Over the course of the last 18 months artificial intelligence (AI) has matured to the point where there are several viable vendor options for nearly every use case.
AI dominated every aspect of the annual gathering of the Radiological Society of North America (RSNA18) in Chicago. Self-described ‘machine learning’ vendors with a presence on the conference floor more than doubled from 49 in 2017 to over 100 in 2018, 25 of which were first-time presenters.
I moderated a panel hosted by Life Image on practical uses cases of imaging AI and was blown away by the conversation that ensued, particularly what I learned about how the veteran radiologists feel about being “replaced.” During the question period, a senior radiologist approached the microphone to address a comment made by a more junior radiologist on the panel which he interpreted to be too pessimistic about the potential for AI. To paraphrase the elder, “Listen here sonny, you are too young to fully appreciate what you don’t know, and you don’t know how many mistakes you are truly making on a day to day basis. 1-2 percent error rate due to fatigue alone. WE NEED AI to save us from ourselves.”
Not all old school radiologists are so optimistic: “When you’re going up the ride, you get excited,” noted University of Chicago radiologist Paul Chang said during his workshop on AI. “But then right at the top, before you are about to go down, you have that moment of clarity—‘What am I getting myself into?’—and that’s where we are now. We are upon that crest of magical hype and we are about to get the trench of disillusionment… It is worth the rollercoaster of hype. But I’m here to tell you that it’s going to take longer than you think.”
Last year, the major cloud vendors each had a significant footprint at RSNA, but this year the two largest, Amazon and Microsoft, were nowhere to be found. Only Google Cloud had a significant, if smaller than last year’s, presence. Donny Cheung, one of the Google Cloud team leaders, was on the panel I moderated and his message to the imaging community could be boiled down to two words: storage and compute. No dashboards or toolkits or tensorflowing, just storage and compute, a smart and refreshing strategy amidst the obvious feature creep many other vendors suffer from.
Over the course of the last 18 months artificial intelligence has matured to the point where there are several viable vendor options for nearly every use case.
While it was surprising that Amazon had no noticeable presence, it was even more surprising to find Facebook making news on the conference floor. Facebook AI Research (FAIR) has partnered with the Center for Advanced Imaging Innovation and Research (CAI2R) in the Department of Radiology at NYU School of Medicine and NYU Langone Health to release the fastMRI, an open source dataset for training and testing machine learning algorithms to reconstruct MRI images.
This offering is roughly equivalent to similar X-Ray and CT datasets released by NIH. Given that algorithms ALWAYS significantly outperform on all metrics against the data used to train them versus new data, the industry needs independent validation of AI claims so it is unlikely that Facebook moves the needle with this offering.
PACS vendors want to get in on the AI action by positioning their existing products as AI marketplaces or platforms (Philips HealthSuite Insights, PureWeb, LifeImage, GE Edison, FujiFilm REiLI, Nuance AI Marketplace, Blackford Analysis). Nuance has shown there is a viable market for these platforms, counting 40 startups and health systems among user groups for its marketplace. There is no shortage of startups taking this approach (MDW, Envoy.ai, Medimsight, Lify, Fovia). Imaging hardware vendors refused to be left out too, with many partnering with AI vendors to embed their algorithms on the “edge.”
International AI startups, particularly from Israel, China, and South Korea, stood out from the crowd in terms of their approach to product design, but only the companies from Israel have been able to break into the US market so far. One Korean company voiced frustration with the FDA, saying it couldn’t understand what was wrong with their application. I wonder if it underestimates the importance of using data from US patients to validate their algorithms?
Not everything we learned about AI at RSNA was positive. A paper presented at the conference showed that neural networks could be used to insert malignant features into mammograms giving a false positives, and then reverse the alterations without detection. Even scarier, it took about 680 images to train the algorithm that executed the adversarial attack. Cyberattacks have been increasing in healthcare over the last couple years, but mostly just for taking data hostage and demanding ransom to get it unencrypted. This type of attack would represent a frightening new paradigm in cyber-vulnerability, and it is certainly not difficult to imagine ways this could be exploited to make money. It could be used for a different sort of ransom, with every image appearing to show cancer until a ransom is paid and the adversarial attack is reversed. Another conceivable way this type of attack could be exploited would be falsifying data for clinical trials.
Matt Guldin · 2 years ago
Chilmark Team · 1 month ago
Chilmark Team · 2 months ago
Brian Edwards · 2 weeks ago
Whose Data is it Anyway?
A common and somewhat unique aspect to EHR vendor contracts is that the EHR vendor lays claim to the data entered into their system. Rob and I, who co-authored this post have worked in many industries as analysts. Nowhere, in our collective experience, have we seen such a thing. Manufacturers, retailers, financial institutions, etc. would never think of relinquishing their data to their enterprise software vendor of choice.
It confounds us as to why healthcare organizations let their vendors of choice get away with this and frankly, in this day of increasing concerns about patient privacy, why is this practice allowed in the first place?
The Office of the National Coordinator for Health Information Technology (ONC) released a report this summer defining EHR contract terms and lending some advice on what should and should not be in your EHR vendor’s contract.
The ONC recommendations are good but incomplete and come from a legal perspective.
As we approach the 3-5 year anniversary of the beginning of the upsurge in EHR purchasing via the HITECH Act, cracks are beginning to show. Roughly a third of healthcare organizations are now looking to replace their EHR. To assist HCO clients we wrote an article published in our recent October Monthly Update for CAS clients expanding on some of the points made by the ONC, and adding a few more critical considerations for HCOs trying to lower EHR costs and reduce risk.
The one item in many EHR contracts that is most troubling is the notion the patient data HCOs enter into their EHR is becomes the property in whole, or in-part, of the EHR vendor.
It’s Your Data Act Like it
Prior to the internet-age the concept that any data input into software either on the desktop, on-premise or in the cloud (AKA hosted or time sharing) was not owned entirely by the users was unheard of. But with the emergence of search engines and social media, the rights to data have slowly eroded away from the user in favor of the software/service provider. Facebook is notorious for making subtle changes to its data privacy agreements that raise the ire of privacy rights advocates.
Of course this is not a good situation when we are talking about healthcare, a sector that collects the most personal data one may own. EHR purchasers need to take a hard detailed look at their software agreements to get a clear picture of what rights to data are being transferred to the software vendors and whether or not that is in the best interests of the HCO and the community it serves..
Our recommendation: Do not let EHR vendor have any rights to the data – Period!
The second data ownership challenge to be very careful of is the increasing incorporation of patient generated health data into the healthcare delivery system. We project an explosion in the use of biometric devices, be it consumer purchased or HCO supplied, to monitor the health of patients outside of the exam room. Much of this data will find its way into the EHR. Exactly who owns this data and what rights each party has is still debatable. It is critical that before HCOs accept user data they work out user data ownership processes, procedures, and rights.
If the EHR vendor has retained some rights to data the patients need to be informed and have consented to this sharing agreement. In our experience this is rarely if ever explicitly stated. HCOs need to be careful here as this could become a public relations disaster.
We are not lawyers, we are offering our advice and experience to HCO CEOs, CFOs and CIOs, from the perspective of business risk and economics. At Chilmark we have deep experience in best practices used in other industries with regards to data use and sharing agreements. We have also spent significant time reviewing the entire software purchasing lifecycle and culture, and are here to help HCOs in reviewing these contracts.
Addendum: Rob and I worked together on this post but our WordPress backend doesn’t like to do co-authored posts.