Understanding women's health care journeys
Insights from the OptumLabs Research & Translation Forum.
Overview
Disease often manifests differently in women than men. We can better address the uniqueness of women's health care journeys with a life-course approach to research and personalized treatment. There's also a lot to learn from maternal health, where many disparities exist today.
Not factoring in the distinct biology of women versus men can lead to critical gaps in diagnosis and treatment. Heart disease, the number one killer in the U.S., is an example. Dr. Paula Johnson knows sex-based research and detailed patient history can help improve outcomes.
An opportunity to take a life-course approach
Learn why Dr. Johnson recommends considering a woman's health through the lens of her entire life to understand the early warning signs of disease. Looking at women's health care this way allows treatment to be tailored for each woman and promotes better results.
Speaker: Paula Johnson, MD, MPH, President, Wellesley College
- Dr. Johnson was one of those people who I met way back in the early days of my residency, and she and I have been casual friends from time to time along the way, colleagues. She's now president of Wellesley College, which unfortunately my daughter who graduated from Wellesley just didn't overlap with her, but I'm very proud that she's the president of Wellesley, but she's also a cardiologist and a former professor at Harvard's Chan School of Public Health. She's a champion for women and women's medicine on so many fronts, from her practice and to research into how disease manifests itself directly in women versus men. Most recently she chaired the landmark report issued just a couple of months ago from the National Academies of Science, Engineering, and Medicine that was featured in the New England Journal of Medicine and a perspective in September on sexual harassment of women in medicine. Today we have the wonderful opportunity to hear her speak about women's health and framing it in terms of the value of thinking about it from a life course approach. I've seen her slides. I think we're all in for a real treat. Paula? Thanks.
- Thanks, Paul.
- Thanks.
- Well, good morning and thank you, Paul. It's wonderful to be here with you. Paul, I just want to say that was pretty generous of you to say those nice things about when I was an intern and you were a junior resident at the Boston Epi at West Roxbury VA. I don't know what I was gonna become back then, but it was generous, your statement, and I'm so thrilled that your daughter is a Wellesley alumna. You know, I don't think it is an understatement to say that we are living in a tumultuous time. It's a tumultuous time in our country and for that matter around the world. Women are front and center in that national conversation. If we think about the Women's March, the Me Too Movement, and with this we're seeing a renewed focus on women's health and the systems that provide it. As Paul mentioned, STEM fields are also the subject of the Me Too reckoning. Paul mentioned a report that I co-chaired at the National Academies of Science, Engineering, and Medicine. The first fully evidence-based report on sexual harassment in STEM fields. If you haven't read it, it's worthwhile because it is focused on academia but I think in all of our industries it gives important information. There's activism that is being born out of the fear of women losing hard fought for rights such as Roe v. Wade and the Affordable Care Act, and there are demands for the medical profession to listen to women and to take their concerns seriously. But today what I want to do is really highlight an issue that runs through and beneath all others, and that is one that has gotten less attention and that is the way that we still in many ways leave women's health to chance. Now, what do I mean by that? Simply put, we know far more about the health and disease in men than we know about them in women, and this is a legacy of decades that has really born the fact that most research is based on a male model and too often even when we include women, which we are doing more and more of now, we still are focused on and resort to one size fits all healthcare and we're ignoring what is unique about female biology, which I refer to as sex, and how that intersects with the experience of being female, known as gender. As a result, I would venture to say that women are really not reaping the full benefit of modern science and medicine. It was my desire to change the state of affairs that led me to build and found and build the Connors Center for Women's Health and Gender Biology at Brigham and Women's Hospital and Harvard Medical School. It was in 2002 that the center was founded with a mission of improving the health of women and transforming their care, and doing this through research. Basically research, studying sex differences in health and disease from more basic science to applied, across organ systems, translating science to care, influencing policy with that knowledge, and training the next generation of leadership both in science, as well as in medicine, who will transform the care of women. Just over two years ago, as Paul said, I left the Connors Center, I left my professorship at Harvard Medical School and also at the Harvard School of Public Health, to become president of Wellesley College. Now to some this might look like a great departure, but I see it as a natural extension, really the next chapter in my work to improve women's lives. Today I spend a lot of my time thinking about how to best serve our students, how to support them as they grow into tomorrow's leaders. I think about pedagogy and curriculum. I also think about how to best build a diverse, inclusive and equitable community, and so much more. But throughout that I remain profoundly conscious of the fact that health is fundamental. A unique and singular good that animates all others. Without health, we are hard pressed to really reach our full potential. This is true for everyone, women and men alike, but women, as I've said, really have faced very special obstacles. Until the 1990s women were rarely included in clinical trials, and for that matter in most of research. Investigators had really worked under the assumption that what was true for men was true for women, and many of you have probably seen articles over the years, The Yentl Syndrome, Women are not Little Men, et cetera. We now know that this was wrong and we know that from heart disease to lung cancer, from depression to Alzheimer's, women and men express disease differently. Now, there's good reason for this. Women and men are different down to the cellular and molecular levels, and it's not just our sex organs. It's our brains, our hearts, our lungs, our joints that are different. Quoting from the 2001 Institute of Medicine, now National Academy of Medicine, report, "Every cell has a sex. "Hormonal and reproductive changes across a women's lifespan "have a ripple effect on every aspect of her health," and with growing recognition of these facts things really did begin to change. In 1993, Congress passed what was known as the NIH Revitalization Act. This was signed by President Clinton