“We don’t know who the peer reviewers are. Imagine opening a newspaper and there’s no masthead. You don’t know who any of the editors are? There’s no accountability for why this work got through or not?”
In this episode, I sit down with Emily Kaplan. She is an investigative journalist, author, business leader, and passionate advocate for women’s health and for a return to what she calls “the roots of true scientific exploration.”
“We’re one of two countries where you can directly market pharmaceutical products to consumers,” says Ms. Kaplan.
Today, she is the co-founder and CEO of the Broken Science Initiative, an alternative approach to health and science that promotes predictive value, access to data, and prioritizing patient welfare over profit.
“My sense is we’re not going to fix these big systematic problems, but you can empower the individual to critically think about things and allow them to make better choices for themselves and their family. So, that’s really the goal of the Broken Science Initiative,” says Ms. Kaplan.
We discuss various forms of scientific misconduct, touching on peer review, statistical manipulation, and the over-medicalization of childbirth.
Watch the video:
“The highest predictor of whether you’re going to have a C-section or not is what hospital you deliver in. It’s not you. It’s not your doctor. It’s the hospital,” says Ms. Kaplan.
Views expressed in this video are opinions of the host and the guest, and do not necessarily reflect the views of The Epoch Times.
FULL TRANSCRIPT
Jan Jekielek: Emily Kaplan, such a pleasure to have you on American Thought Leaders.
Emily Kaplan: Thank you for having me. I’m thrilled to be here.
Mr. Jekielek: You created the Broken Science Initiative. There are real problems with what’s being portrayed as science today. There is a replicability crisis that John Ioannidis pointed out in his huge paper on the topic. He says that a lot of science simply doesn’t pan out. You cannot replicate it, which is a foundational issue. Please tell us what’s going on.
Ms. Kaplan: We think of science as the empirical branch of knowledge and it should be where we most look for truth. We’re never going to find ultimate certainty or the ultimate truth, but we can pursue it. The replication crisis is a really important symptom of a larger breakdown that allows for statistical manipulation and corruption. The pharmaceutical industry spent more money lobbying Congress last year than any other industry. That’s huge. That’s more than manufacturing and more than finance.
If you look at the spending by the pharmaceutical companies on media, you can see a very similar playbook. We’re one of only two countries where you can directly market pharmaceutical products to consumers. All of this falls under this idea of a broken science. This isn’t political. People try to move this into the political sphere, because people feel very defensive about it. You want to trust your doctor. Your doctor didn’t go to medical school to mistreat you.
But the power structure has been inverted, so we’re seeing all these symptoms. Greg Glassman, my partner at the Broken Science Initiative, and I have both been looking at these problems for about 20 years. When Covid happened and there was real polarization and disagreement about what you could trust or what information was valid. Actually, it was a gift, because it brought science to the dinner table in ways we hadn’t seen before.
Regardless of which side they were on, many people didn’t really know who to trust. My sense is that we’re not going to fix these big systematic problems, but you can empower the individual to think critically about things and allow them to make better choices for themselves and their family. The goal of the Broken Science Initiative is to expose these problems.
There is a tremendous amount of scientific misconduct going on right now. We lost Harvard’s president and Stanford’s president within six months of each other to charges of scientific misconduct. This is a real issue that Americans need to inform themselves on. In the fall, we will be launching an education society so kids can understand the importance of asking good questions and challenging authority in a polite and respectful way.
The only way that we make progress scientifically or as a society is having better ways to accomplish things and solve problems. I fear that we have gotten away from that. The isolation and polarization that we see politically is terrifying. We lose curiosity about the things we think we understand. But if you’re not open to listening to other people’s ideas, we are all in big trouble. The truth is that we all want a better life for our kids than we want for ourselves, no matter what political party you’re involved in.
From my stance, health is the root of happiness and a common denominator for all of us. Bobby Kennedy is taking on the chronic illness epidemic in a very thoughtful way. I said that I wasn’t going to get political, but I do think he deserves a lot more attention. He has successfully sued many branches of the government. He knows how they work and where the corruption lies.
The chronic disease epidemic in this country is our number one vulnerability. There are many things that doctors and patients can learn and do. Moms and dads can help their kids in terms of lifestyle changes and getting the sugar out of the diet. These are rudimentary things that we don’t really think of as medicine, because they’re preventative, but they are predictable. Again, at the core of the Broken Science Initiative is this idea of predictable outcomes as the demarcation between science and non-science.
