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The khisr package is designed to seamlessly integrate with DHIS2, providing R users with a powerful interface for efficient data retrieval. DHIS2 is a cornerstone in health information management for many organisations, and khisr simplifies the process of accessing and working with DHIS2 data directly within the R environment.
You can install the release version of khisr from CRAN 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 means you’ll need to provide credentials before using any functions that interact with your DHIS2 instance to download data. To ensure secure access, khisr offers a convenient way to store your credentials within your R environment. Refer to the following resource for detailed instructions on setting your credentials: set you credentials
# 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')
# Option 3: Set credentials using a Personal Access Token, DHIS2's
# recommended method for scripts and integrations, in place of
# username/password
khis_cred(token = 'DHIS2 personal access token',
server = 'https://<dhis2 server instance>')Once you’ve established your credentials, you’re ready to leverage khisr’s functions to download data from your DHIS2 instance.
For this overview, we’ve logged into DHIS2 as a specific user in a hidden chunk.
This is a basic example which shows you how to solve a common problem:
# Retrieve the organisation units by province (level 2)
provinces <- get_organisation_units(level %.eq% '2')
provinces
#> # A tibble: 18 × 2
#> name id
#> <chr> <chr>
#> 1 01 Vientiane Capital W6sNfkJcXGC
#> 2 02 Phongsali YvLOmtTQD6b
#> 3 03 Louangnamtha XKGgynPS1WZ
#> 4 04 Oudomxai rO2RVJWHpCe
#> 5 05 Bokeo FRmrFTE63D0
#> 6 06 Louangphabang MBZYTqkEgwf
#> 7 07 Houaphan hdeC7uX9Cko
#> 8 08 Xainyabouli RdNV4tTRNEo
#> 9 09 Xiangkhouang VWGSudnonm5
#> 10 10 Vientiane quFXhkOJGB4
#> 11 11 Bolikhamxai vBWtCmNNnCG
#> 12 12 Khammouan c4HrGRJoarj
#> 13 13 Savannakhet pFCZqWnXtoU
#> 14 14 Salavan TOgZ99Jv0bN
#> 15 15 Xekong dOhqCNenSjS
#> 16 16 Champasak sv6c7CpPcrc
#> 17 17 Attapu hRQsZhmvqgS
#> 18 18 Xaisomboun K27JzTKmBKh
# Retrieve an organisation unit by name (level included to ensure it refers to a province)
vientiane_capital <- get_organisation_units(level %.eq% '2',
name %.like% 'Vientiane Capital')
vientiane_capital
#> # A tibble: 1 × 2
#> name id
#> <chr> <chr>
#> 1 01 Vientiane Capital W6sNfkJcXGC
# Retrieve all data elements by data element group for malaria
malaria_group <- get_data_elements(dataElementGroups.name %.like% 'malaria')
malaria_group
#> # A tibble: 316 × 2
#> name id
#> <chr> <chr>
#> 1 CH113a - Children (0-4 y) reporting fever in the last two weeks hzstN9blpky
#> 2 CH114 - Households with at least one ITN gRT7NXBCkbB
#> 3 CH115a - Households with at least one ITN for every two persons xjGwK4DRHxh
#> 4 CH115b - Total individuals who live in the household mn8VQbAjlFU
#> 5 CH116a - People sleeping under an ITN the previous night UXCgJMwfQiG
#> 6 CH116b - Individuals sleeping in the household jrbMyDW8Wnb
#> 7 CH117 - People living in an IRS-sprayed house UCpIrYTr88q
#> 8 CH118 - ITNs distributed cp0mXP6STEA
#> 9 CH119a - Febrile cased tested by RDT rlxpxRQU5m0
#> 10 CH119b - Febrile cases of malaria AJhP60PGXKa
#> # ℹ 306 more rows
# Filter the data elements to those reporting on malaria cases and deaths
malaria <- get_data_elements(dataElementGroups.name %.like% 'malaria',
name %.like% 'MAL - ') %>%
filter(name %in% c('MAL - Malaria confirmed cases reported',
'MAL - Malaria deaths',
'MAL - RDT positive malaria cases',
'MAL - Suspected malaria cases'))
malaria
#> # A tibble: 4 × 2
#> name id
#> <chr> <chr>
#> 1 MAL - Malaria confirmed cases reported lYsfXxCw6Qi
#> 2 MAL - Malaria deaths GxlrIgMyEf4
#> 3 MAL - RDT positive malaria cases vTRrNdOOT9g
#> 4 MAL - Suspected malaria cases cE8SDxizo5s
# Retrieve data for malaria in Vientiane Capital province
data <- get_analytics(
dx %.d% malaria$id,
pe %.d% 'LAST_YEAR',
ou %.f% vientiane_capital$id
) %>%
left_join(malaria, by = c('dx'='id'))
data
#> # A tibble: 4 × 4
#> dx pe value name
#> <chr> <chr> <dbl> <chr>
#> 1 GxlrIgMyEf4 2025 966 MAL - Malaria deaths
#> 2 cE8SDxizo5s 2025 1045 MAL - Suspected malaria cases
#> 3 lYsfXxCw6Qi 2025 120 MAL - Malaria confirmed cases reported
#> 4 vTRrNdOOT9g 2025 242 MAL - RDT positive malaria casesAlongside aggregate analytics, khisr also reads DHIS2’s Tracker API — case-based, person-level data such as tracked entities, enrollments, and events. See Tracker Data for a full guide.
# Tracked entities enrolled in a program, at an org unit and everything below it
get_tracked_entities(
program = 'PREnRHSp3be',
org_units = 'IWp9dQGM0bS',
org_unit_mode = 'DESCENDANTS'
)
#> # A tibble: 270 × 6
#> trackedEntity trackedEntityType createdAt updatedAt orgUnit inactive
#> <chr> <chr> <chr> <chr> <chr> <lgl>
#> 1 qkU5JI6SQcd DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… NRcrkS… FALSE
#> 2 ytRUQrTYLFz DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… QoGegg… FALSE
#> 3 xIOlpNNRcNY DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… o0Q54F… FALSE
#> 4 MNUPROje7ZP DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… wQUe9H… FALSE
#> 5 rlTI0qJF8fl DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… mNaSC8… FALSE
#> 6 NKktLYq4wea DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… aJOpUu… FALSE
#> 7 xwZRdamQoGx DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… hfVWi2… FALSE
#> 8 nZZf0IJzkIe DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… XHCI8A… FALSE
#> 9 kA4Fcarkd9T DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… LpTkKu… FALSE
#> 10 Z746P0ZnrFQ DnxQe1mgmlp 2024-06-06T10:40:… 2024-06-… rYTEjU… FALSE
#> # ℹ 260 more rows
# Events for a program stage at a given org unit
get_events(
program_stage = 'mj1stImcUCi',
org_unit = 'NRcrkSgDX5G',
org_unit_mode = 'DESCENDANTS'
)
#> # A tibble: 1 × 8
#> event status program programStage orgUnit occurredAt scheduledAt dataValues
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <list>
#> 1 viu095e… COMPL… PREnRH… mj1stImcUCi NRcrkS… 2026-05-2… 2027-06-06… <list [2]>Get Started is a more extensive general introduction to khisr.
Tracker Data covers retrieving tracked entities, enrollments, and events.
Browse the articles index to find articles that cover various topics in more depth.
See the function index for an organized, exhaustive listing.
Please note that the khisr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.