at the time, and it was a law that required the inclusion of women and racial and ethnic minorities in phase three clinical studies that were funded by the NIH. Now since this time, I can remember actually first giving these talks in the early '90s and almost all the trials did not include women, women are now routinely included in trials and overall in clinical research and we've learned more about these differences in terms of how men and women experience disease. Yet what we've learned is often overlooked. Even today, many studies that include both women and men, and I'll get to this later in my talk, often ignore the differences between them. Think about what that means. When you give an average as a result, when you don't disaggregate the data, that's not really good for women or for men. It doesn't really give the right answer for either. Moreover, preclinical research including animal studies that are preludes to human studies are still often based on a male model. This is an article from The New York Times that talked about depression, and a big study on depression talked about an animal study in depression, depression we're gonna talk about, more common in women than men, and there was an irony here because even though we know this today, the study was only done in male mice and in fact there was no mention of this not only in the paper, but there was no mention of this in the article. So, if you were reading this you would have no idea what the study was based on. So, there's an irony here because even though we're on the cusp of personalized medicine, there is astonishingly little awareness of the impact of sex, the most basic genetic difference that we know of. I'm often asked, "Well, doesn't personalized or genomic "or precision medicine address sex differences?" Here's why the answer is no. Not all disorders are inherited. We may be measuring the wrong endpoints. I'll share a little bit about that when I talk about heart disease as an example. Most measurements are cross-sectional and static and quite frankly we really don't understand how it all works together, and then very importantly sex and gender interactions are rarely considered. We have had progression in the field of women's health since 1993, and I want to discuss some examples of where we know sex impacts disease. In my own field of cardiology, this is to me a good story. This is Linda. Linda was a middle aged woman, she's now a little bit older, but she had a known history of cardiovascular disease. She had actually had a stent placed in her left anterior descending artery. She also had a history of depression, she was a caregiver and she was a landscape architect. She had recurring symptoms and went to her local physician, cardiologist. She had actually had two cardiac catheterizations where they told her that actually nothing was wrong. She then found us at the Connors Center and we did another cardiac catheterization and what we did was we saw some clues but we needed to do intravascular ultrasound. This is a test that's actually reimbursed. You use a small ultrasound probe, place it into the artery and look at the artery from the inside out. What did we find? We found that Linda did not have, and this is the catheterization. I'm not gonna show you the picture of the intracoronary ultrasound. What we found was that Linda did not have what is traditional male disease. Now, women have it too but more traditional male disease. You can see this is an artery in long section with a particular stenosis. You can imagine you can put a stent in here and fix the blockage, but she had more diffuse disease. Disease that is more common in women and can easily be missed because if you can imagine the dye from the angiogram going through the artery, it may look in fact like there is no disease. When we actually did the intracoronary ultrasound we saw actual disease and we actually measured the flow across the artery and actually found that there was a specific area in the artery that had a significant stenosis. She was stented and she did well. She's come back a couple of times but overall she's living her life and living it very happily. This is, I think, one very good example of where we found differences. What we don't fully understand today is what underlies those differences, why does it look differently, and therefore are our preventative strategies and our treatment strategies the right ones for women? We don't yet know. What are the key risk factors for heart disease that we know of? Well, we know that you can know that hypertension, high cholesterol, smoking, your age and family history, just to name a few, but there's another major risk factor and one that only impacts women and that's pregnancy. What we know is that the increase and risk of future heart disease for those who experience complications of pregnancy called cardiometabolic complications is about two to threefold. Now, this is a slide that actually shows you, that green line going across is kind of the threshold for vascular disease. The bottom line with the two little bumps, that's a pregnancy. What it means is that when you experience pregnancy, it's almost like a stress test. But most women who have normal vasculatures kind of pass that stress test. You don't really reach that green line of the threshold. When you have one of these cardiometabolic disorders, preeclampsia, hypertension of pregnancy, gestational diabetes, you actually overshoot that threshold. If you look at the other side of this graph, when you go to middle age you are actually more likely to develop cardiovascular disease not only at a higher rate but earlier in life. We now know that these are valid risk factors for cardiovascular disease in women and we also know that these risk factors are actually not only important for women, but they're also important for the next generation. The children of these women actually are at higher risk. We know that by following women across the lifespan that we can identify in some places women at greater risk for future disease and implement risk reduction strategies to the best of our knowledge today. This approach, as I said earlier, if you look at that bottom line does take into consideration not only the women's lifespan but also the impact on that next generation. The question is what is it in these disorders that impact the vasculature? It's not only the peripheral vasculature, it's also in the brain. Consider that one in five U.S. women who deliver a child has at least one pregnancy that's complicated by preterm, low birth rate, gestational diabetes, hypertension of pregnancy or preeclampsia. You can begin to understand the scale of this issue and the number of women who are walking around with little awareness of their added risks. Now, I see a number of young women in the audience. I'm gonna ask those of you who might have had a pregnancy whether your primary care doctor, when screening you, has asked you whether or not you've had one of these disorders. Just raise your hands. Okay, that's a problem because I know that some of you have had children, and the fact that I don't see one hand raised is an issue because we know this, it's in the AHA Guidelines, and not one of you has