The essential OMOP / OHDSI shelf.

Publications

Foundational reading

The methods shelf

A deeper set once you are ready, grouped by theme. You do not need all of these on day one, since the Book of OHDSI plus the founding vision paper is plenty to start.

Vision & community

• Book

  The Book of OHDSI

  The canonical reference for the CDM, vocabularies, and the full analytic workflow. Start here.

• Paper

  Hripcsak et al. (2015), OHDSI: Opportunities for Observational Researchers

  The founding statement of the collaborative and its goals.

Reliability and calibration

• Paper

  Schuemie et al. (2014), Why empirical calibration is needed to correct p-values

  Introduces empirical calibration against negative controls.

• Paper

  Schuemie et al. (2018), Empirical confidence interval calibration (PNAS)

  Extends calibration from p-values to confidence intervals using positive and negative controls.

• Paper

  Schuemie et al. (2020), How confident are we about observational findings? A benchmark study

  The OHDSI methods benchmark and reference-set thinking behind method evaluation.

Estimation, prediction & phenotypes

• Paper

  Suchard et al. (2019), Comparative effectiveness of antihypertensives (LEGEND-HTN, Lancet)

  Flagship demonstration of high-throughput, systematically calibrated network estimation.

• Paper

  Reps et al. (2018), Standardized patient-level prediction framework (JAMIA)

  The PLP framework for building and evaluating prediction models on observational data.

• Paper

  Swerdel et al. (2019), PheValuator

  Estimating phenotype sensitivity/specificity/PPV without chart review.

Data quality, privacy & SDoH

• Paper

  Kahn et al. (2016), Harmonized data quality assessment framework

  Conformance, completeness and plausibility crossed with verification and validation, which is the data-quality backbone.

• Paper

  Blacketer et al. (2021), Evaluating observational data quality

  The Kahn framework as executable checks, and the write-up behind the DataQualityDashboard.

• Paper

  Hripcsak et al. (2016), Preserving temporal relations while maintaining privacy

  The Shift-and-Truncate method for obscuring dates while preserving within-patient intervals.

• Paper

  Cook, Sachs & Weiskopf (2022), Quality of SDoH data in the EHR

  Applies DQ dimensions to social-determinants variables; plausibility is the top issue.

Search the whole corpus

• Search

  OHDSI Community Intelligence Platform

  Articles, videos, repositories, discussions, and documentation with relevance scoring. Try maternal, pregnancy, or pediatric.

Watch

Videos

• Channel

  OHDSI on YouTube

  Community calls, tutorials, and symposium talks.

• Channel

  Dr. Danielle the Data Diva

  Plain-language explainers of OMOP and observational research.

Featured maternal & child health talks from the OHDSI community, hand-picked rather than whatever is newest.