title: Growth of linked hospital data use in Australia: a systematic review.
abstract: Objective The aim of the present study was to quantify and understand the utilisation of linked hospital data for research purposes across Australia over the past two decades. Methods A systematic review was undertaken guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 checklist. Medline OVID, PsycINFO, Embase, EconLit and Scopus were searched to identify articles published from 1946 to December 2014. Information on publication year, state(s) involved, type of data linkage, disease area and purpose was extracted. Results The search identified 3314 articles, of which 606 were included; these generated 629 records of hospital data linkage use across all Australian states and territories. The major contributions were from Western Australia (WA; 51%) and New South Wales (NSW; 32%) with the remaining states and territories having significantly fewer publications (total contribution only 17%). WA's contribution resulted from a steady increase from the late 1990s, whereas NSW's contribution is mostly from a rapid increase from 2010. Current data linkage is primarily used in epidemiological research (73%). Conclusion More than 80% of publications were from WA and NSW, whereas other states significantly lag behind. The observable growth in these two states clearly demonstrates the underutilised opportunities for data linkage to add value in health services research in the other states. What is known about the topic? Linking administrative hospital data to other data has the potential to be a cost-effective method to significantly improve health policy. Over the past two decades, Australia has made significant investments in improving its data linkage capabilities. However, several articles have highlighted the many barriers involved in using linked hospital data. What does this paper add? This paper quantitatively evaluates the performance across all Australian states in terms of the use of their administrative hospital data for research purposes. The performance of states varies considerably, with WA and NSW the clear stand-out performers and limited outputs currently seen for the other Australian states and territories. What are the implications for practitioners? Given the significant investments made into data linkage, it is important to continue to evaluate and monitor the performance of the states in terms of translating this investment into outputs. Where the outputs do not match the investment, it is important to identify and overcome those barriers limiting the gains from this investment. More generally, there is a need to think about how we improve the effective and efficient use of data linkage investments in Australia.
authors.affiliation: The University of Melbourne, Centre for Health Policy, Melbourne School of Population and Global Health, Level 4, 207 Bouverie Street, Carlton, Vic. 3053, Australia. Email: ;
authors.forename: Michelle
authors.initials: M
authors.lastname: Tew
authors.affiliation: The University of Melbourne, Centre for Health Policy, Melbourne School of Population and Global Health, Level 4, 207 Bouverie Street, Carlton, Vic. 3053, Australia. Email: ;
authors.forename: Kim M
authors.initials: KM
authors.lastname: Dalziel
authors.affiliation: The University of Melbourne, Centre for Health Policy, Melbourne School of Population and Global Health, Level 4, 207 Bouverie Street, Carlton, Vic. 3053, Australia. Email: ;
authors.forename: Dennis J
authors.initials: DJ
authors.lastname: Petrie
authors.affiliation: The University of Melbourne, Centre for Health Policy, Melbourne School of Population and Global Health, Level 4, 207 Bouverie Street, Carlton, Vic. 3053, Australia. Email: ;
authors.forename: Philip M
authors.initials: PM
authors.lastname: Clarke
mesh_terms: D001315:Australia; D016208:Databases, Factual; D006739:Hospital Administration; D006753:Hospital Records; D006761:Hospitals; D006801:Humans; D016247:Information Storage and Retrieval; D008498:Medical Record Linkage / Q000379:methods; D000075403:Semantic Web