been asked. This is a problem. It bears noting that cardiovascular disease is the number one killer of women in the United States today and half of American women will develop heart disease sometime in their lifetime. The ability to learn more about risk in women to prevent cardiovascular disease is important and taking that life course approach is also important. Clearly the link between pregnancy and complications of CVD is very important, and all too often obstetrics and gynecology and issues of other aspects of internal medicine are siloed and we do not connect the dots. So far I've been talking about physical health, but mental health is equally important. Here too we see sex linked traits that are likely playing a very powerful role. Depression is an issue that's near and dear to my heart, and indeed my family experience is really what led me to medicine and one of the things that led me eventually to women's health. I had a very dear, my maternal grandmother was a wonderful influence in my life. She was not college educated but traveled, was truly brilliant and loved to dance, really enjoyed life until I was about nine or 10 years old and she began to ... She stopped working, she wouldn't eat. There were a number of other symptoms she exhibited. For those of you here in this room, I'm sure it's not a surprise that what she had was depression. Back then it was actually quite difficult to get an initial diagnosis. By time we did get a diagnosis though, she was on a downward trajectory that eventually led to her very premature death. But in the years since, we've learned quite a bit. We've learned that women are 70% more likely than men to experience depression over the course of their lifetime and we also know that women are at twice the risk of experiencing major depressive disorder compared with men. Research has clearly demonstrated that sex hormones play a major role in the development of the brain regions that regulate mood and the response to stress. We now know that major endocrine changes throughout a woman's life, including puberty, pregnancy, and menopause have been directly linked to increased risk for the disease. Just consider that 40% of depressive symptoms amongst mothers were experienced during that postpartum phase. At the same time we've been working to understand the links between depression and other health conditions. Major depression has been most commonly associated with cardiovascular disease. The comorbidity of these two diseases is likely to be one of the primary causes of disability in the world. Against this backdrop investigators have really begun to hypothesize that one reason for women's high death rates from cardiovascular disease may be due to their unrecognized and untreated depression, and remarkably they are tracing risk factors back to fetal development, back to when the brain begins to sexually differentiate. Once again, we're reminded that a lifespan perspective is essential if we are to get at the root of what causes disease. One question is whether the study of depression from fetal development across the lifespan gives us clues to both of the biology of clinical and clinical expression of these diseases. This is a complicated slide but I just want to give you the gestalt, which is that major depressive disorder is associated with abnormalities in the brain circuitry that are associated with the stress response. That's kind of over to the left. That stress response is regulated by the hypothalamic-pituitary-adrenal axis or the HPA axis. This includes the hypothalamus, the amygdala, hippocampus, anterior circulate cortex, and the ventromedial prefrontal and orbitofrontal cortices. These are areas of the brain that develop in sex dependent ways, that's that brain up there, and function differently across the lifespan. I just want to give you a sense of where the science is moving. One of my former colleagues and the person who is the director of research at the Connors Center, Jill Goldstein, is really leading the way, she's now at Mass General, really leading the way in studying this connection between depression and the comorbidity of cardiovascular disease. These disorders, depression and cardiovascular disease, are also risk factors for memory decline and Alzheimer's disease. This disease, Alzheimer's, is more common in women. Just to connect the dots, a women's lifetime risk of developing Alzheimer's is almost twice that of men and it isn't just because women live a few years longer. This disease is projected to cost the United States upwards of $300 billion a year. Investigators are now finding as they've begun to look at sex differences in the biology are finding that female biology plays a role. In particular the impact of hormonal changes at menopause and sex differences in gene expression. So, important work that is moving forward. There are other organ systems as well for which there is good evidence that it's important to look not only at sex differences but how these differences are looked at across the lifespan. If we look at pulmonary disease, for example, diseases such as across the top, asthma, primary pulmonary hypertension, LAM, COPD, lung cancer and certain pulmonary infections, each of these is different by sex and different and they evolve across the lifespan. Even when we've done good research, when we've come to understand important differences between women and men, we all too often fail to apply this knowledge to clinical care. One place we see this is with drug therapy, and we're beginning to understand how women and men may process drugs differently, and the FDA is really moving forward today on these issues. Eight of 10 prescription drugs that were withdrawn from the U.S. market from 1997 to 2000 posed greater health risks for women. In 2013, for the first time, the USFDA lowered the recommended dose of a drug for women, and the drug was Ambien. They had found women were really sleepwalking and were given twice the amount that they should be. In fact, what was really interesting was that the data were all there because the FDA had the data. It just hadn't been analyzed. So, important. Just as some drugs may be riskier for women, others may be more beneficial. Now this has been found, for example, true for a particular chemotherapeutic agent in lung cancer. If we just think about aspirin, aspirin is beneficial for women but in a different way than it is for men. Doesn't prevent heart attacks, it prevents strokes in women over the age of 65. Here's an example of a current epidemic, nicotine and opioids. This is an advertisement. The FDA recently held a conference to explore sex differences and gender differences in opioid and nicotine use, in the dependence and recovery. We still haven't scratched the surface of the work that needs to be done. In 2009, an NIH report, if you were to read it at face value, would indicate that the job was done. In fact, so often when I've talked about this issue people raise their hand and say, "I thought that this was in the past." Well, answer is no. That is just not the case. In 2014, at the Connors Center our group in partnership with the Kaiser Family Foundation and the Jacobs Institute for Women's Health at the Milken School of