Literature DB >> 21485667

Empirical aspects of linking intensive care registry data to hospital discharge data without the use of direct patient identifiers.

M A Bohensky1, D Jolley, V Sundararajan, D V Pilcher, S Evans, C A Brand.   

Abstract

In the field of intensive care, clinical data registries are commonly used to support clinical audit and develop evidence-based practice. However, they are often restricted to the intensive care unit episode only, limiting their ability to follow long-term patient outcomes and identify patient readmissions. Data linkage can be used to supplement existing data, but a lack of unique patient identifiers may compromise the accuracy of the linkage process. The aim of this study was to assess the quality of linking the Australia/New Zealand critical care registry to a state financial claims database using a method without direct patient identifiers and to identify possible sources of bias from this method. We used a linkage method relying on indirect patient identifiers and compared the accuracy of this method to one that also included the patient medical record number and date of birth. The overall linkage rate using the method with indirect identifiers was 92.3% compared to 94.5% using the method with direct identifiers. Factors most strongly associated with not being a correct link in the first method included patients at one study hospital, admissions in 2002 and 2003 and having a hospital length of stay of 20 days or more. Linking the Australia/New Zealand critical care without direct patient identifiers is a valid linkage method that will enable the measurement of long-term patient survival and readmissions. While some sources of bias have been identified, this method provides sufficient quality linkage that will support broad analyses designed to signal future in-depth research.

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Mesh:

Year:  2011        PMID: 21485667     DOI: 10.1177/0310057X1103900208

Source DB:  PubMed          Journal:  Anaesth Intensive Care        ISSN: 0310-057X            Impact factor:   1.669


  3 in total

1.  Linkage of Australian national registry data using a statistical linkage key.

Authors:  Tim G Coulson; Michael Bailey; Chris Reid; Gil Shardey; Jenni Williams-Spence; Sue Huckson; Shaila Chavan; David Pilcher
Journal:  BMC Med Inform Decis Mak       Date:  2021-02-02       Impact factor: 2.796

2.  Assessing Hepatitis C Burden and Treatment Effectiveness through the British Columbia Hepatitis Testers Cohort (BC-HTC): Design and Characteristics of Linked and Unlinked Participants.

Authors:  Naveed Zafar Janjua; Margot Kuo; Mei Chong; Amanda Yu; Maria Alvarez; Darrel Cook; Rosemary Armour; Ciaran Aiken; Karen Li; Seyed Ali Mussavi Rizi; Ryan Woods; David Godfrey; Jason Wong; Mark Gilbert; Mark W Tyndall; Mel Krajden
Journal:  PLoS One       Date:  2016-03-08       Impact factor: 3.240

3.  Internal deterministic record linkage using indirect identifiers for matching of same-patient hospital transfers and early readmissions after acute coronary syndrome in a nationwide hospital discharge database: a retrospective observational validation study.

Authors:  Afonso Rocha; Luıs Filipe Azevedo; J C Silva Cardoso; Thomas G Allison; Alberto Freitas
Journal:  BMJ Open       Date:  2019-12-30       Impact factor: 2.692

  3 in total

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