Basic REDCapR Operations • REDCapR

This vignette covers the the basic functions exposed by the httr and curl packages which allow you to interact with REDCap through its API.

Reading REDCap Data

The functions redcap_read() and redcap_read_oneshot() use the httr package to call the REDCap API.

## Loading required namespace: kableExtra

Set project-wide values

There is some information that is specific to the REDCap project, as opposed to an individual operation. This includes the (1) uri of the server, and the (2) token for the user’s project.

library(REDCapR) # Load the package into the current R session.
uri   <- "https://redcap-dev-2.ouhsc.edu/redcap/api/"
token <- "9A068C425B1341D69E83064A2D273A70" # simple

Read all records and fields

If no information is passed about the desired records or fields, then the entire data set is returned. Only two parameters are required, redcap_uri and token. Unless the verbose parameter is set to FALSE, a message will be printed on the R console with the number of records and fields returned.

# Return all records and all variables.
ds_all_rows_all_fields <- redcap_read(redcap_uri = uri, token = token)$data
#> 24 variable metadata records were read from REDCap in 0.2 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 5 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 5 records  at 2024-12-09 22:34:00.392586.
#> Reading batch 1 of 1, with subjects 1 through 5 (ie, 5 unique subject records).
#> 5 records and 25 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
ds_all_rows_all_fields # Inspect the returned dataset
#> # A tibble: 5 × 25
#>   record_id name_first name_last address  telephone email dob          age   sex
#>       <dbl> <chr>      <chr>     <chr>    <chr>     <chr> <date>     <dbl> <dbl>
#> 1         1 Nutmeg     Nutmouse  "14 Ros… (405) 32… nutt… 2003-08-30    11     0
#> 2         2 Tumtum     Nutmouse  "14 Ros… (405) 32… tumm… 2003-03-10    11     1
#> 3         3 Marcus     Wood      "243 Hi… (405) 32… mw@m… 1934-04-09    80     1
#> 4         4 Trudy      DAG       "342 El… (405) 32… pero… 1952-11-02    61     0
#> 5         5 John Lee   Walker    "Hotel … (405) 32… left… 1955-04-15    59     1
#> # ℹ 16 more variables: demographics_complete <dbl>, height <dbl>, weight <dbl>,
#> #   bmi <dbl>, comments <chr>, mugshot <chr>, health_complete <dbl>,
#> #   race___1 <dbl>, race___2 <dbl>, race___3 <dbl>, race___4 <dbl>,
#> #   race___5 <dbl>, race___6 <dbl>, ethnicity <dbl>, interpreter_needed <dbl>,
#> #   race_and_ethnicity_complete <dbl>

Read a subset of the records

If only a subset of the records is desired, the two approaches are shown below. The first is to pass an array (where each element is an ID) to the records parameter. The second is to pass a single string (where the elements are separated by commas) to the records_collapsed parameter.

The first format is more natural for more R users. The second format is what is expected by the REDCap API. If a value for records is specified, but records_collapsed is not specified, then redcap_read_oneshot automatically converts the array into the format needed by the API.

# Return only records with IDs of 1 and 3
desired_records <- c(1, 3)
ds_some_rows_v1 <- redcap_read(
  redcap_uri = uri,
  token      = token,
  records    = desired_records
)$data
#> 24 variable metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.2 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.2 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.2 seconds.  The http status code was 200.
#> 2 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 2 records  at 2024-12-09 22:34:02.415309.
#> Reading batch 1 of 1, with subjects 1 through 3 (ie, 2 unique subject records).
#> 2 records and 25 columns were read from REDCap in 0.2 seconds.  The http status code was 200.

Read a subset of the fields

If only a subset of the fields is desired, then two approaches exist. The first is to pass an array (where each element is an field) to the fields parameter. The second is to pass a single string (where the elements are separated by commas) to the fields_collapsed parameter. Like with records and records_collapsed described above, this function converts the more natural format (i.e., fields) to the format required by the API (i.e., fields_collapsed) if fields is specified and fields_collapsed is not.

# Return only the fields record_id, name_first, and age
desired_fields <- c("record_id", "name_first", "age")
ds_some_fields <- redcap_read(
  redcap_uri = uri,
  token      = token,
  fields     = desired_fields
)$data
#> 24 variable metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 5 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 5 records  at 2024-12-09 22:34:04.178191.
#> Reading batch 1 of 1, with subjects 1 through 5 (ie, 5 unique subject records).
#> 5 records and 3 columns were read from REDCap in 0.2 seconds.  The http status code was 200.

Read a subset of records, conditioned on the values in some variables

The two techniques above can be combined when your datasets are large and you don’t want to pull records with certain values. Suppose you want to select subjects from the previous dataset if the were born before 1960 and their weight was over 70kg. Two calls to the server are required. The first call to REDCap pulls all the records, but for only three columns: record_id, dob, and weight. From this subset, identify the records that you want to pull all the data for; in this case, the desired record_id values are 3 & 5. The second call to REDCap pulls all the columns, but only for the identified records.

