconsistencies and surprises



Assessing Reliability of Routine

Coverage Indicators

Look for reliable data from other sources to

use as a basis for comparison

Cross-check



ESTIMATING COVERAGE

FROM SURVEY DATA



Survey Tools for Coverage

Estimation

WHO-EPI surveys

Lot quality coverage surveys

Large-scale population-based surveys

USAID Demographic and Health SurveysUNICEF Multiple Indicator Cluster Survey

Arab League PAPCHILD surveys

CDC Reproductive Health Surveys

Seventy-five household survey

Knowledge-Practice-Coverage Surveys

Other local surveys



How Do Administrative Data

Compare With Survey Data?

010

20

30

40

50

60

70

80

90

100

P e r c e n t i m m u

n i z e d

Nairobi Central Coast Eastern N/ Eastern Nyanza Rift Valley Western

Survey (2002) Routine Cumm Sep 2002



Reconciling Coverage Estimates

From Different Data Sources

Age group & geographic scope

Health cards versus recall

Different sources for different purposes Not all coverage data can be compared in

constructive way

Differences in inclusion of private sector Selectivity



On-line Resource: STATcompiler

Innovative online database tool Allows users to select numerous countries and

hundreds of indicators to create customized tables

that serve specific needs

Accesses nearly all population and health indicators

published in DHS final reports

http://www.measuredhs.com/statcompiler





STATcompiler



On-line Resource: DOLPHN

DOLPHN: Data Online for Population, Healthand Nutrition

Online statistical data resource

Quick access to frequently used indicators frommultiple sources, including:

DHS, BUCEN, CDC, UNAIDS, UNESCO,

UNICEF, World Bank, WHO

www.phnip.com/dolphn

http://www.phnip.com/dolphn

http://www.phnip.com/dolphn



Advantages and Disadvantages

of Routine-based Coverage

Advantages

Provides information on more timely basis

Makes use of data routinely collected Can be used to detect and correct problems in

service delivery

Disadvantages

Denominator errors

Poor quality reporting



Advantages and Disadvantages

of Survey-based Coverage

Advantages

Avoids problems with denominators

Includes information from non-reporting facilities

Disadvantages

Coverage survey has low precision

Larger standard errors at sub-national levels

Irregular and expensive

Survey timing may affect coverage rates



Case Study 2: Estimating

Vitamin A Coverage

Calculate coverage from routine data

Use tally sheets to determine number of children

who received vitamin A compared to target

population

Compare coverage estimates from routine data

with estimates from survey data

Estimate missed opportunities



References

WHO. 1999a. Indicators to Monitor Maternal Health Goals: Report of a Technical WorkingGroup, Geneva, 8-12 November 1993. Divisionof Family Health Geneva: WHO.

WHO. 1999b. Reduction of Maternal Mortality: A Joint WHO, UNFPA, UNICEF,World Bank Statement . Geneva: WHO.

WHO (2002) Increasing Immunization at the Health Facility Level. Geneva, Switzerland:World Health Organization

calculating coverage indicators 2010 student

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