David Goggins
Former Navy Seal
Career Development
Bryan Cranston
Critical Thinking
Liv Boeree
International Poker Champion
Emotional Intelligence
Amaryllis Fox
Former CIA Clandestine Operative
Chris Hadfield
Retired Canadian Astronaut & Author
from the world's big
Start Learning

Most People Would Prefer to Die at Home. So Why Are We Still Dying in Hospitals?

Too many people continue to die in hospitals, often in pain and hooked up to machines, when they'd much prefer to die at home in peace surrounded by family and friends. Dr. Angelo Volandes' new book helps guide families to understanding end-of-life scenarios and to take control over their fates.

Angelo Volandes: As a doctor, there have been many experiences that encouraged me and inspired me to write this book. Too often in health care, when we ask our patients where do they want to die, they tell us at home surrounded by their families and loved ones. But the fact is most Americans are still dying in our hospitals, often tethered to machines and in a good deal of pain and suffering. The book addresses the conversation, which is that discussion that patients and families and doctors need to have before they become seriously ill.

There are many reasons for that disconnect between people saying they want to die at home but ending up dying in our hospitals. First and foremost, although we expect our doctors to be master communicators, the fact is we don't really train them on how to communicate to patients. Look, I finished medical school, residency, and even became a young junior attending and I had to show competency in how to run a code, how to perform CPR, how to perform a lumbar puncture, but not a single person actually certified that I could actually talk to a patient and a family about care at the end of life. I think that's a huge problem in our health care system, in our education system that accounts for this disconnect, this misalignment between the type of medical care patients want and the type of medical care they end up getting in our health care system today.

I think there are a lot of things in medicine that have led to this state of affairs. First is look, we live in one of the greatest places in the world where science has conquered a lot when it comes to disease. And so I think the expectation is the next new thing in health sciences, the next new cure. We live in a society that has a denial of aging and a denial of death. I think that's a large reason why doctors are uncomfortable about talking about this, but also we as a society don't like to talk about death and dying at all.

I think a lot of people ask me what should I as a non-doctor know about you the doctor when it comes to this topic? And I would say that look, even though I'm a doctor, I struggle with this as well. And so I look forward to when my patient or my family member tells me, "Hey look, I'd like to talk about this. It's an important part of a good life, a good death as well. And so I'm open to talking to you about what's important to me if I become seriously ill and in need of medical care." I think if more patients started the conversation with their doctors, we'd have a much better patient/doctor relationship. I think doctors need to know that it's okay to broach this inherently difficult subject matter.

Too many people continue to die in hospitals, often in pain and hooked up to machines, when they'd much prefer to die at home in peace surrounded by family and friends. Dr. Angelo Volandes of Massachusetts General Hospital describes this fact as the inspiration for his new book, The Conversation: A Revolutionary Plan for End-of-Life Care. The conversation at the heart of the book is the discussion every family needs to have before serious illness rears its head. In the process of teaching how to have this discussion, Dr. Volandes explores the faults of the medical system at large and offers solutions for major fixes.

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.

  • 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.
Keep reading Show less

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.

Keep reading Show less

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.