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R Interface for Retrieving Data from KHIS
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The khisr package is designed to seamlessly integrate with DHIS2,providing R users with a powerful interface for efficient dataretrieval. DHIS2 is a cornerstone in health information management formany organisations, and khisr simplifies the process of accessing andworking with DHIS2 data directly within the R environment.
- Data Retrieval: Easily download and manage data from DHIS2.
- Flexible Queries: Customize data queries to retrieve specificdata elements, periods, and organizational units.
- Secure Access: Manage credentials securely within your Renvironment.
- Health data analysis for research.
- Monitoring and evaluation of health programs
- Generating reports and dashboards for health information systems.
You can install the release version of khisr fromCRAN with:
install.packages("khisr")And the development version of khisr like so:
#install.packages('pak')pak::pak('damurka/khisr')
library("khisr")The khisr package operates in authenticated mode by default. This meansyou’ll need to provide credentials before using any functions thatinteract with your DHIS2 instance to download data. To ensure secureaccess, khisr offers a convenient way to store your credentials withinyour R environment. Refer to the following resource for detailedinstructions on setting your credentials:set youcredentials
# Option 1: Set credentials directly in R (less secure)khis_cred(username='DHIS2 username',password='DHIS2 password',server='https://<dhis2 server instance>')# Option 2: Set credentials from a secure configuration file (recommended)khis_cred(config_path='path/to/secret.json')
Once you’ve established your credentials, you’re ready to leveragekhisr’s functions to download data from your DHIS2 instance.
For this overview, we’ve logged into DHIS2 as a specific user in ahidden chunk.
This is a basic example which shows you how to solve a common problem:
# Retrieve the organisation units by county (level 2)counties<- get_organisation_units(level %.eq%'2')counties#> # A tibble: 47 × 2#> name id#> <chr> <chr>#> 1 Baringo County vvOK1BxTbet#> 2 Bomet County HMNARUV2CW4#> 3 Bungoma County KGHhQ5GLd4k#> 4 Busia County Tvf1zgVZ0K4#> 5 Elgeyo Marakwet County MqnLxQBigG0#> 6 Embu County PFu8alU2KWG#> 7 Garissa County uyOrcHZBpW0#> 8 Homa Bay County nK0A12Q7MvS#> 9 Isiolo County bzOfj0iwfDH#> 10 Kajiado County Hsk1YV8kHkT#> # ℹ 37 more rows# Retrieve organisation units by name (level included to ensure it refers to county)kiambu_county<- get_organisation_units(level %.eq%'2',name %.like%'Kiambu')kiambu_county#> # A tibble: 1 × 2#> name id#> <chr> <chr>#> 1 Kiambu County qKzosKQPl6G# Retrieve all data elements by data element group for outpatient (data element group name MOH 705)moh_705<- get_data_elements(dataElementGroups.name %.like%'moh 705')moh_705#> # A tibble: 96 × 2#> name id#> <chr> <chr>#> 1 Abortion IrWSgk9GsUm#> 2 All other diseases KxT47tbKHsd#> 3 Anaemia cases kkUHOwGMawD#> 4 Arthritis, Joint pains etc. waNhWrS3HL6#> 5 Asthma L82lvvxVaqt#> 6 Autism L529r3Wvtcf#> 7 Bilharzia (Schistosomiasis) ojFSHMwbkHK#> 8 Brucellosis nb9cfWgxYFc#> 9 Burns dkEYL9Sous9#> 10 Cardiovascular conditions sZETzNe1To8#> # ℹ 86 more rows# Filter the data element to element that contain malariamalaria<- get_data_elements(dataElementGroups.name %.like%'moh 705',name %.like%'malaria')malaria#> # A tibble: 4 × 2#> name id#> <chr> <chr>#> 1 Confirmed Malaria (only Positive cases) OoakJhWiyZp#> 2 Malaria in pregnancy gvZmXInRLuD#> 3 MOH 705A Rev 2020_ Tested for Malaria siOyOiOJpI8#> 4 Suspected Malaria Lt0FqtnHraW# Retrieve data for malaria in Kiambu county in the outpatient data element groupsdata<- get_analytics(dx %.d%malaria$id,pe %.d%'LAST_YEAR',ou %.f%kiambu_county$id ) %>% left_join(malaria,by= c('dx'='id'))data#> # A tibble: 4 × 4#> dx pe value name#> <chr> <chr> <dbl> <chr>#> 1 Lt0FqtnHraW 2023 31101 Suspected Malaria#> 2 OoakJhWiyZp 2023 5092 Confirmed Malaria (only Positive cases)#> 3 siOyOiOJpI8 2023 20554 MOH 705A Rev 2020_ Tested for Malaria#> 4 gvZmXInRLuD 2023 397 Malaria in pregnancy
Get Started is a moreextensive general introduction to khisr.
Browse thearticlesindex to find articlesthat cover various topics in more depth.
See thefunction indexfor an organized, exhaustive listing.
Please note that the khisr project is released with aContributor CodeofConduct.By contributing to this project, you agree to abide by its terms.
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