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Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE

Maximising the value of hospital administrative datasets

Shyamala G. Nadathur
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Department of Medicine, Monash Medical Centre, Monash University, Clayton, VIC 3168, Australia. Email: shyamala.nadathur@med.monash.edu.au

Australian Health Review 34(2) 216-223 https://doi.org/10.1071/AH09801
Submitted: 1 July 2009  Accepted: 25 November 2009   Published: 25 May 2010

Abstract

Mandatory and standardised administrative data collections are prevalent in the largely public-funded acute sector. In these systems the data collections are used for financial, performance monitoring and reporting purposes. This paper comments on the infrastructure and standards that have been established to support data collection activities, audit and feedback. The routine, local and research uses of these datasets are described using examples from Australian and international literature. The advantages of hospital administrative datasets and opportunities for improvement are discussed under the following headings: accessibility, standardisation, coverage, completeness, cost of obtaining clinical data, recorded Diagnostic Related Groups and International Classification of Diseases codes, linkage and connectivity. In an era of diminishing resources better utilisation of these datasets should be encouraged. Increased study and scrutiny will enhance transparency and help identify issues in the collections. As electronic information systems are increasingly embraced, administrative data collections need to be managed as valuable assets and powerful operational and patient management tools.

Additional keywords: administrative data; casemix; data collection; health care quality, access, and evaluation; health services administration; health services research; hospital administration; hospital information systems; information management; information storage and retrieval; morbidity; mortality; patient care.


Acknowledgements

This paper and the expressed ideas form part of the doctorate thesis of the author at Monash University. The author is grateful to Professor Jim Warren (Chair in Health Informatics, University of Auckland, New Zealand) for the critical review of this paper.


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