| Title: | Streamline Access to Cancer Screening Data |
|---|---|
| Description: | Retrieve cancer screening data for cervical, breast and colorectal cancers from the Kenya Health Information System <https://hiskenya.org> in a consistent way. |
| Authors: | David Kariuki [aut, cre, cph] |
| Maintainer: | David Kariuki <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 1.1.1.9000 |
| Built: | 2024-11-09 04:38:30 UTC |
| Source: | https://github.com/damurka/cancerscreening |
Some aspects of cancerscreening behaviour can be controlled via an option.
with_cancerscreening_quiet(code) local_cancerscreening_quiet(env = parent.frame())with_cancerscreening_quiet(code) local_cancerscreening_quiet(env = parent.frame())
code |
Code to execute quietly |
env |
The environment to use for scoping |
No return value, called for side effects
No return value, called for side effects
No return value, called for side effects
The cancerscreening_quiet option can be used to suppress messages form
cancerscreening. By default, cancerscreening always messages, i.e. it is not
quiet.
set cancerscreening_quiet to TRUE to suppress message, by one of these
means, in order of decreasing scope:
Put options(cancerscreening_quiet = TRUE) in the start-up file, such as
.Rprofile, or in your R script
Use local_cancerscreening_quiet() to silence cancerscreening in a specific
scope
Use with_cancerscreening_quite to run small bit of code silently
local_cancerscreening_quiet and with_cancerscreening follow the conventions
of the withr package (https://withr.r-lib.org).
## Not run: # message: "The credentials have been set." khis_cred(username = 'username', password = 'password') # suppress messages for a small amount of code with_cancerscreening_quiet( khis_cred(username = 'username', password = 'password') ) ## End(Not run) ## Not run: # message: "The credentials have been set." khis_cred(username = 'username', password = 'password') # suppress messages for a in a specific scope local_cancerscreening_quiet() # no message khis_cred(username = 'username', password = 'password') # clear credentials khis_cred_clear() ## End(Not run)## Not run: # message: "The credentials have been set." khis_cred(username = 'username', password = 'password') # suppress messages for a small amount of code with_cancerscreening_quiet( khis_cred(username = 'username', password = 'password') ) ## End(Not run) ## Not run: # message: "The credentials have been set." khis_cred(username = 'username', password = 'password') # suppress messages for a in a specific scope local_cancerscreening_quiet() # no message khis_cred(username = 'username', password = 'password') # clear credentials khis_cred_clear() ## End(Not run)
get_analytics_formatted() fetches data from the KHIS analytics data tables
for a given period and data element(s), without performing any aggregation.
get_analytics_formatted( element_ids, start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_analytics_formatted( element_ids, start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
element_ids |
A vector of data element IDs for which to retrieve data. Required. |
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
Retrieves data directly from KHIS analytics tables.
Supports optional arguments for providing organization lists, data elements, and categories.
Allows specifying KHIS session objects, retry attempts, and logging verbosity.
A tibble with detailed information, including:
Geographical identifiers (country, county, subcounty, ward, facility, depending on level)
Reporting period (month, year, fiscal year)
Data element names
Category options
Reported values
# Clinical Breast Examination data elements # XEX93uLsAm2 = CBE Abnormal # cXe64Yk0QMY = CBE Normal element_id = c('cXe64Yk0QMY', 'XEX93uLsAm2') # Download data from February 2023 to current date data <- get_analytics_formatted(element_ids = element_id, start_date = '2023-02-01') data# Clinical Breast Examination data elements # XEX93uLsAm2 = CBE Abnormal # cXe64Yk0QMY = CBE Normal element_id = c('cXe64Yk0QMY', 'XEX93uLsAm2') # Download data from February 2023 to current date data <- get_analytics_formatted(element_ids = element_id, start_date = '2023-02-01') data
get_breast_cbe() retrieves data for CBE conducted within a specified
period from the KHIS API server.
get_breast_cbe( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_breast_cbe( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing data for CBE conducted with the following columns:
country - Name of the country country
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
age_group - The age group category of the report (25-34, 35-39, 40-55, 56-74, or 75+).
category - Additional category if available.
element - The data element.
value - The number reported.