Mr. Jekielek: We absolutely need to talk about predictability. You mentioned critical thinking and openness to new ideas. You also mentioned the distinction between science by consensus vs. science by predictability. Please explain that distinction for us.
Ms. Kaplan: Consensus means that we all agree on something by taking a vote. But there is no voting in science. That should stop us right there.
Mr. Jekielek: What do you mean there is no voting in science? Many people would say, “If you get the smartest people in the room and these people vote that something is true, doesn’t that make sense?”
Ms. Kaplan: No. There are three Supreme Court cases that make up the Daubert standard, which determines who can be a scientific expert in a court case. Two of those tests are that you have to have been published with peer review, and you have to be accepted by the scientific community. Let’s think about that for a second. If you look at space exploration, is that not science? A lot of that is top secret and it has not been peer reviewed. Are those people accepted within their scientific community? Yes.
But what about the person who builds a rocket and blasts it off from their backyard. They hit their target and then they do it again. They’re not scientists because nobody knows that they are doing that. We have these ways of thinking and creating standards, or have a certain litmus test for how we define science, but I don’t think that definition is correct.
We have this confusion about peer review. There’s a general misunderstanding about peer review being similar to good journalism. Peer review is actually a consensus. It’s a group of people who have decided that if you get a p-value that is a statistically significant result, that means that you have validated your hypothesis.
With the way p-value works, that’s not right, actually. You’re just looking at the data sets of the null hypothesis and comparing them to the data you gather through the intervention. You’re saying, “Is there a relationship between these two? Did we prove or disprove the null hypothesis?”
There is no testing the null hypothesis. That’s an assumption and you’re not saying anything about your hypothesis with a p-value. You’re also not saying that you can replicate the work, which is our standard at the Broken Science Initiative. You have to be able to replicate your results so that you know that you have a predictable outcome.
You have to take that as a standard to get published, and you have to have a significant p-value. You need to have peer reviewers who are not paid. They need to be told when they get a manuscript to assume that there is no scientific misconduct and that all facts and information are correct. I’ve had peer reviewers tell me that they also are often told, “'Don’t comment on the design of the study, because the study has concluded.”
Mr. Jekielek: It’s very easy for a skilled experimental designer to help the person that’s funding them get the idea they want. When your funding depends on getting a certain outcome, then you are conflicted.
Ms. Kaplan: We had this big scandal at Dana-Farber, which is the Harvard Cancer Research Institute, where they were copying and pasting images. They were taking an image that was day one of the control group, and later, they were pasting it into the intervention group, as if to say, “The tumors didn’t grow. We have suppressed tumors.”
Mr. Jekielek: That’s obviously not a mistake.
Ms. Kaplan: Then that is published, so it gets through these gatekeepers. Is that a design failure? Actually, it’s an execution failure. There’s so much of this kind of image manipulation going on. No one is really looking at the images except for these image sleuths like Elisabeth Bik, who is a big hero of mine. They’re all doing this on PubPeer, and it’s a hobby for them.
My point is that the statistical significance is so easy to manipulate that you can come up with whatever outcome you want. We’re not going a step further to say, “You’re claiming this is a statistically significant result, but let’s look at the images. What do the images say?” With some of this stuff, you don’t need sophisticated technology. You can literally see that it’s been copied and pasted.
Why is this not something that’s causing complete unrest in our society? You have these major institutions committing real fraud and the outcome for the patients isn’t being considered. This is another part of this consensus. You’re a doctor and you hear something’s coming from Harvard Medical School and you say, “I’m going to trust it. I’m not going to challenge that.”
There are even statistical things that are really interesting, like intention-to-treat analysis. We do this thing called journal club where we go onto a Zoom chat and take studies apart. We’re looking at real hallmark studies and then finding how the information is being portrayed in the article vs. what we really know. The intention-to-treat analysis is very common.
It means that you take a snapshot of day one of a trial. Then you have people who drop out of the study or maybe they die. You take their data and you basically supplant it for the time that they’re not in the trial, assuming that it was the same result consistently across that time. We just did this.
We were looking at an exercise and aging study out of Norway which did this. They have people who drop out of the study and they just assumed they kept exercising. Actually, we don’t know that. Maybe they did, and maybe they didn’t. They weren’t part of the study anymore.
