{
  "abstract": "BackgroundEpic Cosmos is a relatively new centralized dataset of electronic health records, largely in the U.S., with high potential utility in perinatal epidemiologic research.\n\nObjectivesThe study objectives were to develop replicable steps to create longitudinal, linked maternal-infant cohorts in Cosmos, assess completeness of key variables, evaluate potential selection bias with restrictions for longitudinal healthcare encounters, and provide an example epidemiologic analysis.\n\nMethodsWe created maternal-infant cohorts by starting with infants born during 2023-2024 and joining with additional data tables as needed. We selected and created variables for perinatal characteristics, common comorbidities, and routinely measured vital signs and laboratory values, and assessed variable completeness. We sequentially restricted the birth cohort for maternal-infant linkage and longitudinal healthcare from first-trimester prenatal care encounter through infant follow-up care within 12 weeks post-discharge from birth hospitalization. Finally, we conducted an example analysis of the association between high systolic blood pressure in the first trimester ([≥]140 mm Hg) and later onset of preeclampsia among those with chronic hypertension.\n\nResultsThe total linked birth cohort included 2,929,600 pregnancies. Completeness was >90% for most variables assessed but was 76% for racial and ethnic group and 77% for body mass index at delivery. Characteristics of the cohort were similar to those reported for the entire United States birth population based on birth certificate data, including similar regional and racial-ethnic composition. Longitudinal cohort restriction requiring linked records from first trimester prenatal care through infant follow-up care reduced the cohort size to 586,841 pregnancies. However, restriction had minimal effects on cohort characteristics. In the example analysis, high systolic blood pressure was associated with increased risk of preeclampsia among those with chronic hypertension (aRR: 1.26; 95% CI: 1.23, 1.30).\n\nConclusionsThis study provides a rigorous and reproducible approach to creating longitudinal, linked maternal-infant cohorts in Epic Cosmos. The analytical findings suggest high data quality and representativeness of the U.S., while also drawing attention to dataset limitations that perinatal epidemiologic researchers should be aware of, notably attrition with longitudinal restrictions.\n\nSYNOPSIS* Study question: The study sought to develop replicable steps for researchers to create longitudinal, linked maternal-infant cohorts using the Epic Cosmos electronic health record (EHR) dataset, assess completeness of key variables, evaluate potential selection bias with sequential restrictions for longitudinal healthcare encounters, and provide an example analysis.\n\n* Whats already known: Epic Cosmos is a relatively new dataset with high potential for perinatal epidemiologic research because of its large size and granular information from structured EHR data.\n\n* What this study adds: This study provides a rigorous and reproducible approach to creating longitudinal, linked maternal-infant cohorts in Epic Cosmos and found overall high completeness of key variables, and high representativeness of the United States. Cohort characteristics did not meaningfully change with longitudinal cohort selection.",
  "abstract_shown": true,
  "affiliations": [
    "Stanford University"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "S. A. Leonard"
    },
    {
      "name": "K. Dysart"
    },
    {
      "name": "A. Callahan"
    },
    {
      "name": "S. Siadat"
    },
    {
      "name": "J. Zhang"
    },
    {
      "name": "S. C. Handley"
    },
    {
      "name": "K. F. Huybrechts"
    },
    {
      "name": "I. Igbinosa"
    },
    {
      "name": "B. T. Bateman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dve3xp521f6ym.bib",
  "cited_by": 1,
  "doi": "10.64898/2026.06.02.26354757",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.06.02.26354757v2.full",
  "id": "dve3xp521f6ym",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.06.02.26354757v2",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "epidemiology"
    ],
    [
      "openalex",
      "3600|Maternal and Neonatal Healthcare"
    ]
  ],
  "openalex": "W7163589884",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.06.02.26354757v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-06-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dve3xp521f6ym.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:27Z",
      "native_id": "10.64898/2026.06.02.26354757",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.06.02.26354757v2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:epidemiology",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Development of Longitudinal, Linked Maternal-Infant Cohorts using the Epic Cosmos Electronic Health Record Dataset",
  "title_text": "Development of Longitudinal, Linked Maternal-Infant Cohorts using the Epic Cosmos Electronic Health Record Dataset",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:27Z",
  "url": "https://research.draconitic.com/paper/dve3xp521f6ym",
  "venue": "medRxiv",
  "versions": []
}