# Download data from February 2023 to current date cbe_data <- get_breast_cbe(start_date = '2023-02-01') cbe_data# Download data from February 2023 to current date cbe_data <- get_breast_cbe(start_date = '2023-02-01') cbe_data
get_breast_mammogram() retrieves data for mammograms conducted within a
specified period from the KHIS API server.
get_breast_mammogram( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_breast_mammogram( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing data for mammograms conducted with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (25-34, 35-39, 40-55, 56-74, or 75+).
category2 - Additional category if available.
element - The data element.
value - The number reported.
# Download data from February 2023 to current date mammogram_data <- get_breast_mammogram(start_date = '2023-02-01') mammogram_data# Download data from February 2023 to current date mammogram_data <- get_breast_mammogram(start_date = '2023-02-01') mammogram_data
get_breast_ultrasound() retrieves data for breast ultrasounds conducted within a
specified period from the KHIS API server.
get_breast_ultrasound( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_breast_ultrasound( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing data for breast ultrasound conducted with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (25-34, 35-39, 40-55, 56-74, or 75+).
category2 - Additional category if available.
element - The data element.
value - The number reported.
# Download data from February 2023 to current date ultrasound_data <- get_breast_ultrasound(start_date = '2023-02-01') ultrasound_data# Download data from February 2023 to current date ultrasound_data <- get_breast_ultrasound(start_date = '2023-02-01') ultrasound_data
get_cervical_hiv_screened() retrieves cervical cancer screening and positivity
data for HIV positive women for a specified period from the KHIS API server.
get_cervical_hiv_screened( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_cervical_hiv_screened( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing cervical cancer screening data on HIV positive women with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (<25, 25-49, 50+).
category2 - Additional category if available.
element - The data element (HPV, VIA or Pap Smear).
source - The source report (MOH 711 or MOH 745).
value - The number reported.
# Download data from February 2023 to current date screened <- get_cervical_hiv_screened(start_date = '2023-02-01') screened# Download data from February 2023 to current date screened <- get_cervical_hiv_screened(start_date = '2023-02-01') screened
get_cervical_positive() retrieves cervical cancer screening data with positive results
for a specified period from the KHIS API server.
get_cervical_positive( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_cervical_positive( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing cervical cancer screening data with positive results with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (<25, 25-49, 50+).
category2 - Additional category if available.
element - The data element (HPV, VIA or Pap Smear).
source - The source report (MOH 711 or MOH 745).
value - The number reported.
# Download data from February 2023 to current date positive <- get_cervical_positive(start_date = '2023-02-01') positive# Download data from February 2023 to current date positive <- get_cervical_positive(start_date = '2023-02-01') positive
get_cervical_screened() retrieves cervical cancer screening data for a
specified period from the KHIS API server.
get_cervical_screened( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_cervical_screened( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing cervical cancer screening data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (<25, 25-49, 50+).
category2 - Additional category if available.
element - The data element (HPV, VIA or Pap Smear).
source - The source report (MOH 711 or MOH 745).
value - The number reported.
# Download data from February 2023 to current date screened <- get_cervical_screened(start_date = '2023-02-01') screened# Download data from February 2023 to current date screened <- get_cervical_screened(start_date = '2023-02-01') screened
get_cervical_treated() retrieves cervical cancer precancerous treatment
data for a specified period from the KHIS API server.
get_cervical_treated( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_cervical_treated( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing cervical cancer precancerous treatment data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (<25, 25-49, 50+).
category2 - Additional category if available.
element - The data element (HPV, VIA or Pap Smear).
source - The source report (MOH 711 or MOH 745).
value - The number reported.
