This appeared a few days ago.
Private companies accessed MBS data dump 1000 times
| 13 October, 2016 |
Around 1000 private companies could potentially identify the MBS claiming histories of individual doctors following the Department of Health's botched data dump.
The department's release of one billion lines of supposedly anonymous MBS data in August was intended for research.
But the department was forced to remove the dataset two weeks ago after learning that provider numbers could be decrypted.
Minister for Health Sussan Ley (pictured) has attempted to reassure doctors, saying no "identifiable data had been compromised".
However, it has now emerged that the data was downloaded 1500 times before it was pulled.
Around 500 downloads were carried out by academics, but there were also 1000 downloads by private companies including private health insurers.
Researchers were able to decrypt the service numbers of providers, which were linked to MBS claims for 10% of all patients between 1984 and 2014.
The service numbers, which can theoretically be linked to doctors’ names and practices, could reveal GPs who frequently claim particular MBS items.
As part of its attempt to sort out the bungle, the government introduced draft laws in the Senate on Wednesday, which will see anyone attempting to decrypt the data after 29 September facing up to two years in jail.
The RACGP said it was possible, but unlikely, that health insurers or other companies would want to identify individual doctors’ claiming history.
“The likelihood for damage to occur is limited,” said Dr Nathan Pinskier, chair of the RACGP expert committee on e-health and practice systems.
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It is very interesting to me just how high the level of interest was in this data.
What do others think the downloaders might be up to?
David.
1 comment:
That amount of data could easily be used to develop service usage histories and trends for providers. Based on this, private insurers could use this to drive a number of commercial activities, such as targeting particular providers to become "favoured" providers for an insurer's customers based on the cost of service to a patient. Or used in the other direction to pull out and isolate providers that an insurer considers too expensive and drive clients away from that provider.
This data dump provides a wealth of information to insurers about the overall service habits of a provider, rather than just services provided to the insurer's customers.
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