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Fulfilling Healthcare’s Digital Promise

Question: How can we reduce costs and improve quality in healthcare?

 

Ron Dixon: So there are certain systems that are in the United States right now that seemed to be able to provide better value-based care. These systems that are commonly mentioned are Kaiser or Mayo Clinic or Geisinger, and what they do is that they have the ability to provide care across the continuum. So if you see someone within the system, you’re likely referred to somebody else within the system, and that information that is obtained from the first person you saw is seen by that second person, so you reduce the cost of repetition.

Additionally, those systems tend to control their administrative cost a lot tighter, and they also tend to follow certain things like formulary restrictions, and they have decision-support for their physicians in their electronic medical records that they use, and they all have the basically 100% electronic medical record utilization.

 

Question: What are some advantages and disadvantages of electronic medical records?

 

Ron Dixon: Electronic medical records are important because they allow for information sharing.

 

The problem with electronic medical records is that if there are a hundred different vendors and therefore a hundred different records and information cannot be shared across so-called systems. So, if you as provider X has a certain system and me as provider Y has a different system, those system don’t share information in the current state. As a result the goal of the record, in terms of making information portable and transferable is lost.

They’re very effective within the system so the tests aren’t repeated. You can see tests that were done the previous day or the previous month. They’re very good for trending tests and trending information. But the real promise of the electronic medical record is not obtained until you have a way to link different records with different information systems.

So if you would think of the electronic medical record as the car. Right now the administration is buying cars, but we need to build roads so that the cars can travel, and all that information that is obtained at a practice in Denver can be seen at a practice in Boston if the consultation has occurred in Boston. There, the promise of the records starts to come to fruition.

Additionally the record can also provide a way for the patient to have some input and access to information about their care. If the record not only becomes the EMR, the electronic medical record, but becomes a window to the personal health record, I believe that they should be one and the same, that the physician should be able to see a part of patient’s record and that the patient should have access to the same information in a view that he or she can understand. That would allow the promise of the record to really be realized, because once you start giving patients access to their information, you start empowering patients, you start empowering self management and you start really developing a shared strategy of care between the patient and the care provider.

 

Question: What aspects of healthcare should the US government focus on?

 

Ron Dixon: I think that the government should also think about investing in things that enabled patients to take better care of themselves. So, again the medical record is not enough. We need something that patients can see and we need them to access to their information, whether it’s through readily available technology like a cell phone or a laptop or a pass-key that they can go to a public library and get their information. Yes, there is a question of safety, but that has to be managed appropriately.

I think those are the types of things that the government should be spending their money on from a technological perspective. Very simple solutions that people can understand and embrace, as opposed to again whiz-bang things that people typically are not going to use.

It’s not the technology that makes the difference it’s the implementation scheme and the people behind the technology that matter.

 

Recorded on: May 28, 2009

 

Ron Dixon, Director of the Virtual Practice Pilot at Massachusetts General Hospital, believes patients and physicians should have the same level of access to electronic medical records.

Does conscious AI deserve rights?

If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.

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  • Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
  • Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
  • One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.

A new hydrogel might be strong enough for knee replacements

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

Photo by Alexander Hassenstein/Getty Images
Technology & Innovation
  • 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.
  • The next step is to test this hydrogel in sheep; human use can take at least three years.
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Hints of the 4th dimension have been detected by physicists

What would it be like to experience the 4th dimension?

Two different experiments show hints of a 4th spatial dimension. Credit: Zilberberg Group / ETH Zürich
Technology & Innovation

Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.

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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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