Package: rwevalidate 0.1.2

Hamid Tavakoli

rwevalidate: Validate Patient Cohorts for Real-World Evidence Studies on the OMOP Common Data Model

Validates instantiated patient cohorts on an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) database for real-world-evidence (RWE) studies. From a single function call it produces a structured validation report in Hypertext Markup Language (HTML) and JavaScript Object Notation (JSON) covering concept coverage, cohort attrition, temporal data density, and covariate feasibility against a comparator. The checks are aligned with the United States Food and Drug Administration (FDA) guidance on real-world data and evidence, FDA (2023) <https://www.fda.gov/media/171667/download>, the Harmonized Protocol Template to Enhance Reproducibility (HARPER), Wang and others (2022) <doi:10.1002/pds.5507>, and the Reporting of Studies Conducted Using Observational Routinely-Collected Data for Pharmacoepidemiology (RECORD-PE) statement, Langan and others (2018) <doi:10.1136/bmj.k3532>. A self-contained example database is bundled so the checks can be run without a live database connection.

Authors:Hamid Tavakoli [aut, cre]

rwevalidate_0.1.2.tar.gz
rwevalidate_0.1.2.tar.gz(r-4.7-any)rwevalidate_0.1.2.tar.gz(r-4.6-any)
rwevalidate_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
rwevalidate/json (API)

# Install 'rwevalidate' in R:
install.packages('rwevalidate', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tavakohr/rwevalidate/issues

On CRAN:

Conda:

3.00 score 12 exports 39 dependencies

Last updated from:89d2467f2e. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK153
source / vignettesOK189
linux-release-x86_64OK152
wasm-releaseOK133

Exports:build_check_summarycdm_connectcdm_disconnectclassify_statusexample_cdmrender_validation_reportrun_attritionrun_conceptsrun_covariatesrun_densityvalidate_cohortwrite_results_json

Dependencies:base64encbitbit64blobbslibcachemclicpp11DBIdigestevaluatefastmapfontawesomefsgenericsgluehighrhmshtmltoolsjquerylibjsonliteknitrlifecyclelubridatememoisemimepkgconfigR6rappdirsrlangrmarkdownRPostgressasstimechangetinytexvctrswithrxfunyaml

Getting started with rwevalidate
Try it without a database | 1. Connect | 2. Instantiate a cohort (upstream) | 3. Validate in one call | 4. Run modules individually | 5. Interpreting the traffic light

Last update: 2026-07-21
Started: 2026-07-21

Validation: cohorts, datasets, and methodology
Datasets | Tier 1 - domain battery (100-patient CDM) | Tier 2 - gold-standard OHDSI phenotypes (5,000-patient CDM) | Tier 3 - independent synthetic source (Eunomia) | Reproducing the validation | 1. Connect (split-schema) | 2. Derive observation_period (if absent) | 3. Instantiate a cohort (OHDSI concept-set method) | 4. Seeds used (replicable) | 5. Validate | Machine-readable results

Last update: 2026-07-21
Started: 2026-07-21