We’ve taken something that in its purest sense is about drilling down on uncertainty, and then we’ve developed all of these statistical, mathematical tools that have made everything far more complex. There’s this whole idea of person-years, which is another statistical thing that is very difficult to understand. It’s a way of estimating, but it doesn’t end up being very accurate.
We are not rethinking what statistical tests are actually meaningful. Gerd Gigerenzer of the Max Planck Institute, who has spoken at some of our events, calls it a ritual. I love that observation. It only has the meaning that we put into it. It’s not actually a stop gap. It’s not actually a safeguard against any of this stuff.
Concerning peer review, there is also the problem of not knowing who the peer reviewers are. Imagine opening a newspaper and there’s no masthead. You don’t know who the editors are. There’s no accountability for the news that is being published.
Another great example is the research that Begley and Ellis did with Amgen, where they realized that cancer and hematology drugs weren’t as effective as they should be. They tried to replicate 53 trials, and they went to great lengths to do this. They worked with the original researchers and tried to recreate the environment, so that all the variables were as close and as stable to the original work as possible, and they could only replicate 11 trials. They could only replicate 11 out of 53 hallmark cancer and hematology studies, going to extreme cost and length to do so.
Then they promised the researchers anonymity because they needed their buy-in and needed them to help. The researchers knew that their work couldn’t be replicated, but none of those trials have been retracted. Those studies still live in high-impact journals as though they are sound research, even though the people involved know their work couldn’t be replicated. Amgen knows, but they haven’t shared it.
Mr. Jekielek: I just referenced John Ioannidis’ work, his meta-analysis, which is shocking. I can’t remember the exact statistics right now, but it was so low.
Ms. Kaplan: Most research findings are false, and that is shocking to people. You can look at people like Marcia Angell, who was editor-in-chief of the New England Journal of Medicine, Richard Smith, who was the BMJ editor, and Richard Horton, who was head of Lancet. These are top medical journals. All three have independently come out and basically said, “We cannot trust anything in these publications.” Marcia Angell wrote a book about it, but it hasn’t changed anything.
It is because of this that I have no hope for the systematic way that we are handling these things. You have people at the highest positions in their own industry who are calling foul and nothing changes. Why is that? Greg sold CrossFit in 2020. We’ve spent about four years trying to find the root cause, rather than looking at these symptoms. There are many organizations doing great work looking at research that won’t replicate or looking at Covid.
Mr. Jekielek: Please lay out the symptoms for us. What you call a symptom, a lot of people might even see as a cause.
Ms. Kaplan: There are many people who are really focused on what happened with Covid, which showed that science is broken or that medicine has been corrupted or captured. That’s a symptom. The amount of money going to the government and to the media from pharmaceutical companies is a symptom.
During Covid, Fauci and Collins controlled all the money. They should not be involved in policy, which is a conflict of interest. If somebody disagrees with them, they’re potentially not going to be funded. That’s a symptom. It should be like the separation of church and state. Peer review is a symptom. This Daubert case, which I would love to see overturned, is a symptom.
From our perspective, looking at the philosophy of science, this goes back to Karl Popper and his denial of induction. Induction is a very clear and simple way of being able to take information that you know and then apply it to a future prediction. Hume actually is the first person to call induction into question, which is reasonable to do. There is an inherent bias if you take your past information and then apply it to something in the future.
However, you’re not going to get the best outcome if you don’t take someone’s medical history into account. You’re looking at an MRI and you want to know what led this person to getting the MRI? That’s hugely important and that is all inductive reasoning.
This has led to this frequentist approach where it’s all zeros and ones, yes and no, and very binary. Our goal is to return predictive value to science, because it isn’t a zero or a one—it’s on a scale and you want to know how close you are to certainty.
Mr. Jekielek: When these MRIs are looked at, they don’t involve the patient’s history?
Ms. Kaplan: No, actually, they do. That’s an example of how we absolutely need to take the patient history into account moving forward. But with this denial of induction comes the notion that we have to be unbiased about how we process information. This is where a lot of the statistical tests come from, like null hypothesis. Significant testing is really a product of this frequentist mindset.
Mr. Jekielek: Frequentist is a word many people will not understand.
Ms. Kaplan: The frequentist approach means we’re going to have certainty about things. It’s like in computer language, it would be zero or one. We employ the Bayesian approach, which is about predictive value. If you use Bayes’ theorem, you can test the hypothesis outcome.