Public Health at GW produced an evidence-based policy report to identify the gaps in scientific research as it pertains to sex and gender. This report, through the help of working with Elizabeth Warren, whose mother by the way had died suddenly of a heart attack and had had symptoms that had been unrecognized, through Elizabeth Warren's work, it led to a 2015 GAO Government Accountability Office report that really looked back at the work that was done since the NIH Revitalization Act in 1993 to say, "Okay, where have we come?" This was the report and here's what they found. They found that NIH has made important progress. They've made important progress in terms of including women in clinical trials. That while women are at least equally represented in clinical research funded by the agency, NIH overall, currently there was no data on the inclusion at the institute or center level, so it was just kind of high level aggregate data. The Women's Health Advisory Committee had no access, that's the committee that was actually tasked at NIH with overseeing the work, had no data on inclusion or reporting at the institute or center level, and there was no collection of summary or of the number of studies required to determine if sex differences occur or whether studies required to conduct these analyses actually complete them. So, without these data it's impossible to effectively oversee implementation and assess the necessary changes to the inclusion policy. This was the first time that a real look was made at the progress from 1993. Once this GAO report was published, immediately the NIH agreed with the GAO's recommendation and said that they would take plans to take action. So, what happened? Two months after the report was published, the NIH stated that it would require the inclusion of female animals and cells in preclinical research and it would require the inclusion of adequate numbers of women in clinical trials to achieve meaningful results, and that includes phases one through three. Now, the GAO report also recommended that we should evaluate publications and recommended analyzing journal articles to determine whether data were being analyzed and reported by sex. It was also one of the recommendations in our report. In response, two of my colleagues, Molly Carnes and Stacie Geller, did a study. They looked at 782 randomized trials in 14 leading U.S. journals that were published in 2015. 142 were primary reports of NIH funded trials and they were done in the U.S. so it made them eligible for this analysis. 107 of the 142 studies included both sexes, so they were eligible. Now, we've made progress because of those 107 studies, 81% enrolled greater than 30% women. Now, is 30% enough? Not clear, but that's progress from 1993. What they also found unfortunately was that of those 107, only 26% reported at least one outcome by sex or included sex as a covariate in the statistical analysis. 74% did not mention whether sex was included in their analyses, didn't report any sex specific outcomes, and didn't provide any explanation. These data show that in fact and with regard to reporting there is no statistical improvement since 2009 when a similar study was done. Interestingly, also another question I sometimes get asked is, "Well, was there a difference "according to the sex of the author?" and there was not. There was no difference according to the sex of the lead author. I would venture to say that we are truly not making the best use, getting the best value out of federal dollars in biomedical research. Now, what I would say is for those of you in academia, we know that publications are the lifeblood, it's how we're evaluated, and our journals hold a very special and powerful place in influencing how we advance and think about sex and gender. So, there is work to be done in this area. It does not take regulation. It just takes the leadership of our journals to be aware and to begin to think about what are some of the ways in which they're going to accept articles. So, where do we go from here? Well, the NIH is really promoting a new policy, not a requirement but a guideline on using sex as a biologic variable in study design, so that's good news. They've also created another set of guidelines, sex and gender equity in research or SAGER guidelines. This is all good news and progress, but remember that these are guidelines, they are not requirements, and guidelines are only as good as they are followed and enforced through the NIH. I've shared with you this morning why it's important to consider sex across the continuum of research and in later research gender as well from preclinical to clinical trials, to translation to clinical medicine, to measurement of outcomes, and without a doubt as we think about how we include these issues in research, it's a matter of equity and it's really a matter of doing the highest quality research and getting the most value from the research that we do. Hopefully today I've also convinced you that taking a life course approach is important. I've only given you a brief tip of the iceberg, but enough that I think it's pretty clear that this life course approach is important. Women's health I truly believe is an issue of equity. I gave a TED Talk a while ago and I said it's an issue of equity that is as important as equal pay, because it is about our health, it is an equal rights issue, and how we carry out our research is a matter of quality and value. Making the most out of the dollars we invest in research. Now that I'm in higher education, I think of young women who we are educating for a lifetime of learning and a lifetime of making a difference in the world, and for them, they have to be as healthy as they can be, both physically and psychologically. Their future depends on our ability to do accurate science that takes female sex as a biologic variable, gender, and also considers the complex nature of women's health across the lifespan into account. Their future depends on it and I would venture to say all of our futures depend on it. Thank you.
Pregnancy and childbirth are important parts of many women's health care journeys. Yet maternal care quality varies a lot across the U.S., including rates of unnecessary C-sections. Dr. Neel Shah knows innovative health system design can help reduce these disparities.
Improving maternal and child health
Childbirth is one of the most-used health care services, yet the most uneven in terms of quality. See how Dr. Shah believes science and engineering principles can make it more equitable for moms and babies.
Speaker: Neel Shah, MD, MPP, Ariadne Labs and Harvard Medical School
- Neil is an obstetric and gynecologic physician who has, in many ways, deeply helped rethink the ways in which care can be delivered. Particularly for pregnant women. And one the really terrific organizations that he works with, that he may be speak about as well, is Ariadne Labs, which is also located close by in the Fenway park area. It was founded by Atul Gawande, and has focused on really improving health at scale among, for a number of conditions, not only in the U.S, but globally. Neil, I really look forward to hearing what you have to tell us. Please come on up and you have the mic.
