Though the government may have trouble settling on the best healthcare policy, everyone agrees on one thing: The system needs to change.
The U.S. is well on its way to a value-based model that rewards providers when patient outcomes improve—and penalizes them when they don’t. It’s a welcome change that should lower costs and improve efficiency, but shifting this trillion-dollar industry will take a combination of human ingenuity and technological prowess, especially from the providers that deliver care.
“Right now, physicians are incentivized to perform services whether they’re right or wrong, whether they’re needed or not, and whether they’re delivered well or poorly,” said Dr. David Wennberg, data scientist at Quartet Health and adjunct associate professor at The Dartmouth Institute. “That’s a flawed model.”
Policymakers, payers, and providers are all doing their best to fix it. Medicaid directors from 20 states instituted value-based models in 2016, according to a survey of Medicaid directors1. In 2015, the Department of Health and Human Services (HHS) set a goal of converting 50 percent of fee-for-service Medicare payments to value-based payment models by the end of 2018, and many private insurers are jumping on board2.
To improve patient care and avoid costly penalties, providers will need to track a host of metrics, from readmission rates to hospital-acquired infections and emergencies. For many, this means drastically improving their ability to acquire and analyze data.
“Having analytics that can tell you, ‘What are the most efficient paths for patients?’ ‘When are patients falling off track?’ ‘How do we interact with patients and know when things are going wrong or right?’ That's all the domain of this complex analytics world,” said Jennifer Esposito, Intel’s general manager for worldwide health and life sciences.
The first step for many providers is having the systems to understand what’s happening today by analyzing data from multiple sources. Advanced analytics systems can give healthcare organizations insights they wouldn’t otherwise be able to get about patient populations, what’s working, and what’s not.
“It just doesn't scale to have humans monitoring all that stuff all the time,” said Esposito. Pulling all that data from disparate sources, and making sense of it, requires sophisticated systems that can work much more quickly and efficiently than any human.
The next step is analytics that can anticipate problems and help solve them before they happen. Powerful analytics programs can take historical data and recommend the best course of treatments, predict which patients are likely to need closer follow-ups after being released, and give other potentially lifesaving insights to keep patients well instead of waiting until they get sick.
"Right now, physicians are incentivized to perform services whether they’re right or wrong, whether they’re needed or not, and whether they’re delivered well or poorly."
"Healthcare is starting to get beyond traditional transactional decision-making, and move toward real-time, predictive, interventional decision-making at the point of care."