Background: Linkage 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.
Methods: Linkage 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.
Results: Compared 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.
Conclusions: Hospitalisation 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.
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http://dx.doi.org/10.1186/1472-6947-14-85 | DOI Listing |
Children (Basel)
December 2022
Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, VIC 3052, Australia.
Linking very large, consented birth cohorts to birthing hospitals clinical data could elucidate the lifecourse outcomes of health care and exposures during the pregnancy, birth and newborn periods. Unfortunately, cohort personally identifiable information (PII) often does not include unique identifier numbers, presenting matching challenges. To develop optimized cohort matching to birthing hospital clinical records, this pilot drew on a one-year (December 2020-December 2021) cohort for a single Australian birthing hospital participating in the whole-of-state Generation Victoria (GenV) study.
View Article and Find Full Text PDFMed J Aust
February 2023
Centre for Outcome and Resource Evaluation (CORE), Australian and New Zealand Intensive Care Society (ANZICS), Melbourne, VIC.
Objective: To compare longer term (12-month) mortality outcomes for Indigenous and non-Indigenous people admitted to intensive care units (ICUs) in Australia.
Design, Setting, Participants: Retrospective registry-based data linkage cohort study; analysis of all admissions of adults (16 years or older) to Australian ICUs, 1 January 2017 - 31 December 2019, as recorded in the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database (APD), linked using the SLK-581 key to National Death Index data.
Main Outcome Measures: Unadjusted and adjusted mortality risk, censored at twelve months from the start of index ICU admission.
BMC Med Inform Decis Mak
February 2021
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.
Background: Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581).
View Article and Find Full Text PDFHealth Inf Manag
August 2016
Centre for Population Health Research, Curtin University, Australia.
Background: The statistical linkage key (SLK-581) is a common tool for record linkage in Australia, due to its ability to provide some privacy protection. However, newer privacy-preserving approaches may provide greater privacy protection, while allowing high-quality linkage.
Objective: To evaluate the standard SLK-581, encrypted SLK-581 and a newer privacy-preserving approach using Bloom filters, in terms of both privacy and linkage quality.
BMC Med Inform Decis Mak
September 2014
Centre for Epidemiology and Evidence, NSW Ministry of Health, Sydney, Australia.
Background: Linkage 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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!