ArticleScientific data2018
Columbia Open Health Data, clinical concept prevalence and co-occurrence from electronic health records.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.Acta neurochirurgica. Supplement · 2022Pooled it
- Implications of Data Extraction and Processing of Electronic Health Records for Epidemiological Research: Observational Study.Journal of medical Internet research · 2025Observational
- Identifying Phenotypes for Earlier Diagnosis of Rare Diseases.Studies in health technology and informatics · 2025Article
- Causal relationship between Parkinson's disease and gastric cancer: a Mendelian randomization study.BMC neurology · 2025Article
- On the Readiness of Scientific Data Papers for a Fair and Transparent Use in Machine Learning.Scientific data · 2025Article
- Generating Biomedical Knowledge Graphs from Knowledge Bases, Registries, and Multiomic Data.bioRxiv : the preprint server for biology · 2024Article
- Acute kidney injury comorbidity analysis based on international classification of diseases-10 codes.BMC medical informatics and decision making · 2024Article
- ARAX: a graph-based modular reasoning tool for translational biomedicine.Bioinformatics (Oxford, England) · 2023Article
- OARD: Open annotations for rare diseases and their phenotypes based on real-world data.American journal of human genetics · 2022Article
- Pneumonia and Related Conditions in Critically Ill Patients-Insights from Basic and Experimental Studies.International journal of molecular sciences · 2022Article
- Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: Asthma Use Case.JMIR formative research · 2022Article
- Big Data in Nephrology.Nature reviews. Nephrology · 2021Review
- Columbia Open Health Data for COVID-19 Research: Database Analysis.Journal of medical Internet research · 2021Article
- An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication.Nature cancer · 2021Article
- Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.PLoS computational biology · 2021Article
- PhenCards: a data resource linking human phenotype information to biomedical knowledge.Genome medicine · 2021Article
- Comparative effectiveness of medical concept embedding for feature engineering in phenotyping.JAMIA open · 2021Article
- Gene expression barcode values reveal a potential link between Parkinson's disease and gastric cancer.Aging · 2021Article
- Renin-angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis.The Lancet. Digital health · 2021Article
- Statistical Enrichment Analysis of Samples: A General-Purpose Tool to Annotate Metadata Neighborhoods of Biological Samples.Frontiers in big data · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Columbia Open Health Data (COHD) is a publicly accessible database of electronic health record (EHR) prevalence and co-occurrence frequencies between conditions, drugs, procedures, and demographics. COHD was derived from Columbia University Irving Medical Center's Observational Health Data Sciences and Informatics (OHDSI) database. The lifetime dataset, derived from all records, contains 36,578 single concepts (11,952 conditions, 12,334 drugs, and 10,816 procedures) and 32,788,901 concept pairs from 5,364,781 patients. The 5-year dataset, derived from records from 2013-2017, contains 29,964 single concepts (10,159 conditions, 10,264 drugs, and 8,270 procedures) and 15,927,195 concept pairs from 1,790,431 patients. Exclusion of rare concepts (count ≤ 10) and Poisson randomization enable data sharing by eliminating risks to patient privacy. EHR prevalences are informative of healthcare consumption rates. Analysis of co-occurrence frequencies via relative frequency analysis and observed-expected frequency ratio are informative of associations between clinical concepts, useful for biomedical research tasks such as drug repurposing and pharmacovigilance. COHD is publicly accessible through a web application-programming interface (API) and downloadable from the Figshare repository. The code is available on GitHub.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.