Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers. (18th December 2014)

• Record Type: Journal Article
• Authors: Hagger‐Johnson, Gareth; Harron, Katie; Gonzalez‐Izquierdo, Arturo; Cortina‐Borja, Mario; Dattani, Nirupa; Muller‐Pebody, Berit; Parslow, Roger; Gilbert, Ruth; Goldstein, Harvey
• Is Part Of: Health services research. Volume 50:Number 4(2015)
• Page Start: 1162
• Page End: 1178
• Publication Date: 2014-12-18
• Subjects: Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12272
• Languages: English
• ISSNs: 0017-9124

Abstract

<abstract abstract-type="main" id="hesr12272-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="hesr12272-sec-0001" sec-type="section"> <title>Objective</title> <p>To identify data linkage errors in the form of possible false matches, where two patients appear to share the same unique identification number.</p> </sec> <sec id="hesr12272-sec-0002" sec-type="section"> <title>Data Source</title> <p>Hospital Episode Statistics (HES) in England, United Kingdom.</p> </sec> <sec id="hesr12272-sec-0003" sec-type="section"> <title>Study Design</title> <p>Data on births and re‐admissions for infants (April 1, 2011 to March 31, 2012; age 0–1 year) and adolescents (April 1, 2004 to March 31, 2011; age 10–19 years).</p> </sec> <sec id="hesr12272-sec-0004" sec-type="section"> <title>Data Collection/Extraction Methods</title> <p>Hospital records pseudo‐anonymized using an algorithm designed to link multiple records belonging to the same person. Six implausible clinical scenarios were considered possible false matches: multiple births sharing HESID, re‐admission after death, two birth episodes sharing HESID, simultaneous admission at different hospitals, infant episodes coded as deliveries, and adolescent episodes coded as births.</p> </sec> <sec id="hesr12272-sec-0005" sec-type="section"> <title>Principal Findings</title> <p>Among 507, 778 infants, possible false matches were relatively rare (<italic>n</italic> = 433, 0.1 percent). The most common scenario (simultaneous admission at two hospitals, <italic>n</italic> = 324) was more likely for infants with missing data, those born preterm, and for Asian infants. Among adolescents, this scenario (<italic>n</italic> = 320) was more common for males, younger patients, the Mixed ethnic group, and those re‐admitted more frequently.</p> </sec> <sec id="hesr12272-sec-0006" sec-type="section"> <title>Conclusions</title> <p>Researchers can identify clinically implausible scenarios and patients affected, at the data cleaning stage, to mitigate the impact of possible linkage errors.</p> </sec> </abstract>