- Darshag, thank you so much. I think that was a prior fine introduction, you know, I'd add that I'm a dad, so I come at this as a fellow human being. I'm an obstetrician, so I think about this as a clinician and I'm a scientist and a little bit of an advocate too. There's meant to be a line in the sand, I think, between scientist and advocacy. Often, you know, science is supposed to be objective and neutral and in advocacy you're supposed to have a strong opinion, but I think often impact comes from coordinating the two. So, I guess what I have to say first, is that child birth is the highest value service that our delivery system provides to society, in my opinion. But I also think just, you can make a strong case. It's the most utilized health care service. If you'd take moms and babies together, it's 25% of all hospitalizations. It's cumulatively the most costly. So, if you'd take our entire 17 trillion dollar GDP and spread it out across the table, you'd be able to see that hospitalizing moms and babies, with your naked eye, it's 0.6% of our whole GDP. And it's by far the most uneven, when it comes to quality, which I'll show you in a second. And yet we don't often get to talk about it in forums like this. So thank you for that opportunity. And I want to talk about how we can use science and engineering priniciples to make the system more reliable and more accurate for our moms and I also want to talk about how we can develop a market place and ultimately drive those improvements to scale. So that went off on purpose, it's not a mistake, I thought I'd go acapella for a moment. And just say a little bit about, you know, what it is that science ought to get us. In almost every domain of our lives, science makes things simpler. The way we get around, the way we put food on the table, to the way we communicate with each other. But in health care, we generally deploy science in ways that make our lives harder. There are many examples of this. This is a labor and delivery room at the Beth Israel Deaconess Medical Center, where I work. It's not to knock them, but I don't know how many ways of throwing things away you have in your hospitals. This is directly opposite a mom's head wall who is in labor and we've got seven ways of throwing things away. And this is what she looks at. Do you know what they are, real quick? So, the yellow one is where we happen to dispense the oxytocin bags, because if you pour them in to the sink and they leech out into the Boston water supply, everybody becomes nices to each other. So you can't have that happen, you gotta ... Then you've got the world's largest shrubs container. A recycling bin, a bio hazard bin, a normal garbage, a soiled linen container and a sterilization tray. This is sort of our M.O. in health care, every time we deploy it without a system and it creates more decisions that people like me have to make, more options and more ways that we can mess up. I know this is a data crowd, which I realized walking into the room and I have maybe two graphs in this entire thing, this is one of them. And I tried to make them as ambitious as possible. This is the entire story of the last half-century of health care, which is time on the X axis and capability on the Y axis. And the thing is, we're directionally correct. Right, the left-hand side is like 1955. Dwight Eisenhower has a heart attack, as the president of the United States. And a state of the art therapy for Dwight Eisenhower at the time was basically to sleep it off. Like, they prescribed a month of bedrest. And today we would've ... This is David Cutler's work. Like, we would have spent, you know, $50 000 extra on his health care, he would've gotten a beta-blocker and and angiogram and maybe a stent, but he would have lived a decade longer. So we spend more, but on average we get things right. And the reason that that's not good enough, is because being directionally correct means we get things right on average. And when people get hurt in our health care systems, they don't get hurt on average, they get hurt on the margins. There are two margins that we should care about. There is one where we do too little too late and then there's one where we do too much too soon. The too little too late problem has been in the focus of patient safety in the last quarter century. The too much too soon problem, I would argue, is something that still lacks a delivery system solution, broadly. There are many examples of too much too soon throughout health care, but the most stark, not only in my field, but in all of health care delivery, is the decision to deliver a baby operatively. So C-sections are the most common major surgery performed on human beings in 2018. They're the most common major surgery performed on Americans and it's the most common surgery that's been performed on the people in this room. And the thing with it is, it's a life saving surgery, but the problem with over-using it, is that, well, you can't get surgical complications unless you do surgery, so that's not great. So the odds of exposing a young, otherwise healthy mom to hemorrhage, sepsis, organ injury about three times higher by the doing the surgery than not. It's also the fact that it's a lot harder to take care of a new infant with an incision than without one. There's also the fact that obstetricians like me are the only surgeons that routinely cut on the same scar over and over again, because moms have more than one baby. So, if you're like a trauma surgeon, or a neurosurgeon and you have to go back and operate on a place that you've operated before, that's usually a bad day in your work week. But for me that's like a Tuesday. And the first time that you do a C-section, it's an easy surgery, you can train an intern how to do it in, like, a couple days. Second time it's a little more complicated and the third time it's like operating on a melted box of crayons. And sometimes the placenta, which is an organ that only exists in pregnancy, it's a big bag of blood vessels, it gets 25% of everything the heart pumps, gets caught up in all that scar tissue and women bleed to death. So, in sub-Saharan Africa maternal mortality has been going down with a trend line for 20 years and in the United States of America it's been going up, with a trend line, for 20 years. This is the half century story on C-sections. Not that long ago, like, a generation ago, from the moms today, the national C-section was only 5%. And then something happens in the early seventies and it rapidly doubles. Five years after that, it more than triples. Five years after that, it quadruples and then guess what happens five years after that? It quintriples. And then, you know, at the end, in the nineties, you guys remember the nineties when like AOL CDs were being mailed to you, it was a very different time. And there was a lot of concern about the end of the millennium. And we set a bunch of population health goals that we called Healthy People 2000 and they were about everything, like