Package 'OmopSketch'

Creates a mock database to test OmopSketch package.

Description

Creates a mock database to test OmopSketch package.

Usage

mockOmopSketch(
  con = NULL,
  writeSchema = NULL,
  numberIndividuals = 100,
  seed = NULL
)

Arguments

con	A DBI connection to create the cdm mock object. By default, the connection would be a 'duckdb' one.
writeSchema	Name of an schema of the DBI connection with writing permissions.
numberIndividuals	Number of individuals to create in the cdm reference object.
seed	An optional integer used to set the seed for random number generation, ensuring reproducibility of the generated data. If provided, this seed allows the function to produce consistent results each time it is run with the same inputs. If 'NULL', the seed is not set, which can lead to different outputs on each run.

Value

A mock cdm_reference object.

Examples

mockOmopSketch(numberIndividuals = 100)

---

Plot the concept counts of a summariseConceptCounts output.

Description

Plot the concept counts of a summariseConceptCounts output.

Usage

plotConceptCounts(result, facet = NULL, colour = NULL)

Arguments

result	A summarised_result object (output of summariseConceptCounts).
facet	Columns to face by. Formula format can be provided. See possible columns to face by with: visOmopResults::tidyColumns().
colour	Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().

Value

A ggplot2 object showing the concept counts.

Examples

library(dplyr)

cdm <- mockOmopSketch()

result <- cdm |>
  summariseConceptCounts(
    conceptId = list(
      "Renal agenesis" = 194152,
      "Manic mood" = c(4226696, 4304866, 37110496, 40371897)
    )
  )

result |>
  filter(variable_name == "Number subjects") |>
  plotConceptCounts(facet = "codelist_name", colour = "standard_concept_name")

PatientProfiles::mockDisconnect(cdm)

---

Create a ggplot2 plot from the output of summariseInObservation().

Description

Create a ggplot2 plot from the output of summariseInObservation().

Usage

plotInObservation(result, facet = NULL, colour = NULL)

Arguments

result	A summarised_result object (output of summariseInObservation).
facet	Columns to face by. Formula format can be provided. See possible columns to face by with: visOmopResults::tidyColumns().
colour	Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().

Value

A ggplot showing the table counts

Examples

library(dplyr)

cdm <- mockOmopSketch()

result <- summariseInObservation(
  cdm$observation_period,
  output = c("person-days","records"),
  ageGroup = list("<=40" = c(0, 40), ">40" = c(41, Inf)),
  sex = TRUE
)

result |>
  filter(variable_name == "Number person-days") |>
  plotInObservation(facet = "sex", colour = "age_group")

PatientProfiles::mockDisconnect(cdm)

---

Create a plot from the output of summariseObservationPeriod().

Description

Create a plot from the output of summariseObservationPeriod().

Usage

plotObservationPeriod(
  result,
  variableName = "number subjects",
  plotType = "barplot",
  facet = NULL,
  colour = NULL
)

Arguments

result	A summarised_result object.
variableName	The variable to plot it can be: "number subjects", "records per person", "duration" or "days to next observation period".
plotType	The plot type, it can be: "barplot", "boxplot" or "densityplot".
facet	Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().
colour	Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().

Value

A ggplot2 object.

Examples

cdm <- mockOmopSketch(numberIndividuals = 100)

result <- summariseObservationPeriod(cdm$observation_period)

result |>
  plotObservationPeriod(
    variableName = "duration in days",
    plotType = "boxplot"
  )

PatientProfiles::mockDisconnect(cdm)

---

Create a ggplot of the records' count trend.

Description

Create a ggplot of the records' count trend.

Usage

plotRecordCount(result, facet = NULL, colour = NULL)

Arguments

result	Output from summariseRecordCount().
facet	Columns to face by. Formula format can be provided. See possible columns to face by with: visOmopResults::tidyColumns().
colour	Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().

