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From diagnosis to spending, how AI is shifting healthcare.
“Automated phone call check-ins after a hospital stay are giving clinicians the unique opportunity to check-in with patients on how their recovery is progressing and to receive additional data after they return home. AI is helping to draw connections between what a patient answers in the phone call and determining if a live follow-up call is warranted from a clinician to talk to the patient and prevent a readmission.”
-John Langton, PhD, director of applied data science at Wolters Kluwer, Health
“Wearables and digital health today have been like the early days of computer-generated characters in movies. They looked awfully close to the real thing, like real clinical care, but there's something missing. But now with high quality comprehensive data sets-in our case a million nights of recorded sleep-we can fully utilize AI to design solutions that take what occurs in the clinical setting-personalized high quality coaching-and help professionals scale it so therapies can achieve their full promise in a larger community or patients and experts.”
-Vik Panda, managing director North America, Dreem
“AI is being used to identify people who are likely to become sick and determine what medicines and supportive care will prevent onset or progression. For example, The Business Health Care Group (BHCG), a coalition of employers located in Wisconsin covering 200,000 lives, has partnered with GNS Healthcare (GNS), which uses AI to discover best practices of health care to improve outcomes and lower the cost of care. The GNS platform has been used to identify and optimize the treatment of high-risk patients with diabetes and NASH. Additionally, the GNS AI platform has been used to determine whether multiple myeloma patients will benefit from stem cell transplants.”
- Robert Goldberg, PhD, CEO, Thrive HealthRx
“The industry standard of Logical Observation Identifiers Names and Codes (LOINC) … eliminates data ambiguity across disparate systems and can even facilitate new understanding of previously un-coded and non-standard data. By facilitating this interoperability, the new, normalized data enables analytics for reporting, analysis, quality of care, and other AI projects that otherwise would be impossible. Essentially, AI is giving health systems a tool to make sense of their data across the organizations. This also helps clinicians more quickly detect hospital acquired infections, as machine learning can flag warning signs after sifting through patient data.”
-Langton
“Healthcare organizations are using AI to identify people with health risks and intervene early, before a high-cost event like an illness or injury occurs. For example, AI systems can predict when a person is at risk of developing diabetes, and can then engage that person in personalized support programs to help them course-correct. Chatbots and other AI-powered engagement tools can also connect people to available resources and benefits, empowering them to shop for the highest quality of care at the lowest cost.”
-Allison Langley, applied AI scientist, Welltok
“AI and machine learning are just beginning to be used in supply chain management. There’s a tremendous amount of rich data constantly flowing from EHRs and enterprise resource planning (ERP) systems. AI allows queries like cost variance analysis and procedure/inventory demand intelligence to update in real time as new information comes in. AI will revolutionize the operating room and materials manager’s ability to plan for and deliver critical supplies at the right time and place, and at the right cost.”
-Todd Plesko, CEO, Syft
“Machine learning applied to a large volume of clinical and social determinant data can guide physicians’ judgment and result in more effective diagnoses. Automating administrative tasks with AI-driven voice and video transcription, as well as insight mining will enable physicians and the care team to focus on the patient, instead of tasks and procedures.”
-Balu Nair, CTO, Gray Matter Analytics
“AI can help facilitate better, more frequent support beyond the walls of care delivery. Rather than replace the work of clinicians, the right technology and data science solutions can extend their reach and help them focus on the patients most likely to benefit from their guidance."
-Trishan Panch, MD, MPH, chief medical officer, Wellframe
“While it won’t happen overnight, AI and machine learning are poised to significantly impact the industry over the next few years. Healthcare benefits accounts (HSAs, FSAs, and HRAs) will become smart and use AI to identify spending and saving opportunities, deliver more personalized experiences across every stage of a consumer’s healthcare journey, and take the guesswork out of healthcare funding decisions. Healthcare is the perfect fit for AI because everyone wins with better healthcare decisions, outcomes, and financial results.”
-Steven Auerbach, CEO, Alegeus