Nearly 100 health economists from across the United States signed a pledge urging U.S. presidential candidates to make chronic disease a policy priority. Karen Eggleston, a scholar of comparative healthcare systems and director of Stanford’s Asia Health Policy Program, is one of the signatories. 

The pledge calls upon the candidates to reset the national healthcare agenda to better address chronic disease, which causes seven out of 10 deaths in America and affects the economy through lost productivity and disability.

Read the pledge below.

Non-smoking campaigns that tell teenage boys they will get lung cancer in 30 years if they don’t stop smoking just don’t work.

“But prevention programs that tell them that girls don’t like smokers make them go pale with fear,” says Keith Humphreys, a professor of psychiatry and behavioral sciences.

Humphreys, an affiliated faculty member of Stanford Health Policy, told an audience at the World Economic Forum in Davos, Switzerland, this January that the better approach to public health campaigns are those tailored to the realities of the human brain.

One of those realities is that our brains have evolved to be vulnerable to addiction, especially if we live in the lower-income tiers of society. An understanding of our evolutionary vulnerability to drugs and alcohol can help us to design effective public policies, Humphreys told the Davos audience.

“Primate research indicates that there may be a political and economic dimension to this,” he said. “When lower primates form a hierarchy, those at the bottom undergo a change in their dopamine system. This makes them more likely to consume drugs in an addictive fashion.”

Addiction can happen to anyone at any level of society — the current opiate epidemic is a case in point — but if you look at wealthy societies, those who have less economic and educational resources are more prone to addiction.

“So as inequality worsens, we really have a risk of creating a disempowered underclass of people who are literally sedated by ever more available psychoactive substances.”

Humphreys is on the NeuroChoice team at the Stanford Neurosciences Institute who attended the forum to present their research into the neural basis of decision-making and how these impact public policy.

He says in this video that neuroscience reveals addictive drugs work on precisely the same brain systems that guide our survival decisions. This is compounded by industrial global capitalism, making the exposure to psychoactive substance nearly universal.

“These two combined realities — our evolutionary conserved vulnerability to addiction and the development of a production and transportation system that can deliver substances worldwide — is why one in six deaths on the planet among adults is attributable to psychoactive substance abuse,” says Humphreys.

Stanford researchers are going after the problem in two ways. First is to use neuroscience to unravel the mechanisms of addiction in the brain. Then, they work directly with public policymakers, such as those who regulate the tobacco, alcohol and pharmaceutical industries, as well as those who oversee health-care and criminal justice systems.

“We communicate to our friends in the policy world what science has to teach about addiction and how you can use that information to do a better job at protecting people and promoting public health,” he said.

He said one of their key messages is that psychoactive substances are not ordinary commodities that should not be regulated.

“That’s probably true for broccoli, but it’s not true for psychoactive substances because they impair our brain’s ability to value things,” he said. And that is why public health policies must take into account the evolutionary-conserved circuits in the brain.

“The magnificent decision-making organ that evolution has bequeathed us is vulnerable to addiction, perhaps particularly if we live on the lower tiers of society. This creates a risk for humanity,” Humphreys said. “Karl Marx was worried that religion would become the opiate of the masses. But if we don’t use neuroscience to make better treatments and better policies regarding addiction, the opiate of the masses will be opiates.”

What is the best way to measure returns on investments in health care?

Does the World Health Organization’s approach help developing countries allocate their limited health-care resources wisely?

What are the economic implications of the global rise in non-communicable diseases?

These are just a few of the global challenges taken up by health economics experts at the third annual Global Health Economics Consortium Colloquium at the University of California, San Francisco.

At the core of the conference is the growing field of health economics, and why cost-effectiveness analysis is fast becoming the underpinning of successful health policies.

Not only is the field expanding, so is the collaboration among researchers and faculty at Stanford Health Policy, UCSF Global Health Sciences, and the UC Berkeley School of Public Health, co-sponsors of the Feb. 12 event.

“It’s been great to see the meeting evolve from a show-and-tell to a platform where we can have nuanced discussions about the challenges and controversies in the field,” said Dhruv Kazi, an assistant professor of medicine at UCSF who helped organize and moderate the event.

Some 180 health policy experts, researchers and speakers representing 11 universities, six non-profit organizations and five for-profit outfits attended the daylong conference on the UCSF Mission Bay campus.