our target BMI as a nation and also our target C-section rate, which, at the time, was recommended to be at the top of the WHL recommendation at 15%. They said about 10 to 15% would make sense, so we were aiming for 15%. And early nineties, we bent it and in the mid-nineties we completely changed our mind and reversed course entirely and then we do that. This is a 500% increase in the use of the surgery in the last generation or two of moms. And what's particularly troubling, is we have literally no idea why. There's a ton of conventional wisdom about what's driving it and all of it is wrong. So what sets us of is the introduction of technology. And everywhere in the world where there's electricity within three years, we have this capacity to monitor fetal heart rates in real time. The only thing it does, reliably, is increase C-section rates. It does not reduce neonatal mortality or even morbidity on average. But it's not what explains the whole trend, because it saturates the market in three years and the way that we used it in the seventies, eighties, nineties, 2000s and 2010s hasn't really changed. Then there's this period where we bend it down, where we encourage women who have had a C-section the first time, to try and have a normal delivery the second time. Right now, in 2018, if you have a C-section the first time, you have a 90% chance of getting a C-section the second time whether you need one or not. And it suggests that this effect is cumulative. You know, just moms having more babies. But then you graft the primary C-section rate at the same time, and they're like railroad tracks. They go down at the same time, they go up at the same time. So something else is driving this. I mean, well, moms look different today than they did in the seventies. There's more obesity, hypertension and diabetes, moms are older, there's more IVF, there's more octo-moms. There's one octo-mom, just to be clear. And it turns out, demographic shifts don't explain this very well either. For a healthy 18-year old today, just over her life time, her odds of getting a C-section doubled. So whether you're thin or healthy or young, doesn't seem to make a big difference and there are still more young people than older people having babies, so demographic shifts don't explain this. Medical malpractice or reimbursement don't explain this, because even during errors our policies have been unchanged, this has just continued to skyrocket and women's preferences don't explain this. It's less than, you know, it's always memorable when a woman requests a C-section and it ends up in the media. There's a U.K Daily Mirror story from a couple of years ago called, it was like, Too Posh to Push and there was a picture of Victoria Beckham. A few people in this audience get it, students generally in 2018 don't. But the truth is, we have like no idea. So one way to explain it is not look at cross time, but at freeze time and look across geography. Which is the kind of thing, you know, Ariadne Labs has the capability to do. And if you wondered, this is a one dimensional graph, it only shows C-section rates, from a nationally representative sample and every dot on here is a hospital in the United States. What it's showing you, is that C-section rates vary from seven to 70%. And there are, like, other health services Whose research is in here and you can tell me if I'm wrong about this, but I'm not aware of another health care service that varies by an order of magnitude nationally. It's also the case that 70-percenters will probably say that they have a really tough patient population that justifies it. So there's various ways of accounting for risk. You can either risk adjust post hoc, or you can exclude people ex anti. And in my world, because most people were healthy, it turns out they're equivalent. But if you're to exlcude high risk women and only look at the lowest risk women, the ones who are fullterm, have only one baby and they're pointing the right way to go out, you don't see 10-fold variation, you see 15-fold variation. This is the only health care service where, after you account for risk, you see more variation, not less. And what that means, that in 2018, the biggest risk factor for the most common surgery we perform, is not a woman's preferences or medical risks, but literally which door she walks through. Which, in a lot of markets across the country, like Boston, where, you know, if you have a heart attack and you fall one way, you go to one hospital and if you fall the other way you go to a different hospital. Like, it's awkward, which side of the street you're on, Brooklyn Avenue, can determine whether you're gonna have a C-section more than your risks or preferences. So that set me off on a journey about five years ago, to try and understand why. This is a map of Boston, it covers the area that we're in now, which is a three-mile radius and it points out that there are three major Harvard teaching hospitals within this three-mile radius. They all fundamentally take care of the same people. And I got to deliver babies at all three of these hospitals, within a few months of each other and transitioning from my training program at Brugmann and Mass General to my current role at Beth Israael. And to me, by the way, they all have very different C-section rates; to me, it could feel like a lot more work to take care of the same patient depending on which hospital I was in. Do you buy that? The thing is, it wasn't entirely clear to me why. Some folks at Harvard Business School helped me to make a cartoon to understand it. Which is to think about our labor and delivery units, or really any service line in our hospitals as a pressure tank. Every pressure tank has a certain capacity, so what this means is, you know, there are no roles for how many labor and delivery rooms you need, based on the volume of the patients you take care of. I found two hospitals on the West Coast, that have the same number of labor and delivery rooms, and one place delivers twice as many babies per year as the other and they both think that they're at their capacity limit. The only way that's possible, according to Isaac Newton, is if one place is moving people through faster. So then we had a project and it turns out that every public facility has a fire escape map and that that map is a floor plan. So we had hospitals across the country send us IPhone pictures of their floor plans, and we developed the ability to predict their C-section rate off of their floor plan. Every pressure tank also has a certain amount of gas in it, which is like your workload and it turns out, between Brugmann and Mass General, there are very different policies for how you manage the same patient. Every patient with pre-eclampsia at Mass General gets put on a magnesium drip, and only the most severely sick patients at the Brugmann get put on a magnesium drip. And if you're a nurse, that is a very, very big difference in terms of the amount of work. And then, every system