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The Category Model

Design for Data Use Level 1

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Session Objectives

  • Define the DHIS2 category model
  • Use categories to disaggregate data in analysis apps
  • Create category options, categories and category combinations following a standard operating procedure
  • Describe the relationship between categories, data dimensions and analytics
  • Apply category combinations to data elements

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Reviewing the Malaria burden reduction dataset

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Reviewing the termly tool

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Key terms

Category options

Categories

Category Combinations

Category options combination

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Category options

Category options

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Example of category options

Dissagregate

  • 0-4years
  • 5-14years
  • 15+ years

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  • Male
  • Female

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Category options

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Principles for category option creation

2 principles

1. Reusability

  • Male
  • Female
  • Femme

​

same cat option

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Principles for category option creation

2 principles

2. Granularity

  • Male
  • 10 -14 years
  • Male, 10 – 14 years

​

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Categories

Categories

  • 10 – 14 years
  • 15 – 19 years
  • 20+ years

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  • Male
  • Female

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Categories

Categories

  • 0 - 4 years
  • 5 – 14 years
  • 15 + years

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  • Male
  • Female

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Malaria Age

Sex

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Principles for category creation

Meaningfulness

= added values for all category options should be meaningful

Aggregated data for < 1 years would be double counted

Data

Malaria Tested Microscopy

Period/Age

< 1 years

< 5 years

2021

4 996

24 567

2022

3 987

22 893

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Categories

Category combinations

Cat 2: Malaria Age

Cat 1: Sex

  • Allows to add one or more categories to data elements

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Category combinations – one dimension

Category combination

Category

Category options

  • 0-4 years
  • 5-14 years
  • 15+ years
  • Age (Malaria)
  • Age (Malaria)

(Only one category)

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Category combinations – two dimensions

Category combination

Category

Category options

  • 0-4 years
  • 5-14 years
  • 15+ years
  • Male
  • Female
  • Age (Malaria)
  • Sex
  • Age (Malaria) and Sex

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Category option combinations

Category combination

  • Age (Malaria) and Sex
  • Male, 0-4 years 
  • Female, 0-4 years
  • Male, 5-14 years
  • Female, 5-14 years
  • Male, 15+ years
  • Female, 15+ years

Category option combinations

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Category model: Advantages

Flexibility in viewing the data outputs

​

Less data elements to create; reduces time for customization

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Reducing opportunities for errors or duplication

​

​

1

2

3

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Summary - Concepts

The category model

Category options

Categories

Category combinations

Category option combinations

Reusability

Granularity

Meaningful Totals

Disaggregation of data elements

Individual component parts

Group of category options

One or more categories

Automatic combination of category options in each cell

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Summary – Model – Data Element with Two Dimensions

Malaria tested microscopy

Malaria Age+Sex

Malaria Age

Male

0-4 years

Data Element

Category Combination

Category

Category Option

Category Option Combination

Sex

0-4 years, Male

Data Value

categoryoptioncomboid

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Summary – Model – Data Element with one Dimension

Classrooms

Number of Rooms

Number of Rooms

Permanent

Data Element

Category Combination

Category

Category Option

Category Option Combination

Permanent

Data Value

categoryoptioncomboid

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Summary – Model – Data Element with no Dimension

Career talks held

default

default

default

Data Element

Category Combination

Category

Category Option

Category Option Combination

default

Data Value

categoryoptioncomboid

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