Electronic medical record systems are built for fee-for-service care. That needs to change, one expert says during the U.S. News Hospital of Tomorrow forum.
It’s no secret that the hospital industry is shifting from fee-for-service to fee-for-value care. One of the problems, according to experts at the U.S. News Hospital of Tomorrow forum in Washington, D.C., is that the electronic medical record (EMR) systems currently in use aren’t geared for tracking value-based service over time.
In a Wednesday morning panel hosted by Humedica’s parent company, Optum, Chief Product Officer of Provider Markets for Humedica A.G. Breitenstein spoke about the future of intelligent health management platforms and how they boost value-based, data-driven care.
Traditional fee-for-service medicine is dead, or at least dying, Breitenstein told the crowd. “I think we can probably all agree that classic fee-for-service — put a claim in, get money back, that’s the end of the transaction — is on its last legs.”
EMRs, however, were built for a fee-for service world. “And the problem is as we move toward a pop based fee for value based notion, the core functions of the EMR and the system as a whole needs to evolve,” she said.
There is no system in America that allows health professionals to document over any longitudinal time the connection between the health of the patient and the care they’ve been given, Breitenstein said. You can be the best doctor in the world and prescribe all the right medications for a given condition, she pointed out, but if the patient has no way to get to appointments or can’t afford the $2 co-pay for the prescription, then the traditional methods won’t work.
Other key takeaways:
- EMRs have to do more than just slowly evolve. The cost centers and the revenue centers are starting to shift around, she said. “We can’t evolve to a fee-for-value model, we have to jump the chasm all at once.”
- What will help: good data, not just big data. “I’m a fan of big data. It’s a good place to start,” she said. “But I’m a bigger fan of good data. I’ll take a smaller pile of good data over a big pile of crap data any time.”
- Relying on EMR codes to predict and treat disease is no longer enough, Breitenstein said.. Across some of the main disease states that drive scores, about 22 percent of patients have definitive clinical evidence of disease but no code within the EMR. Why is that a problem? Because missing codes suggest cures. “If you’re a diabetic one year and you’re not coded for it the next year, you’re cured, even though that’s physically impossible,” she said.
- Uncoded populations had 45 percent more hospitalizations and stayed in the hospital 33 percent longer. Why? They had 73 percent fewer ambulatory (walk-in) visits as a whole, which indicates that they were not being managed well on the ambulatory side, progressing to a more serious illness and showing up on the acute side because they weren’t being managed anywhere else.
- Behavioral issues need to be taken into account to provide well-rounded care, and the focus needs to shift from treating problems (health care) to increasing health overall. If we don’t include behavioral health when thinking about treatment, “we’re not thinking about the end goal of the patient,” Breitenstein said.
- “We do not have a health system in this country,” she said. “We have a health care system. We don’t even have a shared definition of what that is. Patients don’t really want to consume services. They just want to feel better at the end of the treatment. Take pediatric asthma patients, for example. “At the end of the day, it’s really freaking tiring, exhausting beyond measure, to deal with that illness,” she said. Parents of kids who are struggling with severe asthma “very quickly get to the place where more drugs, more doctors visits, is the last thing they want to do.”
- If your goal is to deliver health care services to everyone that walks by, then there’s no need for predictive analytics. But if you’re thinking about a population where you have to manage a limited resource pool, you have to start thinking about the health status of that population and who in that population is trending the wrong direction, Breitenstein said. There isn’t don’t an effective model today to do that, though. “I would argue that, traditionally, risk analytics have been driven by economic data,” she said, adding that providers think “How sick is this population going to be, and how high do I need to set my rates?”
- Providers need to think about what is truly medically predictable, statistically. And then there’s another angle: What is preventable? “There’s no point in going after predicting certain things if there’s no clinical model for changing the direction of that outcome,” Breitenstein said. Good data is predictive, health-centric, multi-disciplinary, EMR agnostic, actionable and open, Breitenstein explained. Data systems also need to be “person-centric and longitudinal,” she added. “At the end of the day, we have a health care system, we don’t have a health system, Breitenstein said. “We don’t have a system that rewards for protecting and preserving health.” Getting fancy technology and drawing more people into your facility is a good model if you’re not thinking about preserving or protecting health. “We want to provide that tip-of-the-arrow medicine but we want to allocate more money toward those places that are going to drive the vast majority of illness,” she said. That is, we need to continue to focus on new technology while not forgetting about preventing the bulk of common illnesses and improving quality-of-life for everyday people.
- What happens if we stop thinking about health care and start thinking about health? People in high-deductible plans buy health, one attendee pointed out; they make decisions about preventing illness or treating illness based on how much of their own money they have to spend. But people in low-deductible plans buy health care; it’s easy to focus on treatment rather than prevention when treatment doesn’t really impact your finances. source
