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Re: What drives economic development?

Question: What drives economic development?

Transcript:I think the off lot of human history is driven by technological change. And technological change is an outcome. And I think the two key underpinnings are first property rights, including intellectual property rights. So if you create an idea, can you patent it and benefit from it? And more generally can you invest and open a factory, or store, or whatever, and benefit from your idea? So property rights are critical. And then I’m a big believer that international trade stimulates technological innovation. I think that people get new ideas by interacting with different economies and different cultures. And they get the opportunity to . . . If they have a good idea or good product, international trade gives them an opportunity to benefit from a very large market. So I think a lot of economic history can be understood in this interplay between property rights and international trade. And the countries that are currently the richest and most developed, like the United States and the United Kingdom, are countries that developed well defined property rights hundreds of years ago, and have generally been believers in free trade going back hundreds of years. So they’ve put this system in place over a long period of time, and have generated tremendous wealth and tremendous human progress. And now we see big developing countries like China, which had gone down a different road for a while, turning and seeing that China was falling further and further behind, and now they very much switched, and they’re trying to develop the institutions of property rights. And they’ve definitely opened up to international trade and international investment in a big way, and they’re getting tremendous results from that. And then unfortunately you look around the world, and I see quite a few developing countries that still that have weak property rights and are largely closed to the world market, and these are countries that . . . They’re the one’s you read about in the press because there’s civil wars going on. Or they’re stagnating and there’s a lot of crime developing, or different types of social problems. So I think we’re seeing the world split to some extent, not between the rich and the poor curiously. Because countries like India and China are definitely not rich, but they have gotten onto this bandwagon of developing property rights, and integrating with the global market. And then there are other developing societies that have just not gotten on to that bandwagon, and they’re falling further and further behind.

The ability to patent an idea, Dollar says, is critical.

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Image source: camillo jimenez/Unsplash
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  • 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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