{
  "abstract": "In claims databases, facility identifiers are often removed during de-identification, leaving only coarse attributes such as bed size. Yet facility information is needed for variance estimation, confounding adjustment and assessment of treatment availability. We examined whether accreditation-gated billing items can build strata standing for hospitals, and how to construct a facility proxy for each use. In 1,730,736 adults undergoing surgery (Medical Data Vision database, Japan, 2019-2023), we built marker-pattern strata from 66 accreditation-gated receipt codes (markers) and evaluated each grouping against a true facility identifier in an insurer-based database (DeSC Healthcare) and in simulation. The variance explained by the marker-pattern strata decreased with the extent to which a variable was patient- rather than hospital-determined ($R^2$ 0.921 for an accreditation item, 0.036 for sex). For variance estimation, the supplied-attribute cells, which can merge but never split hospitals, kept the type I error rate at 4.8% with a wild cluster bootstrap, against 5.4% for the true identifier and 39% when clustering was ignored; every finer marker-based grouping did worse. For adjustment, evaluated with real facility-level confounders and simulated null exposures, the marker pattern removed 51% of the confounding related to accreditation-linked facility characteristics, against 8% for the cells. The proportion of patients in groups mixing hospitals with and without the relevant accreditation was 49% for the marker pattern against 98% for the cells. No single facility proxy serves every purpose: nesting governs variance estimation, and resolution governs adjustment and treatment availability. Without a facility identifier, the supplied-attribute cells can carry the standard errors, and marker-pattern strata are worth considering for the other two uses.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.24679",
  "author_total": 7,
  "authors": [
    {
      "name": "Yuta Nonomiya"
    },
    {
      "name": "Tomoka Matsuura"
    },
    {
      "name": "Ryota Kawai"
    },
    {
      "name": "Andreas Dengel"
    },
    {
      "name": "Koichi Kise"
    },
    {
      "name": "Wakaba Fukushima"
    },
    {
      "name": "Ayumi Shintani"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/02p8fygmxhajd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.24679",
  "fulltext_url": null,
  "id": "02p8fygmxhajd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.24679",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "3605|Medical Coding and Health Information"
    ]
  ],
  "openalex": "W7223047303",
  "pdf_url": "https://arxiv.org/pdf/2610.24679",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-17",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/02p8fygmxhajd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:33:54Z",
      "native_id": "2610.24679",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.24679"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Nesting or resolution? Facility proxies for variance estimation versus confounding adjustment in claims data without facility identifiers",
  "title_text": "Nesting or resolution? Facility proxies for variance estimation versus confounding adjustment in claims data without facility identifiers",
  "type": "preprint",
  "updated_at": "2026-11-09T00:20:32Z",
  "url": "https://research.draconitic.com/paper/02p8fygmxhajd",
  "venue": "arXiv",
  "versions": []
}