Evidence map›Paper›PMID 23349080›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2013

Federated queries of clinical data repositories: the sum of the parts does not equal the whole.

Griffin M Weber

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Fold-stratified cross-validation for unbiased and privacy-preserving federated learning.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Query Health: standards-based, cross-platform population health surveillance.Journal of the American Medical Informatics Association : JAMIA
    Article
  12. Changing the research landscape: the New York City Clinical Data Research Network.Journal of the American Medical Informatics Association : JAMIA
    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

1 author.

Griffin M WeberInformation Technology, Harvard Medical School, Boston, Massachusetts 02115, USA. weber@hms.harvard.edu

Funding

Informatics for Integrating Biology/ the Bedside (RMI)U54LM008748 · NLM · BRIGHAM AND WOMEN'S HOSPITAL · PI KOHANE, ISAAC S. · 2004 to 2013
$39.0M
Harvard Clinical and Translational Science Center (UL1)UL1TR000170 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2012 to 2013
$31.4M
NCATS NIH HHS 8UL1TR000170-05NCATS NIH HHS UL1 TR000170NLM NIH HHS 2U54LM008748NLM NIH HHS U54 LM008748
6 · The paper itself

Abstract

BACKGROUND AND

objectiveIn 2008 we developed a shared health research information network (SHRINE), which for the first time enabled research queries across the full patient populations of four Boston hospitals. It uses a federated architecture, where each hospital returns only the aggregate count of the number of patients who match a query. This allows hospitals to retain control over their local databases and comply with federal and state privacy laws. However, because patients may receive care from multiple hospitals, the result of a federated query might differ from what the result would be if the query were run against a single central repository. This paper describes the situations when this happens and presents a technique for correcting these errors.

methodsWe use a one-time process of identifying which patients have data in multiple repositories by comparing one-way hash values of patient demographics. This enables us to partition the local databases such that all patients within a given partition have data at the same subset of hospitals. Federated queries are then run separately on each partition independently, and the combined results are presented to the user.

resultsUsing theoretical bounds and simulated hospital networks, we demonstrate that once the partitions are made, SHRINE can produce more precise estimates of the number of patients matching a query.

conclusionsUncertainty in the overlap of patient populations across hospitals limits the effectiveness of SHRINE and other federated query tools. Our technique reduces this uncertainty while retaining an aggregate federated architecture.

Indexed as

Computer Communication NetworksInformation Storage and RetrievalMedical Records Systems, ComputerizedBostonDatabases, FactualHospital AdministrationHumansMedical Record LinkageAlgorithmsHospital Shared ServicesMedical Record LinkageMedical Records Systems, ComputerizedSearch Engine

Identifiers

PMID23349080
PMCPMC3715334

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.