# Download data from February 2023 to current date treated <- get_cervical_treated(start_date = '2023-02-01') treated# Download data from February 2023 to current date treated <- get_cervical_treated(start_date = '2023-02-01') treated
get_colorectal_colonoscopy() retrieves data for colorectal screening using
colonoscopy within a specified period from the KHIS API server.
get_colorectal_colonoscopy( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_colorectal_colonoscopy( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing data for colorectal screening with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (45-54, 55-64, or 65-75).
category2 - Additional category if available.
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_colorectal_colonoscopy(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_colorectal_colonoscopy(start_date = '2023-02-01') data
get_colorectal_fobt() retrieves data for colorectal screening using FOBT within a
specified period from the KHIS API server.
get_colorectal_fobt( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_colorectal_fobt( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing data for colorectal screening with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report (45-54, 55-64, or 65-75).
category2 - Additional category if available.
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_colorectal_fobt(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_colorectal_fobt(start_date = '2023-02-01') data
get_filtered_population() filters the population based on age and level
and projects the population base on the year provided
get_filtered_population( year, min_age, max_age, modifier = 1, level = c("country", "county", "subcounty"), pop_sex = c("female", "male", "both"), rate = 0.022 )get_filtered_population( year, min_age, max_age, modifier = 1, level = c("country", "county", "subcounty"), pop_sex = c("female", "male", "both"), rate = 0.022 )
year |
The year to project the population |
min_age |
The minimum age to include in the filtered data |
max_age |
The maximum age to include in the filtered data |
modifier |
A multiplier that affect the population projection. Default 1 |
level |
The desired level of the organization unit hierarchy to retrieve
data for: |
pop_sex |
The desired population sex: |
rate |
The population growth |
A tibble containing the target population
# Get the female population in 2022 aged 25-49 years filtered_population <- get_filtered_population(2022, 25, 49, pop_sex = 'female') filtered_population # Get 5% male population in 2022 aged 40-75 years filtered_population <- get_filtered_population(2022, 40, 75, modifier = 0.05, pop_sex = 'male') filtered_population# Get the female population in 2022 aged 25-49 years filtered_population <- get_filtered_population(2022, 25, 49, pop_sex = 'female') filtered_population # Get 5% male population in 2022 aged 40-75 years filtered_population <- get_filtered_population(2022, 40, 75, modifier = 0.05, pop_sex = 'male') filtered_population
get_lab_bone_marrow() retrieves bone marrow lab data for a specified period
from the KHIS API server.
get_lab_bone_marrow( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_lab_bone_marrow( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing bone marrow lab data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_lab_bone_marrow(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_lab_bone_marrow(start_date = '2023-02-01') data
get_lab_fluid_cytology() retrieves fluid cytology lab data for a specified period
from the KHIS API server.
get_lab_fluid_cytology( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_lab_fluid_cytology( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing fluid cytology lab data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_lab_fluid_cytology(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_lab_fluid_cytology(start_date = '2023-02-01') data
get_lab_fna() retrieves fine-needle aspiration lab data for a specified period
from the KHIS API server.
get_lab_fna( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_lab_fna( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing fine-needle aspiration lab data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_lab_fna(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_lab_fna(start_date = '2023-02-01') data
get_lab_smears() retrieves cytology smears lab data for a specified period
from the KHIS API server.
get_lab_smears( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_lab_smears( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing cytology smears lab data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_lab_smears(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_lab_smears(start_date = '2023-02-01') data
get_lab_tissue_histology() retrieves tissue histology lab data for a specified period
from the KHIS API server.
get_lab_tissue_histology( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_lab_tissue_histology( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble containing tissue histology lab data with the following columns:
country - Name of the country.
county - Name of the county. Optional if the level is county, subcounty, ward or facility.
subcounty - Name of the subcounty. Optional if the level is subcounty, ward or facility.
ward - Name of the ward. Optional if the level is ward or facility.
facility - Name of the health facility. Optional if the level facility.
period - The month and year of the data.
fiscal_year- The financial year of the report(July-June Cycle).
year - The calendar year of the report.
month - The month name of the report.
category - The age group category of the report
element - The data element.
value - The number reported.
