An earlier post highlighted several of the difficulties that Australian researchers face. One of the most prominent of these is related to accessing health and medical research (HMR) data. This is not due to a lack of data, or associated metadata directory such as AIHW’s Meteor, but rather due to a lack of transparency around the custodianship of the many health datasets that exist and the conditions under which they can be used for research. Much of this stems from the fact that a large number of agencies and entities play different roles in the management of HMR data.
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Released in February 2013, the McKeon Review marked the most comprehensive analysis of the health and medical research (HMR) sector since the Wills Review in 1998. McKeon’s words highlight one of the panel’s most alarming takeaways. At the end of the review period, despite the “combined insights of thousands of individuals who contributed their ideas and time”, meeting with “over 300 individuals from universities, MRIs, governments, hospitals, businesses and not-for-profit organisations” and receiving 400 written submissions, the panel were not able to make a confident assessment of total HMR spending.
One would think that the process of obtaining data to conduct health and medical research in Australia would be straightforward. Unfortunately, it’s not. Researchers are constantly plagued by incessant delays and lengthy negotiations – all which stem from the fact that they have to go through a variety of different processes before their projects can commence.
The processes for obtaining datasets are incredibly unwieldy. They’re riddled with inefficiencies and duplication, which means researchers are pitted into an unwilling dance between multiple sets of data agencies, custodians, data linkage key and infrastructure providers, all whilst they’re chasing approvals from multiple ethics committees. The end result? The pace of Australian health and medical research (HMR) is slowed, drastically.
Talk to most Australian health and medical researchers and they’ll tell you that data is vitally important to their work. Data can help us track population health trends and further our understanding of disease causation. It might be used to target government spending more effectively, or identify instances of low value medical care. The right kinds of data can even allow us to survey pharmaceutical drugs once they’re released onto the market, and tell us what kinds of side effects these drugs are producing – or if they’re even working at all.