{
  "abstract": "Background: Fragmented cardiovascular (CV) data abstraction across Allegheny Health Network led to inconsistent data quality, resource inefficiencies, and limited real-time insights, impeding patient care and strategic decision-making.\n\nProject Rationale: To address these challenges, Allegheny Health Network initiated a project to centralize CV registry abstraction, aiming to standardize processes, improve data integrity, enhance operational efficiency, and provide timely, actionable insights to clinicians.\n\nProject Summary: A current state assessment identified 8 CV registries and 11.5 full-time equivalents primarily engaged in abstraction across 5 facilities. A new corporate department was established, a dedicated manager and coordinator hired, nonabstraction tasks reallocated, and standardized workflows implemented. This led to significant reductions in abstraction time, improved accuracy, and enhanced reporting.\n\nTake-Home Messages: Centralized data abstraction drives significant efficiency gains, improves data quality, and empowers clinical and strategic decision-making in complex healthcare networks.",
  "abstract_shown": true,
  "affiliations": [
    "Quality, Analytics and Reporting Department, Allegheny Health Network, Pittsburgh, Pennsylvania, USA"
  ],
  "article_type": "case report",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Sheila B. Nichols"
    },
    {
      "affs": [
        0
      ],
      "name": "Gwynlynn Weil"
    },
    {
      "affs": [
        0
      ],
      "name": "Barbara Sanders"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5mbhj6qw6jwqr.bib",
  "cited_by": 0,
  "doi": "10.1016/j.jaccas.2026.109413",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13728241/",
  "id": "5mbhj6qw6jwqr",
  "issns": [
    "2666-0849"
  ],
  "landing_url": "https://doi.org/10.1016/j.jaccas.2026.109413",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Outcomes and Quality"
    ],
    [
      "heading",
      "Quality Improvement Projects"
    ],
    [
      "openalex",
      "3605|Electronic Health Records Systems"
    ]
  ],
  "openalex": "W7213414420",
  "pdf_url": "https://www.jacc.org/doi/pdf/10.1016/j.jaccas.2026.109413?download=true",
  "pmcid": "PMC13728241",
  "pmid": "42752026",
  "published": "2026-09-16",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/5mbhj6qw6jwqr.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T12:23:57Z",
      "native_id": "PMC13728241",
      "source": "pmc",
      "url": "https://doi.org/10.1016/j.jaccas.2026.109413"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "journal-openalex:2705|Cardiac Valve Diseases and Treatments",
      "subfield": "cardiovascular"
    }
  ],
  "title": "Cardiovascular Data Abstraction Centralization",
  "title_text": "Cardiovascular Data Abstraction Centralization",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T12:21:16Z",
  "url": "https://research.draconitic.com/paper/5mbhj6qw6jwqr",
  "venue": "JACC Case Reports",
  "versions": []
}