Value

A ggplot showing the table counts

Examples

cdm <- mockOmopSketch()

summarisedResult <- summariseRecordCount(
  cdm = cdm,
  omopTableName = "condition_occurrence",
  ageGroup = list("<=20" = c(0,20), ">20" = c(21, Inf)),
  sex = TRUE
)

plotRecordCount(summarisedResult, colour = "age_group", facet = sex ~ .)

PatientProfiles::mockDisconnect(cdm = cdm)

---

Summarise concept use in patient-level data

Description

Summarise concept use in patient-level data

Usage

summariseAllConceptCounts(
  cdm,
  omopTableName,
  countBy = "record",
  year = FALSE,
  sex = FALSE,
  ageGroup = NULL,
  dateRange = NULL
)

Arguments

cdm	A cdm object
omopTableName	A character vector of the names of the tables to summarise in the cdm object.
countBy	Either "record" for record-level counts or "person" for person-level counts
year	TRUE or FALSE. If TRUE code use will be summarised by year.
sex	TRUE or FALSE. If TRUE code use will be summarised by sex.
ageGroup	A list of ageGroup vectors of length two. Code use will be thus summarised by age groups.
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object with results overall and, if specified, by strata.

---

Summarise an omop table from a cdm object. You will obtain information related to the number of records, number of subjects, whether the records are in observation, number of present domains and number of present concepts.

Description

Summarise an omop table from a cdm object. You will obtain information related to the number of records, number of subjects, whether the records are in observation, number of present domains and number of present concepts.

Usage

summariseClinicalRecords(
  cdm,
  omopTableName,
  recordsPerPerson = c("mean", "sd", "median", "q25", "q75", "min", "max"),
  inObservation = TRUE,
  standardConcept = TRUE,
  sourceVocabulary = FALSE,
  domainId = TRUE,
  typeConcept = TRUE,
  sex = FALSE,
  ageGroup = NULL,
  dateRange = NULL
)

Arguments

cdm	A cdm_reference object.
omopTableName	A character vector of the names of the tables to summarise in the cdm object.
recordsPerPerson	Generates summary statistics for the number of records per person. Set to NULL if no summary statistics are required.
inObservation	Boolean variable. Whether to include the percentage of records in observation.
standardConcept	Boolean variable. Whether to summarise standard concept information.
sourceVocabulary	Boolean variable. Whether to summarise source vocabulary information.
domainId	Boolean variable. Whether to summarise domain id of standard concept id information.
typeConcept	Boolean variable. Whether to summarise type concept id field information.
sex	Boolean variable. Whether to stratify by sex (TRUE) or not (FALSE).
ageGroup	A list of age groups to stratify results by.
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object.

Examples

cdm <- mockOmopSketch()

summarisedResult <- summariseClinicalRecords(
  cdm = cdm,
  omopTableName = "condition_occurrence",
  recordsPerPerson = c("mean", "sd"),
  inObservation = TRUE,
  standardConcept = TRUE,
  sourceVocabulary = TRUE,
  domainId = TRUE,
  typeConcept = TRUE
)

summarisedResult

PatientProfiles::mockDisconnect(cdm = cdm)

---

Summarise concept counts in patient-level data. Only concepts recorded during observation period are counted.

Description

Summarise concept counts in patient-level data. Only concepts recorded during observation period are counted.

Usage

summariseConceptCounts(
  cdm,
  conceptId,
  countBy = c("record", "person"),
  concept = TRUE,
  interval = "overall",
  sex = FALSE,
  ageGroup = NULL,
  dateRange = NULL
)

Arguments

cdm	A cdm object
conceptId	List of concept IDs to summarise.
countBy	Either "record" for record-level counts or "person" for person-level counts
concept	TRUE or FALSE. If TRUE code use will be summarised by concept.
interval	Time interval to stratify by. It can either be "years", "quarters", "months" or "overall".
sex	TRUE or FALSE. If TRUE code use will be summarised by sex.
ageGroup	A list of ageGroup vectors of length two. Code use will be thus summarised by age groups.
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object with results overall and, if specified, by strata.

