Evidence map›Paper›PMID 21926112›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2012

Evaluation of record linkage between a large healthcare provider and the Utah Population Database.

Scott L DuVall, Alison M Fraser, Kerry Rowe, Alun Thomas, Geraldine P Mineau

Abstract readEvaluation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. GUILD: GUidance for Information about Linking Data sets.Journal of public health (Oxford, England) · 2018
    Guideline
  2. Trial
  3. Trial
  4. Familial Risk of Hashimoto's Thyroiditis in a Large Genealogical Database.The Journal of clinical endocrinology and metabolism · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Familial aggregation of stillbirth: A pedigree analysis of a matched case-control study.BJOG : an international journal of obstetrics and gynaecology · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  15. Fine Particulate Matter and Respiratory Healthcare Encounters among Survivors of Childhood Cancers.International journal of environmental research and public health · 2019
    Article
  16. A Method for Integrating Healthcare Provider Organization and Research Sponsor Systems and Workflows to Support Large-Scale Studies.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Scott L DuVallVA Salt Lake City Health Care System, Salt Lake City, Utah, USA.
Alison M Fraser
Kerry Rowe
Alun Thomas
Geraldine P Mineau

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Jared P Rutter · 1986 to 2026
$72.6M
UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
NCI NIH HHS HHSN261201000026CNCI NIH HHS P30 CA042014NCI NIH HHS P30 CA42014NLM NIH HHS LM007124-11NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

objectiveElectronically linked datasets have become an important part of clinical research. Information from multiple sources can be used to identify comorbid conditions and patient outcomes, measure use of healthcare services, and enrich demographic and clinical variables of interest. Innovative approaches for creating research infrastructure beyond a traditional data system are necessary. MATERIALS AND

methodsRecords from a large healthcare system's enterprise data warehouse (EDW) were linked to a statewide population database, and a master subject index was created. The authors evaluate the linkage, along with the impact of missing information in EDW records and the coverage of the population database. The makeup of the EDW and population database provides a subset of cancer records that exist in both resources, which allows a cancer-specific evaluation of the linkage.

resultsAbout 3.4 million records (60.8%) in the EDW were linked to the population database with a minimum accuracy of 96.3%. It was estimated that approximately 24.8% of target records were absent from the population database, which enabled the effect of the amount and type of information missing from a record on the linkage to be estimated. However, 99% of the records from the oncology data mart linked; they had fewer missing fields and this correlated positively with the number of patient visits. DISCUSSION AND

conclusionA general-purpose research infrastructure was created which allows disease-specific cohorts to be identified. The usefulness of creating an index between institutions is that it allows each institution to maintain control and confidentiality of their own information.

Indexed as

Databases, FactualMedical Record LinkageMedical Records Systems, ComputerizedAgedDelivery of Health CareDelivery of Health Care, IntegratedFemaleHumansMaleMiddle AgedNeoplasmsUniversitiesUtah

Identifiers

PMID21926112
PMCPMC3392872

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.