1

Data analysis

2

Turning data into information

How do we process it?

How do we present it?

How do we use it? Reliable Information

Information CycleWhat do we collect?

Stages Tools Outputs

data sources & tools

Timely Quality data

Data quality checks, Data

analysisInformation

4

Data analysiswhat, why and how?

turns raw data into useful information

is the process of producing indicators – most important step in data analysis

requires timely quality data – remember the 3 C’s

5

Data analysiswhat, why and how?

the improvement of coverage and quality of local health services - is facilitated by only collecting data that can be analyzed and used at the local level

allows comparisons

self assessment (have I reached my target ?)

supports decision-making

6

Data analysiswhat, why and how?

calculate indicators

use basic epidemiological concepts

7

Indicators measures of COVERAGE and QUALITY

variables used to measure CHANGE

monitor progress towards defined targets

describe situations

measure trends over time (temporal)

provide a yardstick whereby facilities / teams can compare themselves to others (spatial, organizational)

8

Indicator calculation types

– Example: Maternal mortality rate – How is it defined?

Millenium development goals have a set of proposed indicators

denominatorindicator =

numeratorX 100 = %

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Atop the line – numerators(activities / interventions / events / observations / people)

a count of the event being measured

How many occurrences are there:

morbidity (health problem, disease)

mortality (death)

resources (manpower, funds, materials)

Generally raw data (numbers)

11

Under the line - denominators(population at risk)(population at risk)

size of target population at risk of the event

What group do they belong to:

general population (total, catchment, target)

gender population (male / female)

age group population (<1, >18, 15-44)

cases / events – per (live births, TB case)

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An ideal An ideal indicator indicator RAVES !!!RAVES !!!

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Indicators RAVES

RELIABLE gives the same result if used by different people

APPROPRIATE fits with context, capacity, culture and the required decisions

VALID truly measures what you want to measure

EASY feasible to collect the data

SENSITIVE immediately reflects changes in events being measured

Essential indicators: determines the essential data set at each level

Indicator OperationalizationDefining the sources of the data – both numerator & denominator (how is it to be collected?)

Determining the frequency of collection and processing of the indicator (How often should it be collected, reported, analyzed?)

Determining appropriate levels of aggregation(To where should it be reported and analyzed/broken down?)

Setting levels of thresholds and target

What will be the nature of the action (decision) once the indicator reaches the threshold?

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Epidemiological questions

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Epidemiology: who, where, when?

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Epidemiology:what, why and how?

WHAT ?

study of the distribution, frequency and determinants of health problems and disease in human populations

WHY ?

obtain, interpret and use health information to promote health and reduce disease

HOW ?

uses indicators to answer basic epidemiological questions

How do we process it?

How do we present it?

How do we use it? Reliable Information

Information CycleWhat do we collect?

Stages Tools Outputs

data sources & tools

Timely Quality data

Data quality checks, Data

analysisInformation

Having a plan

Operationalization of organizational goals

Settings targets

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Targets

state exactly what has to be achieved, by whom and by when

a realistic point at which to aim to reach a goal

turning the organizational goal into numbers

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Targets should be SMART

SPECIFIC measurable based on changes in situation concerned

MEASURABLE able to be easily quantified

APPROPRIATE fit in to local needs, capacities and culture

REALISTIC can be reached with available resources

TIME BOUND to be achieved by a certain time

Example Targets

CHIEFDOM LEAGUE TABLE 2ND QUARTER APRIL – JUNE 2009

20.893.632.4114.34391.4Total

14143.228.3100.038.273.82954.9Bumpeh

12123.738.677.8101.268.02961.1Upper Banta

12123.760.5100.057.453.72671.8Ribbi

884.364.086.689.492.64049.8Kori

884.336.5100.077.693.24580.4Kargboro

884.386.5100.0140.769.73555.6Kamaje

884.332.193.092.4110.33761.4Bagruwa

664.735.6100.0120.8201.64888.3Lower Banta

664.778.2100.046.796.552118.4Kowa

334.833.091.791.7106.846140.3Timidale

334.871.375.093.4162.75590.3Kaiyamba

334.845.9100.086.390.557134.9Dasse

225.048.1100.086.2154.362124.3Fakunya

115.393.386.696.6170.94598.2Kongbora

RankingRankingAverage Score

% Exclusive Breastfeeding

at Penta3

% MMRC Submitted

% 2nd Dose of IPT

% 3rd ANC Visit

% PHU Delivery2nd

Quarter

% FullImmunized 2nd Quarter

Chiefdoms

Chiefdom/ Facility league table

Immunization

DeliveriesAntenatal

MalariaData Quality

Nutrition