OmopSketch

Provides comprehensive database characterization and quality assessment for OMOP CDM databases.

Database Overview Functions

Snapshot Analysis:

• summariseOmopSnapshot(cdm) - Generate real-time database overview including vocabulary version, table sizes, observation period span
• tableOmopSnapshot(result, type) - Format snapshot results into tables

Observation Period Analysis

Temporal Analysis:

• summariseObservationPeriod(observationPeriod, sex) - Analyze observation period characteristics including records per person, duration, gaps
• summariseInObservation(observationPeriod, interval, output, ageGroup) - Track trends over time intervals (years, quarters, months)
• plotObservationPeriod(result, plotType, variableName, colour) - Visualize observation period statistics
• plotInObservation(result, colour, facet) - Plot temporal trends

Clinical Table Analysis

Quality Assessment:

• summariseMissingData(cdm, omopTableName, col, sample) - Analyze missing data patterns and zero concept IDs
• summariseClinicalRecords(cdm, omopTableName, recordsPerPerson, inObservation, standardConcept, sourceVocabulary, domainId, typeConcept) - Comprehensive clinical table characterization
• summariseRecordCount(cdm, omopTableName, interval, dateRange) - Analyze record trends over time

Concept Analysis:

• summariseConceptIdCounts(cdm, omopTableName, countBy) - Count records and subjects per concept ID
• tableConceptIdCounts(result, display, type) - Interactive tables of concept counts
• tableTopConceptCounts(result, countBy, top, type) - Display most frequent concepts

Integrated Database Characterization

Comprehensive Analysis:

• databaseCharacteristics(cdm, omopTableName, sex, ageGroup, interval, dateRange, conceptIdCounts) - Complete database characterization combining all analysis types
• shinyCharacteristics(result, directory) - Create interactive Shiny application for exploring results