######
## Step 1: First call to REDCap
desired_fields_v3 <- c("record_id", "dob", "weight")
ds_some_fields_v3 <- redcap_read(
  redcap_uri = uri,
  token      = token,
  fields     = desired_fields_v3
)$data
#> 24 variable metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 5 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 5 records  at 2024-12-09 22:34:05.927422.
#> Reading batch 1 of 1, with subjects 1 through 5 (ie, 5 unique subject records).
#> 5 records and 3 columns were read from REDCap in 0.2 seconds.  The http status code was 200.

ds_some_fields_v3 #Examine the these three variables.
#> # A tibble: 5 × 3
#>   record_id dob        weight
#>       <dbl> <date>      <dbl>
#> 1         1 2003-08-30      1
#> 2         2 2003-03-10      1
#> 3         3 1934-04-09     80
#> 4         4 1952-11-02     54
#> 5         5 1955-04-15    104

######
## Step 2: identify desired records, based on age & weight
before_1960 <- (ds_some_fields_v3$dob <= as.Date("1960-01-01"))
heavier_than_70_kg <- (ds_some_fields_v3$weight > 70)
desired_records_v3 <- ds_some_fields_v3[before_1960 & heavier_than_70_kg, ]$record_id

desired_records_v3 #Peek at IDs of the identified records
#> [1] 3 5

######
## Step 3: second call to REDCap
#Return only records that met the age & weight criteria.
ds_some_rows_v3 <- redcap_read(
  redcap_uri = uri,
  token      = token,
  records    = desired_records_v3
)$data
#> 24 variable metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 2 records  at 2024-12-09 22:34:07.725472.
#> Reading batch 1 of 1, with subjects 3 through 5 (ie, 2 unique subject records).
#> 2 records and 25 columns were read from REDCap in 0.2 seconds.  The http status code was 200.

ds_some_rows_v3 #Examine the results.
#> # A tibble: 2 × 25
#>   record_id name_first name_last address  telephone email dob          age   sex
#>       <dbl> <chr>      <chr>     <chr>    <chr>     <chr> <date>     <dbl> <dbl>
#> 1         3 Marcus     Wood      "243 Hi… (405) 32… mw@m… 1934-04-09    80     1
#> 2         5 John Lee   Walker    "Hotel … (405) 32… left… 1955-04-15    59     1
#> # ℹ 16 more variables: demographics_complete <dbl>, height <dbl>, weight <dbl>,
#> #   bmi <dbl>, comments <chr>, mugshot <chr>, health_complete <dbl>,
#> #   race___1 <dbl>, race___2 <dbl>, race___3 <dbl>, race___4 <dbl>,
#> #   race___5 <dbl>, race___6 <dbl>, ethnicity <dbl>, interpreter_needed <dbl>,
#> #   race_and_ethnicity_complete <dbl>

Additional Returned Information

The examples above have shown only the resulting data frame, by specifying $data at the end of the call. However, more is available to those wanting additional information, such as:

The data object has the data frame, as in the previous examples.
The success boolean value indicates if redcap_read_oneshot believes the operation completed as intended.
The status_codes is a collection of http status codes, separated by semicolons. There is one code for each batch attempted.
The outcome_messages: A collection of human readable strings indicating the operations’ semicolons. There is one code for each batch attempted. In an unsuccessful operation, it should contain diagnostic information.
The records_collapsed field passed to the API. This shows which record subsets, if any, were requested.
The fields_collapsed fields passed to the API. This shows which field subsets, if any, were requested.
The elapsed_seconds measures the duration of the call.

#Return only the fields record_id, name_first, and age
all_information <- redcap_read(
  redcap_uri = uri,
  token      = token,
  fields     = desired_fields
)
#> 24 variable metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> The data dictionary describing 17 fields was read from REDCap in 0.1 seconds.  The http status code was 200.
#> 3 instrument metadata records were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 1 rows were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 2 data access groups were read from REDCap in 0.1 seconds.  The http status code was 200.
#> 5 records and 1 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
#> Starting to read 5 records  at 2024-12-09 22:34:09.467074.
#> Reading batch 1 of 1, with subjects 1 through 5 (ie, 5 unique subject records).
#> 5 records and 3 columns were read from REDCap in 0.2 seconds.  The http status code was 200.
all_information #Inspect the additional information
#> $data
#> # A tibble: 5 × 3
#>   record_id name_first   age
#>       <dbl> <chr>      <dbl>
#> 1         1 Nutmeg        11
#> 2         2 Tumtum        11
#> 3         3 Marcus        80
#> 4         4 Trudy         61
#> 5         5 John Lee      59
#> 
#> $success
#> [1] TRUE
#> 
#> $status_codes
#> [1] "200"
#> 
#> $outcome_messages
#> [1] "5 records and 3 columns were read from REDCap in 0.2 seconds.  The http status code was 200."
#> 
#> $records_collapsed
#> [1] ""
#> 
#> $fields_collapsed
#> [1] "record_id,name_first,age"
#> 
#> $forms_collapsed
#> [1] ""
#> 
#> $events_collapsed
#> [1] ""
#> 
#> $filter_logic
#> [1] ""
#> 
#> $datetime_range_begin
#> [1] NA
#> 
#> $datetime_range_end
#> [1] NA
#> 
#> $elapsed_seconds
#> [1] 1.592879

Session Information

For the sake of documentation and reproducibility, the current report was rendered in the following environment. Click the line below to expand.

Environment

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