This function will compute the number of rows, patients, and (optionally) visits associated with the fact of interest within a specified time period. The user will supply the end points of the time span (i.e. January 2009 - January 2024) and the time period they wish to divide it by (i.e. month, year).
Usage
check_fot(
fot_tbl,
omop_or_pcornet = "omop",
compute_method = "loop",
time_span = list("2009-01-01", today()),
time_period = "month",
lookback_interval = 1,
check_string = "fot",
visits_only = FALSE,
distinct_visits = TRUE
)Arguments
- fot_tbl
tabular input || required
The primary input table that contains descriptive information about the checks to be executed by the function. It should include definitions for the clinical fact types that should be evaluated across the user-specified time span per each time period. see
?fot_input_omopor?fot_input_pcornetfor examples of the input structure- omop_or_pcornet
string || defaults to
omopA string, either
omoporpcornet, indicating the CDM format of the data- compute_method
string || defaults to
loopA string, either
looporgroup, that controls whether the check is executed by looping through each time period or grouping by a date field to obtain counts.groupis recommended for high performing database systems.- time_span
list (length 2) || defaults to
list('2009-01-01', today())A list that contains the start date and end date of the total time period of interest
- time_period
string || defaults to
monthA string indicating the length of each time period that should be examined, like months or years
- lookback_interval
integer || defaults to
1An integer indicating the number of time periods (defined in
time_period) to look back in each interval. For example, atime_periodofmonthand alookback_intervalof3would produce quarterly counts.- check_string
string || defaults to
fotAn abbreviated identifier that will be used to label all output from this module
- visits_only
boolean || defaults to FALSE
If set to
TRUE, then this function will only return visit counts and will not return patient or row counts. By default, visit, row, and patient counts are returned.- distinct_visits
boolean || defaults to TRUE
If set to
FALSE, then this function will only return patient and row counts and will not return visit counts. By default, visit, row, and patient counts are returned.
Value
This function will return a dataframe with one row for each time period within the specified time span for each check. Additionally:
If
visits_only = TRUE, only visit counts will be returned for the check + time periodIf
visits_only = FALSEanddistinct_visits = TRUE, patient, row, and visit counts will be returned for the check + time periodIf
visits_only = FALSEanddistinct_visits = FALSE, only patient and row counts will be returned for the check + time period
Examples
# First create input file with desired checks to be executed
# You can access examples for both OMOP & PCORnet here:
ndq::fot_input_omop
#> # A tibble: 22 × 6
#> check_id check_description schema table date_field filter_logic
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 vi all visits cdm visi… visit_sta… NA
#> 2 vo_office outpatient visits cdm visi… visit_sta… visit_conce…
#> 3 vo_labs outpatient lab visits cdm visi… visit_sta… visit_conce…
#> 4 vo_th telehealth visits cdm visi… visit_sta… visit_conce…
#> 5 vo_oa other ambulatory visits cdm visi… visit_sta… visit_conce…
#> 6 vip inpatient visits (9201 or 200… cdm visi… visit_sta… visit_conce…
#> 7 ved emergency department visits cdm visi… visit_sta… visit_conce…
#> 8 vob observation visits cdm visi… visit_sta… visit_conce…
#> 9 co all conditions cdm cond… condition… NA
#> 10 dp prescription drugs cdm drug… drug_expo… drug_type_c…
#> # ℹ 12 more rows
ndq::fot_input_pcornet
#> # A tibble: 21 × 6
#> check_id check_description schema table date_field filter_logic
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 vi all visits cdm enco… admit_date NA
#> 2 vo_office outpatient visits cdm enco… admit_date enc_type ==…
#> 3 vo_th telehealth visits cdm enco… admit_date enc_type ==…
#> 4 vo_oa other ambulatory visits cdm enco… admit_date enc_type ==…
#> 5 vip inpatient visits (9201 or 200… cdm enco… admit_date enc_type %i…
#> 6 ved emergency department visits cdm enco… admit_date enc_type ==…
#> 7 vob observation visits cdm enco… admit_date enc_type ==…
#> 8 co all diagnoses cdm diag… admit_date NA
#> 9 dp prescription drugs cdm pres… rx_start_… NA
#> 10 ip inpatient administration drugs cdm med_… medadmin_… NA
#> # ℹ 11 more rows
# Use this as your input to the FOT function
## This check can be executed for different time period lengths, like...
### Yearly
if (FALSE) { # \dontrun{
my_fot_rslt <- check_fot(fot_tbl = ndq::fot_input_omop,
omop_or_pcornet = 'omop',
compute_method = 'loop', # use 'group' for high performant DBMSs
time_span = list('2015-01-01', '2025-01-01'),
time_period = 'year',
lookback_interval = 1,
check_string = 'fot')
} # }
### Monthly
if (FALSE) { # \dontrun{
my_fot_rslt <- check_fot(fot_tbl = ndq::fot_input_omop,
omop_or_pcornet = 'omop',
compute_method = 'loop', # use 'group' for high performant DBMSs
time_span = list('2015-01-01', '2025-01-01'),
time_period = 'month',
lookback_interval = 1,
check_string = 'fot')
} # }
### Quarterly
if (FALSE) { # \dontrun{
my_fot_rslt <- check_fot(fot_tbl = ndq::fot_input_omop,
omop_or_pcornet = 'omop',
compute_method = 'loop', # use 'group' for high performant DBMSs
time_span = list('2015-01-01', '2025-01-01'),
time_period = 'month',
lookback_interval = 3,
check_string = 'fot')
} # }