has, you know, based on the amount of work and the capacity to get the work done, some people are just willing to try harder. And that's a manageable thing too. Which the business folks helped to think of in terms of managing motivation and accountability. So we did a study where we threw 53 hospitals together, we took all of their claims, from across the country, for 220 000 patients, who delivered at their hospitals over two years. We could observe a lot about the facility, the kinds of things that normal health service researchers look at, like their case mix, you know, their size, whatever structural measures you would use and their claims. And then we used some things called the World Management Survey, or a modification of it, where you basically talk to a service line manager for 45 minutes on the phone about they manage their unit and then you score their responses on a Likert scale from one to five. And this predicts a lot of things. It predicts profitability in manufacturing, it predicts odds of dying after an MI in cardiac ICUs and in our case we tried to predict risk of caesarian, hemorrhage, financial efficiency, a lot of things. And what we found is that, after accounting for fixed characteristics of a mom walking into a hospital and every fixed observable characteristic of the hospital itself. The last and final thing that determines if the mom is going to have a C-section or hemorrhage is the ability of the hospital to manage the complexity of the system, basically. In a nutshell. So just a quick word on what that implies about how we get out of this. There are only two causes of human fallibility. One is ignorance, which is not knowing the answer and the other is ineptitude, which is knowing the answer but failing to execute on the knowledge that you have. And the reason that's relevant to this, is what follows from it about the solution. If the problem is that people don't know what they're doing, you fix it with education and the reason that matters, it's that what the professions do. That's what, like, my American College of OBGYN, like that's the prom that they own, is educating and steering my profession around instead of the science. If you know the answer but fail to execute, there are only two possibilities again. You're either doing it on purpose or you're not. And if you're doing it on purpose, the solution is fixing incentives. And if you're a policy maker, that's your whole wheelhouse. But what we found in doing this work, and, you know, this was like an Americana tour, visiting 53 hospitals to stand this up, it took years to do. Most people are well informed and well intended and are failing anyway, because the systems are not set up to make the right thing to do the easier thing to do. Right, like that pressure tank funnels down to this dichotomous choice, between persisting with the woman in labor, who's taking much longer than average, has ambiguous fetal heart racing, or just playing the rip chord, and it's not really clear who the owner of that problem is. I showed you the garbage can example of unnecessary complexity in the system. That's the most mundane example I have. Here is the complete opposite extreme. It's part of this project, I visited a hospital called Magee Hospital for Women, in Pittsburgh. It's part of the UPMC system. It is not the average hospital that delivers babies. Most of you and most Americans today are born at hospitals that do 500 to a 1000 deliveries per year. The labor and delivery units are in some retro-fitted corner of the hospital and it's the bass-leader for the whole system. It's a high-cost, thin-margin service. Magee is like a 100-year old free-standing women's hospital, where there are like stautes of women, pregnant women in the lobby, and they do about ... They do well over 10 000 deliveries a year. It's atypical. They're in Pittsburgh, so they have a huge catchment area and take care of very sick people, and despite that have a relatively low C-section rate. So I just showed up one day to try to understand what was going on there, I mean I called first and then I showed up. And then they gave me a tour and this is a picture I took with my IPhone, of the person who I think has the hardest job in all of health care delivery. Her name is Vivian and she's the charge nurse, the nurse in charge of the unit for that day on that shift. Let me tell you what she's doing. She's got two computer screens in front of her, that are helping her manage her nurse staffing assignment, so figuring out which nurse goes to which patient. Then she's got four more giant LCD screens, that are her bed-management system, to figure out which patient goes to which bed. Then she's got eight more screens that are the fetal heart tracings, and you know, other people have to observe those too, but they're like, "Vivian while you're there, "you might as well pay attention." And then there's a dry-erase board, with 30 rows and 15 columns, where she manually reproduces most of that information, because she doesn't like the way it's displayed on the board. And there are two things that this made me realize. The first is that she's an air traffic controller without an air traffic controller's tools or support. I actually visited the air traffic control tower at Logan Airport to get a head-on-head comparison, and you'd never see one person managing that much complexity in an air traffic controller tower. Because it would be unsafe. The other thing that I've realized is that our labor and delivery units are functionally ICUs. So what defines an ICU, is not a ventilator, but to a health services researcher an ICU is the ability to staff one nurse to one patient. The cardiac ICU does that, the labor floor does that. The cardiac ICU has telemetry and can monitor vital signs in real time, so can we, that's what all those monitors are. Cardiac ICU titrates medicine on a minute to minute basis, so do we with oxytocin. The only difference between the cardiac ICU and the labor floor, is that our operating rooms are actually attached. Which means we have the most intense treatment area of the entire hospital for the healthiest patients. It doesn't take rocket science to figure out what's going on. We're taking 99% of American women, put them in ICUs and surround them by surgeons. I wanna just briefly talk about the way we're approaching unwinding this. It starts with having basic goal clarity. So if you were to ask anybody who manages labor and delivery units or oversees the women's health service line, what the goals are for caring for women in labor. Or even the frontline obstetricians and nurses. They will tell you healthy baby, healthy mom. And then probably drop the mic. The reasons these goals are necessary, but insufficient because, one, often it creates a false choice between the mom and the baby where it doesn't exist, and two, and more fundamentally, it ignores the fact that women have goals in labor other than emerging unscathed from the process. Like, survival is