1 Data analysis. 2 Turning data into information.
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Transcript of 1 Data analysis. 2 Turning data into information.
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Data analysis
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Turning data into information
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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
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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
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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
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Data analysiswhat, why and how?
calculate indicators
use basic epidemiological concepts
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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)
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Indicator calculation types
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– 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)
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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
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Essential indicators: determines the essential data set at each level
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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
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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
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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
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Example Targets
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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