Skip to contents

Extract a 'history of' type variable

extract_ho.Rd

Query an RSQLite database and return a data frame with a 0/1 vector depending on whether each individual has at least one observation with relevant code between a specified time period.

Usage

extract_ho(
  cohort,
  varname = NULL,
  codelist = NULL,
  codelist_vector = NULL,
  codelist_df = NULL,
  indexdt,
  t = NULL,
  t_varname = TRUE,
  time_prev = Inf,
  time_post = 0,
  numobs = 1,
  db_open = NULL,
  db = NULL,
  db_filepath = NULL,
  tab = c("observation", "drugissue", "hes_primary", "death"),
  table_name = NULL,
  out_save_disk = FALSE,
  out_subdir = NULL,
  out_filepath = NULL,
  return_output = TRUE
)

Arguments

cohort

Cohort of individuals to extract the 'history of' variable for.

varname

Name of variable in the outputted data frame.

codelist

Name of codelist (stored on hard disk) to query the database with.

codelist_vector

Vector of codes to query the database with. This takes precedent over codelist if both are specified.

codelist_df

data.frame used to specify the codelist.

indexdt

Name of variable in cohort which specifies the index date. The extracted variable will be calculated relative to this.

t

Number of days after indexdt at which to extract the variable.

t_varname

Whether to alter the variable name in the outputted data frame to reflect t.

time_prev

Number of days prior to index date to look for codes.

time_post

Number of days after index date to look for codes.

numobs

Number of obesrvations required to return a value of 1.

db_open

An open SQLite database connection created using RSQLite::dbConnect, to be queried.

db

Name of SQLITE database on hard disk (stored in "data/sql/"), to be queried.

db_filepath

Full filepath to SQLITE database on hard disk, to be queried.

tab

Table name to query in SQLite database.

table_name

Specify name of table in the SQLite database to be queried, if this is different from tab.

out_save_disk

If TRUE will attempt to save outputted data frame to directory "data/extraction/".

out_subdir

Sub-directory of "data/extraction/" to save outputted data frame into.

out_filepath

Full filepath and filename to save outputted data frame into.

return_output

If TRUE will return outputted data frame into R workspace.

Value

A data frame with a 0/1 vector and patid. 1 = presence of code within the specified time period.

Details

Specifying db requires a specific underlying directory structure. The SQLite database must be stored in "data/sql/" relative to the working directory. If the SQLite database is accessed through db, the connection will be opened and then closed after the query is complete. The same is true if the database is accessed through db_filepath. A connection to the SQLite database can also be opened manually using RSQLite::dbConnect, and then using the object as input to parameter db_open. After wards, the connection must be closed manually using RSQLite::dbDisconnect. If db_open is specified, this will take precedence over db or db_filepath.

If out_save_disk = TRUE, the data frame will automatically be written to an .rds file in a subdirectory "data/extraction/" of the working directory. This directory structure must be created in advance. out_subdir can be used to specify subdirectories within "data/extraction/". These options will use a default naming convention. This can be overwritten using out_filepath to manually specify the location on the hard disk to save. Alternatively, return the data frame into the R workspace using return_output = TRUE and then save onto the hard disk manually.

Codelists can be specified in three ways. The first is to read the codelist into R as a character vector and then specify through the argument codelist_vector. The second is codelists stored on the hard disk, which can = be referred to from the codelist argument, but require a specific underlying directory structure. The codelist on the hard disk must be stored in a directory called "codelists/analysis/" relative to the working directory. The codelist must be a .csv file, and contain a column "medcodeid", "prodcodeid" or "ICD10" depending on the input for argument tab. The input to argument codelist must be a character string of the name of the files (excluding the suffix '.csv'). The third is to specify the codelist through an R data.frame, codelist_df, this must contain a column "medcodeid", "prodcodeid" or "ICD10" depending on the chosen tab. Specifying the codelist this way will retain all the other columns from codelist_df in the queried output.

The argument table_name is only necessary if the name of the table being queried does not match the CPRD filetype specified in tab. This will occur when str_match is used in cprd_extract or add_to_database to create the .sqlite database.

Examples


## Connect
aurum_extract <- connect_database(file.path(tempdir(), "temp.sqlite"))

## Create SQLite database using cprd_extract
cprd_extract(aurum_extract,
filepath = system.file("aurum_data", package = "rcprd"),
filetype = "observation", use_set = FALSE)
#> 
  |                                                                            
  |                                                                      |   0%
#> Adding /home/runner/work/_temp/Library/rcprd/aurum_data/aurum_allpatid_set1_extract_observation_001.txt 2025-09-07 13:13:48.933999
#> 
  |                                                                            
  |=======================                                               |  33%
#> Adding /home/runner/work/_temp/Library/rcprd/aurum_data/aurum_allpatid_set1_extract_observation_002.txt 2025-09-07 13:13:48.946714
#> 
  |                                                                            
  |===============================================                       |  67%
#> Adding /home/runner/work/_temp/Library/rcprd/aurum_data/aurum_allpatid_set1_extract_observation_003.txt 2025-09-07 13:13:48.957771
#> 
  |                                                                            
  |======================================================================| 100%

## Define cohort and add index date
pat<-extract_cohort(system.file("aurum_data", package = "rcprd"))
pat$indexdt <- as.Date("01/01/1955", format = "%d/%m/%Y")

## Extract a history of type variable prior to index date
extract_ho(pat,
codelist_vector = "187341000000114",
indexdt = "fup_start",
db_open = aurum_extract,
tab = "observation",
return_output = TRUE)
#>    patid ho
#> 1      1  0
#> 2      2  1
#> 3      3  0
#> 4      4  0
#> 5      5  0
#> 6      6  1
#> 7      7  0
#> 8      8  0
#> 9      9  0
#> 10    10  0
#> 11    11  0
#> 12    12  0

## clean up
RSQLite::dbDisconnect(aurum_extract)
unlink(file.path(tempdir(), "temp.sqlite"))