“By building bridges between our universities, we create a space where thought-leaders and students alike can engage in discussions to challenge working assumptions and also spearhead innovate strategies and solutions,” said James Kahn, a professor of health policy and epidemiology at UCSF and the director of the consortium.

The Consortium — known as GHECon — was awarded a five-year cooperative agreement of up to $8 million by the CDC to conduct economic modeling of disease prevention in five areas: HIV, hepatitis, sexually transmitted diseases, tuberculosis and school health.

Taking a break during the third annual Global Health Economics Consortium Colloquium at UCSF on Feb. 13, 2016. Photo by UCSF/Cindy Chew.

As global economies remain turbulent, Kazi said, governments and donors have become increasingly cost-sensitive and want to better understand the societal returns they are getting for their investments in health.

“That enhances the influence of our work, but also increases the scrutiny it receives, creating an opportunity for the community to have an honest discussion about the challenges and opportunities that lie ahead,” he said. “And that is precisely the platform GHECon sees itself becoming.”

Some of the tough challenges consortium members are undertaking:

1. The World Health Organization recommends using per capita GDP as a benchmark for how much money countries should be willing to spend on health-care interventions. GHECon researchers have shown that this approach is problematic and does not always help countries allocate their limited health-care resources optimally.
2. Economic evaluations have typically only considered health-care costs, overlooking the lost income of patients or caregivers during hospital stays. GHECon researchers are working on ways to value this lost productivity in an effort to estimate the true cost of a disease and, conversely, the benefit of its alleviation. 
3. Cost-effectiveness evaluations traditionally are concerned with how efficiently health-care resources are utilized by asking questions like: How many lives can I save per million dollars invested? But society may care about other benefits that go beyond efficient use of resources, such as reducing disparities by helping the most vulnerable sections of society and alleviating poverty.

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Mark Sculpher, one of the leading health economists in the world, gave the keynote address about his efforts in the UK to use cost-effectiveness analysis to inform decisions at the National Institute for Health and Care Excellence.

He said there are two big challenges today: defining cost-effectiveness thresholds that are meaningful, and determining how policymakers, donors and payers make decisions when there are multiple criteria and perspectives.

“The realities of decision-making inevitably involve a whole host of considerations,” said Sculpher, who is director of the Program on Economics Evaluation and Health Technology Assessment at the University of York. “Ultimately it’s about what is this measure of benefit that we want to maximize — and how do we invest in it.”

Stanford Health Policy’s Douglas K. Owens, director of the Center for Health Policy at the Freeman Spogli Institute for International Studies and the Center for Primary Care and Outcomes Research at the Department of Medicine, presented his influential economic modeling research about the need for routine HIV screening.

“We determined that HIV screening is cost-effective in virtually all health-care settings,” Owens told the audience, noting that the findings became policy at the Centers for Disease Control and Prevention and other national health policy organizations. It has become an example of how economic modeling can inform crucial policy decisions — and help save lives.

There were also robust panel discussions about the challenges of doing cost-effectiveness analysis in developing countries with limited resources; the difficult paths to universal health care; and how economics can help address disparities in health care and financial protection.

“The consortium is particularly valuable because it fosters collaborations among a broad group of global health experts,” Owens said.

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This season, “Downton Abbey's” plot line has health policy wonks on the edge of their seats: a heated debate about hospital consolidation that closely parallels what’s going on in the U.S. health care system today.

If you’re not a Downton fan, here’s a quick plot recap by Kaiser Health News reporter Jenny Gold: It’s 1925 for the lords and ladies at Downton Abbey. Think flapper dresses, cocktail parties and women’s rights. And a big hospital in the nearby city of York is making a play to take over the Downton Cottage Hospital next to the posh estate.

As Maggie Smith’s character, the Dowager Countess of Grantham, sees it, “The Royal Yorkshire county hospital wants to take over our little hospital, which is outrageous!”

Stanford Health Policy’s Kathy McDonald — an unabashed fan of the popular PBS period piece — says things haven’t changed that much today. There has been an uptick in hospital consolidations since 2010, with about 100 taking place each year, she says.

You can listen to McDonald’s interview with Gold, who took the Downton debate to the American Public Media radio show, “Marketplace.”

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A substantial share of all malpractice claims in the United States is attributable to a small number of physicians, according to a study led by researchers at Stanford University and the University of Melbourne.

