Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38258
Title: Investigating increased admissions to neonatal intensive care in England between 1995 and 2006: data linkage study using Hospital Episode Statistics
Authors: Morgan, Andrei S.
Marlow, Neil
Costeloe, Kate
Draper, Elizabeth S.
First Published: 20-May-2016
Publisher: BioMed Central
Citation: BMC Medical Research Methodology, 2016, 16:57
Abstract: BACKGROUND: A 44 % increase was observed in admissions to neonatal intensive care of babies born ≤26 weeks completed gestational age in England between 1995 and 2006. Hospital Episode Statistics (HES) may provide supplementary information to investigate this. The methods and results of a probabilistic data linkage exercise are reported. METHODS: Two data sets were linked for each year (1995 and 2006) using 3 different algorithms (Fellegi and Sunter, Contiero and estimation-maximisation). RESULTS: In 1995, linkage was performed between 668 EPICure and 486,705 HES records; 1,820 linked pairs were identified of which 422 (63.17 %) were confirmed. In 2006, from 2,750 EPICure and 631,401 HES records, 8,913 linked pairs were identified with 1,662 (60.40 %) confirmed as true. Reported births in HES at <26 weeks gestation increased 37.0 % from 867 to 1188. CONCLUSIONS: Results support the EPICure findings that there was an increase in the birth rate for extremely premature babies between 1995 and 2006. There were insufficient data available for detailed investigation. Routine data sources may not be suitable for investigations at the margins of viability.
DOI Link: 10.1186/s12874-016-0152-0
eISSN: 1471-2288
Links: http://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0152-0
http://hdl.handle.net/2381/38258
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2016. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Health Sciences



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