As an example, I just did something on Instagram looking at mammograms. People often talk about mammogram sensitivity and specificity, which is just the rate of false positives or true positives or false negatives, which is not telling you anything about you. It’s telling you about the test. But as a patient, what do I want to know?
I want to know what is the likelihood that I have a positive mammogram which indicates breast cancer. I need to have a prevalence rate, which is prior information. That’s larger information than just what I’m looking at. With sensitivity and specificity, all you need to know is the outcome of the test. But if you want to know something for the patient, you really need to know what the prevalence rate is. Then you can come up with positive predictive value.
Ms. Kaplan: (pre-recorded audio) Suppose you get a mammogram and receive a positive result. What is the probability that you actually have breast cancer? Let’s calculate it. Positive predictive value is a measure of how often someone who tests positive for a disease actually has the disease. Positive predictive value can also be expressed as a conditional probability, the probability you have breast cancer given you have a positive mammogram. We can use Bayes’ theorem to calculate the positive predictive value.
First, we need to know how well mammograms correctly diagnose cancer. This is known as sensitivity. It is the percentage of true positives out of all the mammograms that correctly diagnose cancer. This is known as sensitivity. It is the percentage of true positives out of all the mammograms done. Sensitivity for a mammogram is around 84 percent.
Next, we need to know how common breast cancer is in the population. This is the disease prevalence represented in our formula with the letter P. For breast cancer, 1.25 percent of women have it.
Next, we need to know the percentage of the time a mammogram correctly identifies an individual who does not have a disease. A test with a high specificity means there are few false positives. For mammograms, around 91 percent of the time the test is negative, when in fact the person does not have cancer, so the specificity of mammograms is 91 percent.
What does this mean? Let’s put it all together. If you get a mammogram and receive a positive result, the probability that you actually have breast cancer is only 10.56 percent. At first, this may seem shocking, but let’s think about it. If 1.25 percent of women have breast cancer, and a mammogram gives a false positive 8.88 percent of the time, for an uncommon disease, most of the positive test results will be wrong.
Ms. Kaplan: That’s hugely important and nobody tells patients that and it causes stress. You could do this for anything. You could get an AIDS test and then ask, “Am I dying? I'd like to know that.” It may be two weeks before you can go back and get another test. It would be nice to know the likelihood that you are going to die, even if it is five or ten percent.
You don’t care about the sensitivity and specificity of the test other than how it relates to you. That requires predictive power, so you need to have other information. Using the Bayes’ theorem, with something like the mammogram or the AIDS test, you can refine it.
You could say, “I have a genetic predisposition. I don’t want the general prevalence rate. I actually want my cohort rate. Am I more likely than the general population to have breast cancer?” Then you factor that in and you'll still be able to figure out how likely this test will predict that I have it. There are things like that we are not doing, that we could be doing.
I’m not trying to take down the practice of medicine. Doctor morale is at an all-time low and I understand why. They entered this profession to heal and to treat, but they do not spend much time with patients. I have a doctor friend who says that it used to be when the doctors walked down the hallway the administrators would run and hide out of fear. Now, it’s the other way around.
It is because the doctors are being yelled at for not filling the form out correctly, or not coding something correctly. They are not accountants, and that’s not why they got into this. They got into this to hold the hand of the patient, help the person heal, and help prevent illness, but we’ve taken that power away from them.
I like to remind doctors they are the only ones with any moral authority. They take the Hippocratic Oath and that really means something. As patients, we are absolutely dependent on them, because the pharmaceutical companies are only beholden to their investors. They have a fiduciary responsibility to deliver returns, and so do hospital systems, and even academia.
The only safeguard that I see in the system is the doctor who stands up and says, “If I put you on this drug, you’re going to get these side effects, so let’s just try something different. Let’s see if we can get 50 pounds off of you and see how that goes. Then maybe you won’t need this drug.”
That’s a conversation we would all value and respect. It’s not happening to nearly the degree that it should be happening. You can see this with federal funding. More than 80 percent of medical research funding goes into treatment, not prevention. Let the pharmaceutical companies pay for the treatment. Why doesn’t the government pay for the prevention? You’re working for me, right? I don’t want the treatment. I'd like to prevent the disease.
