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Clinical Facts per Patient – PCORnet

Source: R/pf_process_pcornet.R
pf_process_pcornet.Rd

This is a completeness check that will compute the number of facts per years of follow-up for each patient in a cohort. The user will provide the domains (domain_tbl) and visit types (visit_type_tbl) of interest. Sample versions of these inputs are included as data in the package and are accessible with patientfacts::. Results can optionally be stratified by site, age group, visit type, and/or time.

Usage

pf_process_pcornet(
  cohort = cohort,
  study_name = "my_study",
  patient_level_tbl = FALSE,
  visit_types = c("outpatient", "inpatient"),
  multi_or_single_site = "single",
  time = FALSE,
  time_span = c("2014-01-01", "2023-01-01"),
  time_period = "year",
  p_value = 0.9,
  age_groups = NULL,
  anomaly_or_exploratory = "exploratory",
  domain_tbl = patientfacts::pf_domain_file,
  visit_tbl = cdm_tbl("encounter"),
  visit_type_table = patientfacts::pf_visit_file_pcornet
)

Arguments

cohort

A dataframe with the cohort of patients for your study. Should include the columns:

  • person_id

  • start_date

  • end_date

  • site

study_name

A custom string label with the name of your study

patient_level_tbl

logical indicating whether an additional table with patient level results should be output; if TRUE, the output of this function will be a list containing both the summary and patient level output. Otherwise, this function will just output the summary dataframe

visit_types

A list of visit types by which the output should be stratified. Options for visit types can be found or adjusted in the provided pf_visit_file_(omop/pcornet) file. If you would not like to stratify your results by visit type, please set the visit_types argument equal to all

multi_or_single_site

Option to run the function on a single vs multiple sites

  • single: run the function for a single site

  • multi: run the function for multiple sites

time

a logical that tells the function whether you would like to look at the output cross-sectionally (FALSE) or longitudinally (TRUE)

time_span

when time = TRUE, this argument defines the start and end dates for the time period of interest. should be formatted as c(start date, end date) in yyyy-mm-dd date format.

time_period

when time = TRUE, this argument defines the distance between dates within the specified time period. defaults to year, but other time periods such as month or week are also acceptable

p_value

an integer indicating the p value to be used as a threshold in the multi-site anomaly detection analysis

age_groups

If you would like to stratify the results by age group, create a table or CSV file with the following columns and include it as the age_groups function parameter:

  • min_age: the minimum age for the group (i.e. 10)

  • max_age: the maximum age for the group (i.e. 20)

  • group: a string label for the group (i.e. "10-20", "Young Adult", etc.)

If you would not like to stratify by age group, leave the argument as NULL

anomaly_or_exploratory

Option to conduct an exploratory or anomaly detection analysis. Exploratory analyses give a high level summary of the data to examine the fact representation within the cohort. Anomaly detection analyses are specialized to identify outliers within the cohort.

domain_tbl

a table that defines the domains where facts should be identified. defaults to the provided pf_domain_file table, which contains the following fields:

  • domain: a string label for the domain being examined (i.e. prescription drugs)

  • domain_tbl: the CDM table where information for this domain can be found (i.e. drug_exposure)

  • filter_logic: an optional string to be parsed as logic to filter the domain_tbl as needed to best represent the domain

visit_tbl

the CDM table with visit information (i.e. visit_occurrence or encounter)

visit_type_table

a table that defines available visit types that are called in visit_types. defaults to the provided pf_visit_file_(omop/pcornet) file, which contains the following fields:

  • visit_concept_id or enc_type: the visit_concept_id or enc_type that represents the visit type of interest (i.e. 9201 or IP)

  • visit_type: the string label to describe the visit type; this label can be used multiple times within the file if multiple visit_concept_ids/enc_types represent the visit type

Value

a dataframe with summary results (i.e. medians) that can be used as the input for pf_output to generate graphical output

if patient_level_tbl = TRUE, an additional dataframe is returned in a list format with patient level output

Details

This version of the function is compatible with the PCORnet CDM.