Examples

library(OmopSketch)

cdm <- mockOmopSketch()

cs <- list(sumatriptan = c(35604883, 35604879, 35604880, 35604884))

results <- summariseConceptCounts(cdm, conceptId = cs)

results

PatientProfiles::mockDisconnect(cdm)

---

Summarise the number of people in observation during a specific interval of time.

Description

Summarise the number of people in observation during a specific interval of time.

Usage

summariseInObservation(
  observationPeriod,
  interval = "overall",
  output = "records",
  ageGroup = NULL,
  sex = FALSE,
  dateRange = NULL
)

Arguments

observationPeriod	An observation_period omop table. It must be part of a cdm_reference object.
interval	Time interval to stratify by. It can either be "years", "quarters", "months" or "overall".
output	Output format. It can be either the number of records ("records") that are in observation in the specific interval of time, the number of person-days ("person-days"), or both c("records","person-days").
ageGroup	A list of age groups to stratify results by.
sex	Boolean variable. Whether to stratify by sex (TRUE) or not (FALSE).
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object.

Examples

library(dplyr, warn.conflicts = FALSE)

cdm <- mockOmopSketch()

result <- summariseInObservation(
  cdm$observation_period,
  interval = "months",
  output = c("person-days","records"),
  ageGroup = list("<=60" = c(0,60), ">60" = c(61, Inf)),
  sex = TRUE
)

result |>
  glimpse()

PatientProfiles::mockDisconnect(cdm)

---

Summarise missing data in omop tables

Description

Summarise missing data in omop tables

Usage

summariseMissingData(
  cdm,
  omopTableName,
  col = NULL,
  sex = FALSE,
  year = FALSE,
  ageGroup = NULL,
  sample = 1e+06,
  dateRange = NULL
)

Arguments

cdm	A cdm object
omopTableName	A character vector of the names of the tables to summarise in the cdm object.
col	A character vector of column names to check for missing values. If NULL, all columns in the specified tables are checked. Default is NULL.
sex	TRUE or FALSE. If TRUE code use will be summarised by sex.
year	TRUE or FALSE. If TRUE code use will be summarised by year.
ageGroup	A list of ageGroup vectors of length two. Code use will be thus summarised by age groups.
sample	An integer to sample the table to only that number of records. If NULL no sample is done.
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object with results overall and, if specified, by strata.

---

Summarise the observation period table getting some overall statistics in a summarised_result object.

Description

Summarise the observation period table getting some overall statistics in a summarised_result object.

Usage

summariseObservationPeriod(
  observationPeriod,
  estimates = c("mean", "sd", "min", "q05", "q25", "median", "q75", "q95", "max",
    "density"),
  ageGroup = NULL,
  sex = FALSE,
  dateRange = NULL
)

Arguments

observationPeriod	observation_period omop table.
estimates	Estimates to summarise the variables of interest ( ⁠records per person⁠, ⁠duration in days⁠ and ⁠days to next observation period⁠).
ageGroup	A list of age groups to stratify results by.
sex	Boolean variable. Whether to stratify by sex (TRUE) or not (FALSE).
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object with the summarised data.

Examples

library(dplyr, warn.conflicts = FALSE)

cdm <- mockOmopSketch(numberIndividuals = 100)

result <- summariseObservationPeriod(cdm$observation_period)

result |>
  glimpse()

PatientProfiles::mockDisconnect(cdm)

---

Summarise a cdm_reference object creating a snapshot with the metadata of the cdm_reference object.

Description

Summarise a cdm_reference object creating a snapshot with the metadata of the cdm_reference object.

Usage

summariseOmopSnapshot(cdm)

Arguments

cdm	A cdm_reference object.

Value

A summarised_result object.