Mr. Jekielek: Please tell us about yourself. Actually, you have a journalism background as well.
Ms. Kaplan: I got a master’s degree in journalism from Northwestern University. I’ve written for newspapers and magazines. In 2020, I worked at Primetime, mostly covering murder stories. I’ve always been very curious about problems, corruption, how things work or don’t fall apart, interplay between different groups, and thinking about how to take complex information and make it accessible to people. Telling truth to power is really important to me.
When I was coming up as a journalist, you weren’t trying to be friendly with the power set. I had a lot of really great mentors that were really rigorous with me. I’ve launched a couple of startup companies and then helped with that, which I love. It’s actually quite like journalism in that you have to be scrappy and resourceful, compile lots of different data, and figure out what is going to work and what’s not going to work. Those companies all had a heavy tech focus.
I had been working on a long form story about Greg Glassman. He had sued the CDC. He had taken on the NSCA [National Strength and Conditioning Association], which was the rival personal training certification company. They had used peer review to publish a journal article in the preeminent exercise physiology journal that said his company, CrossFit, had caused injuries. Greg recognized that they had falsified all their data, so he sued, and he won.
A federal judge called it the biggest case of scientific fraud and misconduct she had ever seen in all her years on the bench. I was in the process of writing up that story when he got canceled. He was called a racist because he put out a tweet when George Floyd was murdered. This whole tweeting situation happened because the IHME [Institute for Health Metrics and Evaluation] was the modeling body for Covid. Greg is a math guy and was raised by a rocket scientist. The methodology that he designed and developed for all of CrossFit was based on Newtonian physics.
During Covid, he recognized that these models were wrong. We didn’t have a death rate. We didn’t have a denominator. How are we making these projections? So again, predictive value. In the United States, it was the IHME that was doing that work. He had been tweeting at them for a while, “Guys, your math is wrong. You’re leading us to financial despair in this country with these policies that aren’t based on solid math.
Then they said that they were going to start modeling racism as a public health issue, and Greg just about lost his mind. He thought these guys had led us into quarantine. Lockdown was going to disproportionately impact minority groups. Why in the world would we trust them to model racism? It’s too important of an issue.
He wrote, “What is this Floyd 19?” Then he had this quote from this medical journal that nobody bothered to put into google, because they would have found the article, but they didn’t. Because he’s a 60-something-year-old white man, it was easy to just call him a racist. I was working on the story about the case that he had against the NSCA. He called me and said, “I need you to help me.” I said, “I can’t, I’m not a PR person. If I do that, I won’t ever be a journalist again.”
The allegations against him escalated, then turned into toxic workplace and sexual harassment accusations. I knew him very well. He had more female executives than he had male, which is basically unheard of for a male-run company. CrossFit was the only sports company to ever pay women the same prize money as men. I had asked Greg years before, “Why did you do that? He said, “What do you mean, why did I do that? It’s the right thing to do. It’s strange that it’s not standard procedure.”
None of these stories matched with the man that I knew. As the allegations escalated, I felt a moral obligation to jump in and help him. I had done some negotiation training at Harvard Law School. I ran a business that was in the Middle East and in the United States. I was comfortable in a high stakes environment. I felt like I couldn’t stand on the sidelines and watch him be destroyed for things he hadn’t done.
I jumped in and got on the phone with the New York Times who was running a story the next day and explained that I’ve written for the New York Times and I was not a PR person, but I knew they had the story wrong. To her credit, the reporter there worked with me. She had to run the piece the next day, but after that we were able to work together.
I said to Greg, “I’m going to do a deep investigation into this. Who’s behind it? What escalated things to the point where it seems very much like a smear campaign?” He gave me access to everything I asked for; all his credit cards, all his photographs, and anything that I could use as verifiable information to forensically rip dates and locations.
I was able to prove the allegations were all false. That launched my crisis management strategic communications firm. I do the broken science work and I help people who have been wrongly accused in the media. I also help businesses that are trying to launch products into markets that they know are going to be tricky. It’s a lot like being an investigative reporter.
I go in and try to figure out who is behind it, what is true, and what is not true. It’s very hard to disprove a negative. It’s really easy for somebody to throw an allegation at you, and it’s very hard to prove that didn’t happen, especially with sexual harassment. I had a client who was accused of sexual harassment, but had never even met the woman. It was a big corporate board and somebody wanted him off the board, so they spread this rumor about him. The fear that it was going to be leaked to the media was enough to threaten his job.