# Download data from February 2023 to current date data <- get_lab_tissue_histology(start_date = '2023-02-01') data# Download data from February 2023 to current date data <- get_lab_tissue_histology(start_date = '2023-02-01') data
get_screening_reporting_analytics() It fetches the reporting metrics for the
screening tool (MOH 745).
get_screening_reporting_analytics( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )get_screening_reporting_analytics( start_date, end_date = NULL, level = c("country", "county", "subcounty", "ward", "facility"), organisations = NULL, ... )
start_date |
The start date to retrieve data. It is required and in the
format |
end_date |
The ending date for data retrieval (default is the current date). |
level |
The desired data granularity: |
organisations |
A list of organization units ids to be filtered. |
... |
Other options that can be passed onto KHIS API. |
A tibble with the reporting metrics.
# Download screening metric from February 2023 to current date data <- get_screening_reporting_analytics(start_date = '2023-02-01') data# Download screening metric from February 2023 to current date data <- get_screening_reporting_analytics(start_date = '2023-02-01') data
These functions subsets the Kenyan population to the desirable screening population.
get_cervical_target_population( year, level = c("country", "county", "subcounty") ) get_breast_cbe_target_population( year, level = c("country", "county", "subcounty") ) get_breast_mammogram_target_population( year, level = c("country", "county", "subcounty") ) get_colorectal_target_population( year, level = c("country", "county", "subcounty") )get_cervical_target_population( year, level = c("country", "county", "subcounty") ) get_breast_cbe_target_population( year, level = c("country", "county", "subcounty") ) get_breast_mammogram_target_population( year, level = c("country", "county", "subcounty") ) get_colorectal_target_population( year, level = c("country", "county", "subcounty") )
year |
Year for which to estimate population. |
level |
The desired level of the organization unit hierarchy to retrieve
data for: |
get_cervical_target_population() subsets the target population for cervical
cancer screening: females aged between 25 years and 50 years
get_breast_cbe_target_population() subsets the target population for clinical
breast examination: females aged between 25 years and 74 years
get_breast_mammogram_target_population() subsets the target population for
breast cancer screening through mammography: females aged between 40 years to 74 years
get_colorectal_target_population() subsets the target population for
colorectal cancer screening: males and females aged between 45 years to 75 years
These target populations are guided by the Kenya National Cancer Screening Guidelines 2018. The population projection for counties and the national level are calculated based on population growth 2.2% obtained from the Kenya National Bureau of Statistics. The annual targets follows the guidance of screening guidelines and for cervical cancer it is also guided by the WHO publication 'Planning and implementing cervical cancer prevention programs: A manual for managers.'
A tibble containing the target screening population
county - name of the county. Optional if the level is county or subcounty
subcounty - name of the county. Optional if the level if subcounty
target - number to be screened
A tibble containing the target screening population
A tibble containing the target screening population
A tibble containing the target screening population
# Get the country projection for cervical cancer screening for the year 2024 target_population <- get_cervical_target_population(2024) target_population # Get the projection for cervical cancer screening for 2022 by county target_population <- get_cervical_target_population(2022, level = 'county') target_population # Get the projection for CBE for 2022 by county target_population <- get_breast_cbe_target_population(2022, level = 'county') target_population # Get the country projection of women to perform mammogram for the year 2024 target_population <- get_breast_mammogram_target_population(2024) target_population # Get the country projection colorectal cancer screening for the year 2024 target_population <- get_colorectal_target_population(2024) target_population# Get the country projection for cervical cancer screening for the year 2024 target_population <- get_cervical_target_population(2024) target_population # Get the projection for cervical cancer screening for 2022 by county target_population <- get_cervical_target_population(2022, level = 'county') target_population # Get the projection for CBE for 2022 by county target_population <- get_breast_cbe_target_population(2022, level = 'county') target_population # Get the country projection of women to perform mammogram for the year 2024 target_population <- get_breast_mammogram_target_population(2024) target_population # Get the country projection colorectal cancer screening for the year 2024 target_population <- get_colorectal_target_population(2024) target_population