In order for precision oncology to be fruitful and to be effective, we need interoperability and we need to be able to share patient data, said James Lin Chen, MD, Ohio State University, and chair of ASCO CancerLinQ Oncology Informatics Task Force.
In order for precision oncology to be fruitful and to be effective, we need interoperability and we need to be able to share patient data, said James Lin Chen, MD, Ohio State University, and chair of ASCO CancerLinQ Oncology Informatics Task Force.
Transcript
How has precision medicine changed the information needs for oncologists and tumor boards?
So, I talked about 5 rights of precision medicine today: the right diagnosis, the right test that needed to be made to make a diagnosis, the right targets, the right treatment, and the right monitoring. That all goes along with this. But along these rights for the right treatment for precision medicine are the data sets that underlie it. So, you need prognostic biomarkers, diagnostic biomarkers, monitoring biomarkers.
You also need guidelines in terms of what are the appropriate tests to run in the first place. Precision medicine has really opened up the world of biomarkers to oncologists, and that is, I think, one of the big paradigm shifts.
How does health information technology play a role in obtaining the information needed to make an informed decision for a patient?
In order for precision oncology to be fruitful and to be effective, we need interoperability and we need to be able to share patient data, because the more data that we have that we can aggregate together, the better the better the quality of the predictions we can make. So, predicting for a very small set of patients is going to be prone to error, but if we have a very large set of patients, we’re going to be able to make better predictions for who might respond to therapy.
So, in the era of electronic health records, I don’t think we’re quite there yet, but there’s a lot of work that needs to be done from a harmonization standpoint, from an interoperability standpoint, as well as simply data standardization. One of the issues that came up today during the talk was that we don’t have a common nomenclature on how to capture genes or gene alterations. These standards are being developed and they’re starting to be implemented. But, they’re starting to be implemented, we’re not quite there yet from an interoperability point of view.
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