We all need to take a minute and think about why somebody is saying something, what their motivations are, and how they might just be wrong by accident. We can’t just jump on these social bandwagons, because that does the biggest disservice to the real victims. There are women who really are sexually harassed.
It’s really important to be thoughtful, ask good questions, and be conscious of the impact that you have when you challenge somebody. In the medical sphere, if you decide to take a treatment, do you really understand what that treatment is? We just had this story that we’re writing up for Broken Science. We have original pieces that we put out, and then we also have ones that are curated news pieces which are part of our newsletter.
There was a headline around the world saying that this new cancer therapy called CAR-T was amazing. It had stopped tumor growth in the brain, which would be remarkable. We really do need a cancer treatment breakthrough. But when we looked at the study, all-cause mortality was no different and people weren’t living longer. They were stopping the tumors from growing, but they were dying at the same rate.
That’s fascinating. What does that mean? I don’t have an answer, but I would think maybe the treatment is killing them. They’re not dying from the tumor. They’re dying from something else. Nobody in the media covered that. Everyone that covered it said, “It’s a cancer breakthrough. Look, these tumors have stopped.” That’s great. You stopped the tumor, but the goal is to live longer.
Mr. Jekielek: Your approach is to see the context of every scenario and make sure you factor in all these elements that often are missing.
Ms. Kaplan: Yes, and it’s also to challenge both yourself and whatever it is that you’re considering. It is asking good questions, and really good questions come from really good listening. We’re not doing enough listening. There is a real detriment to not having a life of learning and wanting to be curious. I love people who don’t agree with me, because I always learn from them. But I think that that is less and less common.
Even for me, I can put people off because I challenge them. It’s not because it’s a disrespectful thing. It’s just the opposite. I respect you enough to want to know how you formed that idea because it’s different from mine. Please explain it to me. It doesn’t mean I’m going to agree or disagree. It means that I want to know how you got there.
Mr. Jekielek: There’s one study that you looked at that says black women in America can disproportionately die from childbirth compared to many industrialized countries. Is that true? If so, why is that?
Ms. Kaplan: Yes, it’s true. This is looking at statistics and not peeling back to get to the root cause. I did a lot of reporting on maternal mortality in my prior life when I was still a journalist. I became really interested in C-sections because the maternal mortality thing is usually downstream from a C-section. C-sections are really difficult to study.
Neil Shaw is a great researcher in Boston who has looked at this more critically than anybody else, because he was delivering babies in two hospitals in Boston, both Harvard medical teaching hospitals. The populations were very similar. His C-section rate was much different in one hospital than it was in the other.
Now, he’s the same doctor and there are all these variables that are constant. He became really obsessive about trying to understand why so many more people were being given C-section in one hospital. He was the doctor choosing to do it. He thought, “What’s going on in this one hospital where I’m delivering more by C-section than the other hospital?”
Because he’s just one guy, the patient populations are very similar, and the hospitals are funded similarly, he was able to unpack some of this. He said to me, “It’s really hard to study, because you never deliver a baby via C-section and think that you didn’t really need to do that.” The hindsight bias is so strong, because every time you think, “Thank God, the baby’s okay.”
With the maternal mortality crisis, they will say things like hemorrhaging or name other things. The CDC codifies this stuff. They’re not calling it a C-section death. The race component of this comes in because it’s probably a socioeconomic thing more than a race thing, if you were to really dial it down.
If you have a C-section, you’re not supposed to lift anything over 10 pounds for weeks. If you have an hourly paying job where you don’t get maternity leave and you have to go back to work maybe a week after you have a baby, you are at way higher risk for some sort of complication. If you’re a mom and you’re home with other kids you are responsible for and you’ve had a C-section, then you are at high risk.
Those populations are not cared for properly. We don’t care for women in the health system very well. I really became very interested in women’s health, because we know that women’s brains are different, our hearts are different, and our 91 are different. Everything in our health is dictated by your endocrine system, which is hormonal and women’s bodies are not studied.
In 1977, the government made it illegal for women to be in clinical trials if you were of childbearing age. What is childbearing age? It’s like the majority of your life, like age 15 to age 55, if you want to be safe. We weren’t studying women’s bodies. It was illegal to do so.
