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.

Highlights

  • Linkage of aged care and hospitalisation data provides valuable information on patterns of health service utilisation among aged care service recipients

  • The Home and Community Care (HACC) Program, an Australian Government initiative, provides essential community care and support services to enable people who are frail or disabled and at risk of long-term residential care to remain in the community

  • The aims of this study were to: examine the quality of statistical linkage key (SLK)-581 derived for Admitted Patient Data (APD) data; determine the optimal strategy to be used when linking datasets containing an SLK-581 with datasets containing full personal identifiers; and quantify the extent to which the recommended optimal strategy biases estimates of hospitalisation rates among HACC clients for a range of health priority areas

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Summary

Introduction

Linkage of aged care and hospitalisation data provides valuable information on patterns of health service utilisation among aged care service recipients. Linkage of data collected from hospital and aged care services has been used to assess aged care service utilisation [1] and mortality [2] of clients of aged care services in Australia. Information derived from these linked data is essential for policy development and planning to deliver high quality care for older Australians. The HACC Minimum Data Set (MDS) is a person based dataset containing information about clients receiving services by HACC providers and the level and type of services the clients receive. The HACC MDS contains a nationally agreed set of data items collected by all HACC service providers for each of their clients [4]

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