Evidence map›Paper›PMID 25257549›Full record

ArticleBMC medical informatics and decision making2014

Optimal strategy for linkage of datasets containing a statistical linkage key and datasets with full personal identifiers.

Lee K Taylor, Katie Irvine, Renee Iannotti, Taylor Harchak, Kim Lim

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Linkability measures to assess the data characteristics for record linkage.Journal of the American Medical Informatics Association : JAMIA · 2024
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Lee K TaylorCentre for Epidemiology and Evidence, NSW Ministry of Health, Sydney, Australia. ltayl@doh.health.nsw.gov.au.
Katie Irvine
Renee Iannotti
Taylor Harchak
Kim Lim

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLinkage of aged care and hospitalisation data provides valuable information on patterns of health service utilisation among aged care service recipients. Many aged care datasets in Australia contain a Statistical Linkage Key (SLK-581) instead of full personal identifiers. We linked hospital and death records using a full probabilistic strategy, the SLK-581, and three combined strategies; and compared results for each strategy.

methodsLinkage of Admitted Patient Data for 2000-01 to 2008-09 and Registry of Births, Deaths and Marriages death registration data for 2008-09 for New South Wales, Australia, was carried out using probabilistic methods and compared to links created using four strategies incorporating a SLK-581. The Basic SLK-581 strategy used the SLK-581 alone. The Most Recent SLK-581, Most Frequent SLK-581, and Any Match SLK-581 strategies leveraged probabilistic links between hospital records drawn from the Centre for Health Record Linkage Master Linkage Key. Rates of hospitalisations among people who died were calculated for each strategy and a range of health conditions.

resultsCompared to full probabilistic linkage, the basic SLK-581 strategy produced substantial rates of missed links that increased over the study period and produced underestimates of hospitalisation rates that varied by health condition. The Most Recent SLK-581, Most Frequent SLK-581, and Any Match SLK-581 strategies resulted in substantially lower rates of underestimation than the Basic SLK-581. The Any Match SLK-581 strategy gave results closest to full probabilistic linkage.

conclusionsHospitalisation rates prior to death are substantially underestimated by linkage using a SLK-581 alone. Linkage rates can be increased by combining deterministic methods with probabilistically created links across hospital records.

Indexed as

HumansMedical Record LinkageMedical Records Systems, ComputerizedNew South WalesRegistries

Identifiers

PMID25257549
PMCPMC4236530

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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.