Extract test data. — extract_test

Query an RSQLite database and return a data frame containing the most recent test result that meets specified criteria.

Usage

extract_test_recent(
  cohort,
  varname = NULL,
  codelist = NULL,
  codelist_vector = NULL,
  codelist_df = NULL,
  indexdt,
  t = NULL,
  t_varname = TRUE,
  time_prev = 365.25 * 5,
  time_post = 0,
  lower_bound = -Inf,
  upper_bound = Inf,
  keep_numunit = FALSE,
  db_open = NULL,
  db = NULL,
  db_filepath = NULL,
  table_name = NULL,
  out_save_disk = FALSE,
  out_subdir = NULL,
  out_filepath = NULL,
  return_output = FALSE
)

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.
lower_bound: Lower bound for returned values.
upper_bound: Upper bound for returned values.
keep_numunit: TRUE/FALSE whether to keep numunitid, medcodeid and obsdate in the outputted dataset.
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.
table_name: Specify name of table in the SQLite database to be queried, if this is different from 'observation'.
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 containing most recent test result that meets required criteria.

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 convetion. 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.

Currently only returns most recent test result. This will be updated to return more than one most recent test result if specified.

The argument table_name is only necessary if the name of the table being queried does not match 'observation'. 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 2025-03-31 10:55:12.586361
#> 
  |                                                                            
  |=======================                                               |  33%
#> Adding /home/runner/work/_temp/Library/rcprd/aurum_data/aurum_allpatid_set1_extract_observation_002.txt 2025-03-31 10:55:12.601482
#> 
  |                                                                            
  |===============================================                       |  67%
#> Adding /home/runner/work/_temp/Library/rcprd/aurum_data/aurum_allpatid_set1_extract_observation_003.txt 2025-03-31 10:55:12.613296
#> 
  |                                                                            
  |======================================================================| 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 most recent test value prior to index date
extract_test_data(pat,
codelist_vector = "187341000000114",
indexdt = "fup_start",
db_open = aurum_extract,
time_prev = Inf,
return_output = TRUE)
#>    patid value
#> 1      1    NA
#> 2     10    NA
#> 3     11    NA
#> 4     12    NA
#> 5      2    46
#> 6      3    NA
#> 7      4    NA
#> 8      5    NA
#> 9      6    28
#> 10     7    NA
#> 11     8    NA
#> 12     9    NA

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