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Health Care Consumers Need Incentives

Question/Topic: How should consumers be included in the picture?

George Halvorson: I think consumers need to be brought into the picture in a couple areas. One of them is when you're looking at something like knee surgery or back surgery, even cancer survival rates, if you've got consumers armed with sufficient data to make an informed decision about the best caregivers, they will make those decisions. If you have stage three lung cancer and you knew there was a difference in survival rate between three different oncology groups in town, would you or would you not use that data to pick an oncology group. Of course you would. And what would happen if that happened? That oncology group would get better than the other ones would catch up. And you'd have a different market than oncology. Right now you have no clue. If you have stage 3 lung cancer you don't have a clue, you don't know who to pick you know who's got the best reputation, but you don't know if we have the best outcomes in study after study has shown that organizations who could best reputations often don't have the best outcomes. Some heart surgery survival rates show that the institutions that everybody thought the absolute premiere institutions have a death rate was double, triple than some of the others. So you need the data and if you've got the data you make an informed choice that's part of the market.

The second thing is, if you've got a chronic condition, you need to have appropriate incentives to go to the right team of caregivers and work to with those caregivers in getting your care. That's where the benefit package needs to reward you and incent you and channel you to the best caregivers. And caregivers should then be rewarded for the best care. And if you put those two pieces together you get people to the very caregivers. Right now, there are no incentives, no channeling, no direction, no data, nothing is pushing people towards this caregivers. And so people who want the best caregivers don't even know where to go. And part of the problem with medical savings accounts, at the very bottom level – the concept of having people make value-based choices is not a bad concept; the problem is people have no data years. They don't know this but I give them the best knee surgery, they don't know this but I give them the best of anything, there is no data. And so the medical savings accounts as an incentive for better care of pretty much failed. As an incentive to get people not to buy certain kinds of things they've had some success in the challenges that if you've got somebody with a chronic condition who is not getting their appropriate treatments because of the deductible, well that’s a very bad thing. And so there is architecture to that process that needs to be done really well.

But medical savings accounts on their own didn't create informed decision-making on the part of consumers because there's no information. I mean, if Medicare, with all of its information can't make informed decisions about the best care givers, why would a consumer with a $1,000 deductible suddenly be magically empowered to make that decision.

Data. We actually need data. We need to track outcomes. We need to track care delivery. We need information about the entire care delivery infrastructure. We need to know which kids are having asthma attacks. Ideally, you’ve got electronic medical record in real time. What we do at Kaiser Permanente, we have electronic medical records. It’s real time in the doctor’s office. When I had the x-ray on my shoulder, I walked down the hallway, by the time I got to the end of the hallway, the doctor already had the x-ray up on the screen because it was all digital and it was enlarging it and showing me the little bone spur on my shoulder. I mean, that kind of thing is optimal. The rest of the world isn’t going to be there for awhile, but what the rest of the world can do is take that electronic claims database and follow-up on the patients with chronic conditions and identify who is having complications, and then make sure the ones with complications are channeled into care teams. And use the benefit packets to channel people into care teams.

One of the things that some people experimenting in India have done that has been very successful is, instead of changing the benefits, because you don’t want to give a person who is not getting their chronic care needs met a higher deductible because then they are just less likely to get it met. But if you say to the person, which they’ve done in India, “You’re not doing the right things for your chronic care needs and therefore, the amount we take out of your paycheck is going to go from $40 to $80. And it’s going to stay at $80 until…” The model in India was, until people had their blood sugar managed appropriately. Anyone whose blood sugar went beyond a certain percentage, if you were a diabetic, paid double the premium until the blood sugar came back in line. And guess what, the blood sugar came back in line because people didn’t like to have the money taken out of their paycheck.

I’m not sure we could do that type of thing explicitly in America, but it is that kind of thing that you need to be doing to get the patients who have those conditions into the right care settings and then reward those care settings with both volume and fair payment. So that’s the business model of American healthcare. We need to change the business model of American healthcare to produce what we want it to produce.

Topic: Creating a national culture of health

George Halvorson: We need a national culture of health. We need to say, we need people to eat differently, we need a higher activity level, we need people to smoke less. There are certain things we know will really have an impact on health. The numbers are overwhelming. The relationship between obesity and heart disease and diabetes is stunning. And now there’s really good evidence that your likelihood of having Alzheimer’s doubles if your cholesterol level is high in your forties. And so, if your Alzheimer’s risk goes up, if your heart disease risk, there’s all kinds of reasons pushing us toward healthier attitudes.

Finland, a decade ago had the worst health in Europe. Highest cholesterol levels, most obesity, most heart attacks, most diabetes. Finland was absolutely the least healthy country. They adopted a national culture of health. Their leaders promoted it, their schools promoted it, their businesses promoted it, they changed eating habits, they went through a whole series of things. They are now 20% below the European average on those issues. They’ve gone from the top, to way down on the bottom just by, as a country, being absolutely conscious about it, talking to everybody about it, making it a national goal. It’s a very small country, but it’s a really impressive result. And if you look at the lines. I think the last chapter in my book has the Finnish success chart and shows what an incredible difference they have made in that country by making that a national initiative.

If President Obama and the Congress said, we are going to create a national culture of health in America and we are going to cut the number of diabetics in America in half in five years or 10 years, we could do it. The biology is there, the science is there, the approaches are there. It’s not rocket science. We wouldn’t have to inject everybody with something. We could get there. But we are not going to get there unless it becomes a national initiative and unless somebody calls for us to go down that path. But we should. And it would be a huge mistake not to.

Recorded on:  September 21, 2009

George Halvorson, the CEO of Kaiser Permanente believes patients need more access to data and should be rewarded for taking care of chronic conditions.

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A new hydrogel might be strong enough for knee replacements

Duke University researchers might have solved a half-century old problem.

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  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
  • The blend of three polymers provides enough flexibility and durability to mimic the knee.
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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.

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