Then in 1993 they said, “Okay, women can be involved in clinical trials again.” It wasn’t that long ago that med schools started doing female cadavers. It was just this assumptive practice that our bodies are the same, except that because of our hormonal cycle, we are complicated to study. Maybe people don’t want complex problems that are hard to understand. The diseases women get are different, the prevalence rates are different, and the treatments affect us differently.
There is a huge amount of research that needs to be done in that realm. Childbirth is a huge inflection point for a woman for all kinds of reasons. It’s usually the first interaction that she has with the medical system. We have over-medicalized childbirth. It used to be that you would have a midwife, unless you were at high risk, and then you would go to a hospital.
I have interviewed nurses who have said, “I used to sit by the woman’s bedside and tell her that everything was normal and this is how it goes. I would count for her, and do all kinds of things. Now, I’m sitting with a bay of 20 monitors watching heart rates.” Today, you have a heart rate monitor in the room with you and it’s monitoring the baby. The mom’s heart rate is going to go through the roof, because she’s worried about the baby.
There was a clinic pilot program where they realized that moms will skip their follow-up appointment, but they will not skip their baby’s follow-up appointment. If you can book the mom and baby at the same time, and you have the pediatrician and the OB in the same office, the mom will show up. It’s a simple fix. It’s like the maternal mortality stuff is happening because women aren’t going to the hospital, they’re going to a hospital that’s not taking them seriously, or they’re not making follow-up appointments to monitor for real problems.
In many countries, when you give birth, somebody from the medical establishment, whether it be a doula or a midwife or a doctor, comes to visit you at your house. You get a lot of data when you visit somebody in their house, not just about the patient, but also about the environment. Is she being cared for? Is she safe? Is she healing properly? We don’t do that here.
Again, that feels like a frequentist approach, because what we’re doing is checking a box. With the IVF [in vitro fertilization] doctors that help you get pregnant, their success score is based on whether you get pregnant or not, not if you have a healthy baby. This is a misalignment. Lots of women who go through IVF try to pick the best doctor they can find. The doctor will tell you their rate of getting people pregnant, not the miscarriage rate, which is really important.
Mr. Jekielek: By the way, what happened to the doctor who had the two hospitals that were very similar, but had these different rates of C-sections? What was happening there?
Ms. Kaplan: His premise is that it has to do with the mom being involved. He was developing a dashboard that would basically allow the mom to know all of these different things, and the medical team would have to go in and talk to her about certain things. His premise was if the mom is really involved and there is open communication, the C-section rate will plummet.
In one hospital where there was all this technological innovation, it was leading to more C-sections. The mom wasn’t at the table. The doctor would come in and say, “You’ve been in labor long enough. We got to take you into the OR.” There’s a fallacy that women are scheduling C-sections because they want to. I didn’t find that in the data at all.
Most of it happens in real time. Things aren’t going quite right and we know we have this other way of delivering. Why not just make that a preferred option when things don’t seem to go right? Maternal mortality is a big risk. There also was a lot of data I found that said that women are far more likely to have to have a hysterectomy later in life if they’ve had a C-section. It also prohibits your ability to have lots of kids, right?
It’s the only time a surgeon will cut on the same scar over and over again. Surgeons are taught to never do that, because it’s very damaging. I actually did a story about how you can find out what your hospital C-section rate is. The highest predictor of whether you’re going to have a C-section or not is not your doctor. It’s the hospital you deliver in.
Mr. Jekielek: There was a study done on which type of psychotherapy works best, but it turned out that actually the method of psychotherapy doesn’t matter. The only variable that really kind of jumps out is the identity of the psychotherapist, irrespective of which method they use. Some people are successful and some people aren’t.
Ms. Kaplan: Please tell me more about that. I’m curious.
Mr. Jekielek: Presumably, they were real good listeners, or they somehow knew how to cue in on body language. It was the therapist that mattered. They could use any method they wanted to, and they would be successful.
Ms. Kaplan: Listening is an incredibly powerful tool for healing. There’s something that stands out in research and how we identify these things, like this protocol works better than this other one. But it turns out it’s about the practitioner. We have this doctor morale problem. I hope the Broken Science Medical Society becomes a huge network for doctors to feel empowered again.
