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As 2017 winds to a close, here’s a look back at a half-dozen particularly illuminating discussions about analytics, AI, the opioid crisis, and more.
In its first year of existence, Healthcare Analytics News™ has been fortunate to speak with dozens of experts, academics, and executives. As 2017 winds to a close, here’s a look at a half-dozen particularly illuminating discussions.
Jonathan Hirsch, founder and president of notable precision medicine company Syapse, sat down with Healthcare Analytics News™ to try to define the term itself and lay out some of the challenges in the field.
“We define it as enabling the physician in a real, clinical practice to use both the molecular data and the clinical data about a patient to direct a therapeutic strategy tailored to that unique clinical and molecular profile,” he said in the first half of the interview. “It’s not to say that it’s genetics and genetics alone: there are many places where genetics may not be the predominant factor.”
In the latter part of the conversation, he went on to detail the privacy difficulties and cultural challenges to practicing precision medicine. “Some small community groups and labs think that their data is a valuable commodity to be monetized, but by-and-large I would say it’s not really anything to do with large health systems not wanting to share,” he said. “It’s more of a compliance, regulatory, and legal standpoint of making that work while still protecting their risk profile.”
An associate professor of medicine and one of the physician faculty members at the Mayo Clinic’s Center for Innovation, Jean Huddleston, MD also has an industrial engineering degree. Deeply invested in the use of analytics to optimize patient treatment and improve hospital outcomes, she sat down with Healthcare Analytics News™ at the Center for Innovation’s annual Transform meeting.
“The two parts of that problem are the recognition and the rescue. It does absolutely no good to just recognize something, to have a score. Whatever use case you're using that just has a score, that just throws up a red flag. It's not necessarily going to help if you don't have a standardized response to that particular thing,” she said.
“I sincerely believe that once we try some of these things, if we can get a willing few to try, the demonstration of the impact will be so significant that the uptake will move faster.”
Trotter is the founder and CEO of DocGraph and CTO of its sister company, CareSet, which is a Medicare data vendor. At a big data meeting in Philadelphia, he sat down with Healthcare Analytics News™ to discuss how his company is able to access valuable CMS data, and why he thinks the free and responsible use of that data may be essential to Medicare’s survival.
“The numbers just don’t add up. The angles are too high on Medicare costs,” he said. “What has happened in the past is that the administration of Medicare has generated a massively valuable data set that Medicare beneficiaries themselves don’t get the benefit of.”
By using that data to inform value-based care efforts nationwide, Trotter argued, CMS can gain needed relief from an overall decrease in healthcare costs. Those efforts are dependent, however, on bureaucracy and politics.
““I hope the Trump administration can look at this and see the case that I am making, which is that data transparency is good for new business initiatives, and therefore new business initiatives are going to be part of the cure,” he said.
Marco D. Huesch, MBBS, PhD, has deep thoughts on the role of analytics in healthcare. Earlier this year, he and a colleague penned a compelling “Case for Data Scientists Inside Healthcare” for the New England Journal of Medicine’s Catalyst publication. He granted Healthcare Analytics News™ a long, thought-provoking interview, speaking of major systemic issues he sees in American healthcare’s adoption of analytics and their extensive upside for those that are able to make the leap.
“You’ve got this sort of systemic, in my opinion, under-resourcing in management competencies, only one of which is analytics. Whatever you can say about the other weaknesses, however, applies in spades to analytics,” he said in the first part of the interview.
In the follow-up, he acknowledged that analytics departments may be a prohibitively expensive undertaking for some institutions, but had very little sympathy for academic medical centers that chose not to adopt: “There is a tradeoff, but for academic medical centers there’s almost no justification for not doing it in-house. It would be equivalent to just getting rid of your medical school and just being a provider,” Huesch said.
Before she spoke at the Mayo Clinic Center for Innovation’s Transform 2017 meeting in Rochester, Minnesota, Laura Adams sat down with Healthcare Analytics News™ to discuss her work on camera. She is the CEO of the Rhode Island Quality Institute, which is compiling a comprehensive database of healthcare information in the state.
“We wanted to be the nation’s living laboratory, the petri dish for innovation. I’m happy to say 17 years later I think that we can legitimately claim that mantle now,” she said.
Her multi-part interview covered multiple topics. She spoke passionately about how RIQI’s work is being used in the fight against opioid abuse, to test artificial intelligence overlays for outcome prediction, and to move away from the “toxic” fee-for-service model.
In June, a pair of Stanford researchers wrote a well-read piece for the New England Journal of Medicine to argue that healthcare should “move past the hype cycle” when it came to machine learning technologies. One of the authors, Jonathan H. Chen, MD, PhD, is an assistant professor of medicine in the Stanford Center for Biomedical Informatics Research.
Speaking to Healthcare Analytics News™, Chen talked at length about the potential that artificial intelligence (AI) holds for medicine and outlined the motivation behind the commentary:
“I actually think AI has huge potential for medicine, that’s exactly the type of stuff that I’m working on. If there’s a backlash because people overhype what’s possible too early on, it becomes harder to invest in the longer-term work…People just don’t have the right expectations at times.”