the floor. We're not even doing that particularly well. But we should be aiming for the ceiling. Which is making sure that the process is not only safe, but also supportive and empowering. And then there's the fact that this is the only windows in health care, where you can influence the long-term wellbeing of two people, two human beings. Right, because we often don't have line of sight until after what happens when people leave, but there's the whole melted box of crayons things. And the melted box of crayons happened six years after the index C-section that I do. As does the maternal mortality, that may have been caused by it. And what follows from having this kind of goal clarity, like, if we can have two goals, we can have three or four, right? Is what we should be doing reliably for every woman every time during every assessment in labor. Which is, you know, we're checking in on the mom, we're checking in on the baby, we're checking in on the progress of labor, as three independent things, that right now get conflated all of the time, not only on the front line of health care, but at the highest levels. At the Newman's editorial table and in our professional leadership. It turns out that a high risk pregnancy and a high risk labor are not the same thing. They are not even necessarily related. Like, you can have hypertension. Like this increasing number of women show up on our labor floor, thinking they have a high risk pregnancy. You can have hypertension and not only labor normally, but the most likely thing is that you'll labor normally. And in the way that we use our data, because there are a lot of data nerds, we reinforce that bias, because we adjust for things that are risk factors in pregnancy, to understand how we ought to be managing labor. And it just reinforces this lack of clarity. So what we're doing is engineering a different process for managing this and you know, often, you know, reliability and health care systems are thought of in terms of forcing functions and checklists. Our solution is not a checklist, because checklists require a natural pause point, which is before a surgeon picks up a scalpel. And labor and delivery doesn't necessarily have a natural pause point. Also, checklists are not meant to be pushing back against people, they're meant to be the reinforcing things we think we're already doing, but are not doing reliably every time. So, we developed a way of thinking about this for C-sections, where we put, you know, the 150 ICD-10 codes that you can apply to C-sections and the 27 indications into a simple table. We just labeled them in terms of recent for a mom, a baby and labor progress and then we subdivide it into the clear reasons to do it and the fuzzy reasons to do it. And this is really important, because ultimately this and many other things in health care are timing failures. We're either acting with too little too late, or with too much too soon. In an emergency, everybody in the world has clarity on when to act, you should act now for a C-section. Most of the variation in the country and most of the harm is from lack of clarity about when to prevent the emergency. And that requires a different process. And the thing is, in 2018, there's no objective way of knowing how a big a baby is until it's out, right. So at 3 am, when a woman's been pushing for two hours or three hours, and then four hours, you kind of have to use your Malcolm Gladwell 10 000 hours of experience and just like judge if it's gonna happen or not. And that's okay, you know. Clinicians feel so beaten down by being told what to do, this is very clearly one of the domains where we should allow people to use their judgment. But we should make sure they're using ... They're making judgments with all the information that ought to be available to them in the room. And it turns out that information lives in the brains of multiple people, not just the delivering provider, but the nurse who spends more time at the bedside than anyone else and the woman herself, who can tell you things that no one else can, like her energy to push. And right now, there is now way for these three people, who come together randomly, for every woman every time, everywhere in the world, to very quickly become a high performing team, for one of the most important moments in our lives. So we just organized a way of doing that. It's very simple, it's not a widget, it's not a block chain, it's not an app, it's a totally analog whiteboard that sits opposite the mom's head wall. We got rid of the trash cans. And it's big enough that she can see it, it's simple enough that she can understand it and it just does four things. It names everyone on the team, one, because it's nice to know people's name, but also because it gives everyone an opportunity in the permission to say something when it counts and we put the mom at the center of the team. Then it creates a field for things only the mom can tell you so that she has an active role in giving input. There's a third part where you itemize the plan for the mom in terms of mom, baby and labor progress, it's three different things so that they don't get conflated. And the fourth part is you just say when you think the team will get back together again to talk about the plan. Doesn't have to be a time, it can just be, like, when you you think you want an epidural. And that avoids the problem of moms feeling like the way you probably feel when you're held on the tarmac and don't know why and the pilot just doesn't come overhead, right. That's how it feels like for most women today. And we're testing it in a different way too. We're not doing a giant RCT, we're spending the money that we could have spent on an RCT, on a phase one trial. We're doing what I think Marc would do, if they're going after a 110 billion dollar problem, which is what this is. We're doing a feasibility trial first and we're not doing it at the big tertiary medical centers, we're doing it in community hospitals where real Americans are born. So we're at South Shore Hospital, here near the Boston hub, later today I'm going to Tulsa, Oklahoma, where we're testing it and then out in the Seattle area. It turns out it's an enormously complex trial because these teams come together randomly, so the only way to do it is to train every clinician on how to do it, and so it's hundreds of clinicians who will deliver tens of thousands of babies across three different geographies. It's very, very complicated. But what we're doing is, you know, there are a million things that we know are effective and very few things that we know are doable. And we're doing the trial that proves it's doable first as a way of getting the scale. I have gone over time, so I think I'm gonna stop there but hopefully that at least gives you a sense of why this issue was so important, why it deserves more of our attention, as people who think about the health care system more broadly, and also the potential for us to do a lot better. So thanks a lot.