Examples

cdm <- mockOmopSketch(numberIndividuals = 10)

summariseOmopSnapshot(cdm)

---

Summarise record counts of an omop_table using a specific time interval. Only records that fall within the observation period are considered.

Description

Summarise record counts of an omop_table using a specific time interval. Only records that fall within the observation period are considered.

Usage

summariseRecordCount(
  cdm,
  omopTableName,
  interval = "overall",
  ageGroup = NULL,
  sex = FALSE,
  dateRange = NULL
)

Arguments

cdm	A cdm_reference object.
omopTableName	A character vector of omop tables from the cdm.
interval	Time interval to stratify by. It can either be "years", "quarters", "months" or "overall".
ageGroup	A list of age groups to stratify results by.
sex	Whether to stratify by sex (TRUE) or not (FALSE).
dateRange	A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object.

Examples

library(dplyr, warn.conflicts = FALSE)

cdm <- mockOmopSketch()

summarisedResult <- summariseRecordCount(
  cdm = cdm,
  omopTableName = c("condition_occurrence", "drug_exposure"),
  interval = "years",
  ageGroup = list("<=20" = c(0,20), ">20" = c(21, Inf)),
  sex = TRUE
)

summarisedResult |>
  glimpse()

PatientProfiles::mockDisconnect(cdm = cdm)

---

Create a visual table from a summariseAllConceptCounts() result.

Description

Create a visual table from a summariseAllConceptCounts() result.

Usage

tableAllConceptCounts(result, type = "gt")

Arguments

result	A summarised_result object.
type	Type of formatting output table, either "gt" or "flextable".

Value

A gt or flextable object with the summarised data.

---

Create a visual table from a summariseClinicalRecord() output.

Description

Create a visual table from a summariseClinicalRecord() output.

Usage

tableClinicalRecords(result, type = "gt")

Arguments

result	Output from summariseClinicalRecords().
type	Type of formatting output table, either "gt" or "flextable".

Value

A gt or flextable object with the summarised data.

Examples

cdm <- mockOmopSketch()

summarisedResult <- summariseClinicalRecords(
  cdm = cdm,
  omopTableName = c("condition_occurrence", "drug_exposure"),
  recordsPerPerson = c("mean", "sd"),
  inObservation = TRUE,
  standardConcept = TRUE,
  sourceVocabulary = TRUE,
  domainId = TRUE,
  typeConcept = TRUE
)

summarisedResult |>
  suppress(minCellCount = 5) |>
  tableClinicalRecords()

PatientProfiles::mockDisconnect(cdm)

---

Create a visual table from a summariseMissingData() result.

Description

Create a visual table from a summariseMissingData() result.

Usage

tableMissingData(result, type = "gt")

Arguments

result	A summarised_result object.
type	Type of formatting output table, either "gt" or "flextable".

Value

A gt or flextable object with the summarised data.

---

Create a visual table from a summariseObservationPeriod() result.

Description

Create a visual table from a summariseObservationPeriod() result.

Usage

tableObservationPeriod(result, type = "gt")

Arguments

result	A summarised_result object.
type	Type of formatting output table, either "gt" or "flextable".

Value

A gt or flextable object with the summarised data.

Examples

cdm <- mockOmopSketch(numberIndividuals = 100)

result <- summariseObservationPeriod(cdm$observation_period)

tableObservationPeriod(result)

PatientProfiles::mockDisconnect(cdm)

---

Create a visual table from a summarise_omop_snapshot result.

Description

Create a visual table from a summarise_omop_snapshot result.

Usage

tableOmopSnapshot(result, type = "gt")

Arguments

result	Output from summariseOmopSnapshot().
type	Type of formatting output table, either "gt" or "flextable".

Value

A gt or flextable object with the summarised data.

Examples

cdm <- mockOmopSketch(numberIndividuals = 10)

result <- summariseOmopSnapshot(cdm)

result |>
  tableOmopSnapshot()

PatientProfiles::mockDisconnect(cdm)

---