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Brian Behlendorf: So there’s a tremendous amount of fraud in the prescription drug marketplace. And just like with provenance tracking of diamonds or the food supply chain you can have provenance tracking for pharmaceuticals. You can have a system whereby the drugs—from the time they’re manufactured and the batch that they were made in and in the factory they were made in—were tracked in someway that maybe parts of that were public, maybe parts of it were private, but were tracked through the distribution process to the end recipient. Now obviously when we're talking about individual patients and the prescriptions that they get, that is highly sensitive data. That's data that you wouldn't ever store directly in a chain—what your prescription is, what my prescriptions are, that sort of thing. But tracking these objects, tracking these individual vials of a drug or bottles of a drug as they get down to the pharmacy level is something that we can do to try to see: where are there pharmacies that seem to be dispensing a lot more than they should be based on the prescriptions that they’re receiving? Furthermore, finding ways to actually measure, so maybe separate from the opioid crisis but we actually have a challenge of adherence in the drug industry of understanding for a given prescription drug who is actually taking that at the times they should be taking it and continuing to take the full regiment rather than stopping halfway through because they felt okay. And so you could see IoT sensor data from the dispenser devices themselves, weaving together a picture that allows us to see all the way from the batch the drug was made in to the people who were prescribed it, and who took it if there is a problem out there, if there is a quality control issue where did that come from, and who might be responsible for that? And correspondingly the patients who do adhere well, are they benefiting from the use of those drugs? Or the ones who are having poor reactions are the ones who are only taking half their prescription? That sort of thing.
Bringing it back to the opioid crisis, I think tracking prescriptions in a system like this, if we can find ways to do it that respect patient confidentiality (because I’m a huge believer in the importance of keeping the patient at the center of who their information is being shared with and on what basis), but if we can build kind of an airtight system for tracking all that and understanding where these prescriptions are going we’ll have a much better basis for discovering fraud, discovering places where there might be fraud, and it’s worth deeper investigation and trying to understand how do we get to - I tend not to blame the drug taker because I think they're just medicating to meet their needs, it's really the distributors and those writing fake prescriptions and others who are enabling a lot of this crisis, and I think distributed ledger technology can help us understand where there might be abuses in that system.
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Brian Behlendorf: So there’s a tremendous amount of fraud in the prescription drug marketplace. And just like with provenance tracking of diamonds or the food supply chain you can have provenance tracking for pharmaceuticals. You can have a system whereby the drugs—from the time they’re manufactured and the batch that they were made in and in the factory they were made in—were tracked in someway that maybe parts of that were public, maybe parts of it were private, but were tracked through the distribution process to the end recipient. Now obviously when we're talking about individual patients and the prescriptions that they get, that is highly sensitive data. That's data that you wouldn't ever store directly in a chain—what your prescription is, what my prescriptions are, that sort of thing. But tracking these objects, tracking these individual vials of a drug or bottles of a drug as they get down to the pharmacy level is something that we can do to try to see: where are there pharmacies that seem to be dispensing a lot more than they should be based on the prescriptions that they’re receiving? Furthermore, finding ways to actually measure, so maybe separate from the opioid crisis but we actually have a challenge of adherence in the drug industry of understanding for a given prescription drug who is actually taking that at the times they should be taking it and continuing to take the full regiment rather than stopping halfway through because they felt okay. And so you could see IoT sensor data from the dispenser devices themselves, weaving together a picture that allows us to see all the way from the batch the drug was made in to the people who were prescribed it, and who took it if there is a problem out there, if there is a quality control issue where did that come from, and who might be responsible for that? And correspondingly the patients who do adhere well, are they benefiting from the use of those drugs? Or the ones who are having poor reactions are the ones who are only taking half their prescription? That sort of thing.
Bringing it back to the opioid crisis, I think tracking prescriptions in a system like this, if we can find ways to do it that respect patient confidentiality (because I’m a huge believer in the importance of keeping the patient at the center of who their information is being shared with and on what basis), but if we can build kind of an airtight system for tracking all that and understanding where these prescriptions are going we’ll have a much better basis for discovering fraud, discovering places where there might be fraud, and it’s worth deeper investigation and trying to understand how do we get to - I tend not to blame the drug taker because I think they're just medicating to meet their needs, it's really the distributors and those writing fake prescriptions and others who are enabling a lot of this crisis, and I think distributed ledger technology can help us understand where there might be abuses in that system.
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