There is also a rejection of wisdom in our culture. Medicine is both an art and a science. Somebody comes in presenting certain symptoms, and you can have an intuition about it. If you entered it into AI, it might not put it all together. The last time you saw them, you remember this person mentioned they had headaches, or that they had some other symptom that now becomes very important. Again, it’s taking that prior knowledge and applying it to the patient you’re treating.
But it also has to do with experience, treating patients, and spending a lot of time listening to patients. We’re not valuing that, because we’re not allowing doctors to spend time with patients. For the average doctor’s appointment, the doctor is spending like 12 minutes with a patient. That is not enough time.
There’s some interesting work that looks at the communication breakdown between doctors and patients. It indicates that when you’re scared or nervous, you are most likely to put forward your least significant symptoms. Also, they’re thinking about how to code whatever it is that you just mentioned. There is a communication breakdown where you’re listing your least significant symptoms, and then I’m not hearing the rest.
At Broken Science, we have a class that’s coming out this summer that’s for patients to navigate their own healthcare. As a journalist I’m thinking about what questions you can ask that can help drive you to be a driver? Just like with maternal mortality, you have to have a seat at the table. These are the most important decisions you’re ever going to make in your life. You can’t be passive. Yes, you’re vulnerable. Yes, you want to get along with people. But there’s a respectful way of doing this and you don’t have to be combative. If you’re reluctant, having an advocate or somebody go with you to the appointments is hugely helpful.
Mr. Jekielek: I really appreciate what you’re doing here, because you’re not necessarily saying that you can solve this huge, giant problem. You’re pointing out some of the problems, but you’re also empowering people to help themselves in this difficult environment. How do people access the Broken Science Initiative?
Ms. Kaplan: Brokenscience.org is the mothership, and we have just redesigned the site. The back end is actually an AI operating system, so it will go in and learn what your interests are. Then it will start recommending things to you. We also realized a lot of the material was intimidating to people, so we’ve created summaries and versions of the really dense material. It is at different grade levels so that you can really come in knowing nothing. You can also go and read the original work, and all of that is free.
We’re starting these cohorts that are called societies. The medical society is the first one we’re launching, and that’s going to be a networking opportunity. There’s a huge amount of social media type capability on the back end of the site so that people can follow each other and share research. They can invite each other to events.
We’re doing this thing called Journal Club, which is taking apart the medical journal studies that will be part of the resource library for the doctors and patients. I’m not a doctor, but I’m interested in all this stuff. There will also be individual groups that will be more specifically focused on the medical profession.
The approach is very similar to what Greg did when he started CrossFit. He knew he wasn’t going to be able to save everybody, but he knew anybody who wanted to work really hard and do his methodology would benefit from it. It was a real grassroots way of building. Harvard Business School called it the fastest growing company in world history.
We’re going to replicate that. We have our personal health society that’s launching at the end of the summer, and then an education society. Those cohorts will feed into each other. With our personal health society, there will be a lot of people who do self-experimentation. I’m going to do the keto diet for six months.
Then we’re going to have doctors in the doctor cohort who can go study them and then hopefully publish that work in a journal that we'll launch in a year or so. There’s a lot of exciting stuff. Our YouTube channel has a lot of content. I’m creating explainer videos where I break down some of these concepts. I have one on induction, and I have one on statistical significance. I’m happy to do more of those.
I love it when people say, “I’ve been doing this forever but I never I can’t quite remember. I don’t quite understand. I can’t hold onto this.” Then I can think of ways that we can animate it. Our Instagram account, (at)BrokenScienceInitiative, is very active and popular.
I’m doing a new show called Emily Unleashed that looks at people who have changed a paradigm in art or science, and there’s an Instagram account for that. When we launch, it will be on YouTube and it is meant to inspire critical thinking. It talks to people about how they stood up to the status quo and it either made them tons of money or it got them canceled, but they felt they had to do it.
I want to inspire more of that American spirit rebellion. Don’t defer to authority, not on matters that are really important. Learn to listen and be respectful to each other. But there is no ultimate certainty. I am not 100 percent confident in anything that I just said to you. I’m pretty confident, but somebody could come in here and know more about something and I would be open to listening to them.
Mr. Jekielek: Emily Kaplan, such a pleasure to have you on the show.
Ms. Kaplan: Thank you so much. I really enjoyed this.
Mr. Jekielek: Thank you all for joining Emily Kaplan and me on this episode of American Thought Leaders. I’m your host, Jan Jekielek.
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