Package 'OmopSketch'

Title: Characterise Tables of an OMOP Common Data Model Instance
Description: Summarises key information in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Assess suitability to perform specific epidemiological studies and explore the different domains to obtain feasibility counts and trends.
Authors: Marta Alcalde-Herraiz [aut, cre] , Kim Lopez-Guell [aut] , Elin Rowlands [aut] , Edward Burn [aut] , Martí Català [aut]
Maintainer: Marta Alcalde-Herraiz <[email protected]>
License: Apache License (>= 2)
Version: 0.1.1
Built: 2024-10-21 14:19:00 UTC
Source: https://github.com/ohdsi/omopsketch

Help Index

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 = "codelist_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 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
)

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.

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
)

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.

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
)

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).

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 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
)

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).

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
)

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).

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 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 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)