The team found that just 1 percent of practicing physicians accounted for 32 percent of paid malpractice claims over a decade. The study also found that claim-prone physicians had a number of distinctive characteristics, such as practicing specialities that are riskier than others.

“The fact that these frequent flyers looked quite different from their colleagues — in terms of specialty, gender, age and several other characteristics — was the most exciting finding,” said David Studdert, professor of medicine and of law at Stanford. “It suggests that it may be possible to identify high-risk physicians before they accumulate troubling track records, and then do something to stop that happening.”

Studdert is also a core faculty member at Stanford Health Policy and the lead author of the study published in The New England Journal of Medicine.

Concentrated among a small group

“The degree to which the claims were concentrated among a small group of physicians was really striking,” added Studdert, an expert in the fields of health law and empirical legal research.

The researchers analyzed information from the U.S. National Practitioner Data Bank, a data repository established by Congress in 1986 to improve health-care quality. Their study covered 66,426 malpractice claims paid against 54,099 physicians between January 2005 and December 2014.

Almost one-third of the claims related to patient deaths; another 54 percent related to serious physical injury. Only 3 percent of the claims were litigated to verdicts for the plaintiff. The remainder resulted in out-of-court settlements. Settlements and court-ordered payments averaged $371,054.

“The concentration of malpractice claims among physicians we observed is larger than has been found in the few previous studies that have looked at this distributional question,” said Michelle Mello, a co-author of the study and professor of law and of health research and policy at Stanford.

“It’s difficult to say why that is,” Mello added. “The earlier estimates come from studies of single insurers or single states, whereas ours is national in scope. Also, the earlier numbers are more than 25 years old now, and claim-prone physicians may be a bigger problem today than they were then.”

Encouraging greater awareness

The authors recommend that all institutions that handle large numbers of patient complaints and claims develop a greater awareness of how these events are distributed among clinicians.

“In our experience, few do,” they write in the paper. “With notable exceptions, fewer still systematically identify and intervene with practitioners who are at high risk for future claims.”

The most important predictor of incurring repeated claims was a physician’s claim history. Compared to physicians with only one prior paid claim, physicians who had two paid claims had almost twice the risk of another one; physicians with three paid claims had three times the risk of recurrence; and physicians with six or more paid claims had more than 12 times the risk of recurrence.

“Risk also varied widely according to specialty,” the authors noted. “As compared with the risk of recurrence among internal medicine physicians, the risk of recurrence was approximately double among neurosurgeons, orthopedic surgeons, general surgeons, plastic surgeons and obstetrician-gynecologists.”

The lowest risks of recurrence occurred among psychiatrists and pediatricians.

Male physicians had a 40 percent higher risk of recurrence than female physicians, and the risk of recurrence among physicians younger than 35 was about one-third the risk among their older colleagues, the study found.

“If it turns out to be feasible to predict accurately which physicians are going to become frequent flyers, that is something liability insurers and hospitals would be very interested in doing,” Studdert said.

“But institutions will then face a choice,” he added. “One option is to kick out the high-risk clinicians, essentially making them someone else’s problem. Our hope is that the knowledge would be used in a more constructive way, to target measures like peer counseling, retraining, and enhanced supervision. These are interventions that have real potential both to protect patients and reduce litigation risks.”

Other stories about the study:

The New York Times Well Blog

The Huffington Post

KQED Public Radio

U.S. News & World Report

CBS News

Reuters

Medscape

The prestigious panel of medical experts who provoked a nationwide debate when it suggested fewer mammograms is standing by its recommendation that women 50 and older only get the screening every other year.

The U.S. Preventive Services Task Force issued an update of its 2009 guidelines on Tuesday, noting that women in their 40s with an average risk of breast cancer should discuss mammography with their clinicians and make individual decisions about whether to have the screening.

When the panel made the panel first made the recommendation, it provoked an outcry from some medical associations and cancer-awareness advocates who feared the advice would lead some women to delay having mammograms and put them at greater risk of death.

“In 2015, contentious discussions about breast cancer screening and prevention continued, with physicians, advocates, lawmakers, and scientists all lending their voices to the debate,” the Task Force said in an editorial on its website.

“Many of these stakeholders focused on the need for women to be able to make more informed health care choices about when to start screening without having to worry about the cost of an insurance copayment,” said the panel of experts, including Stanford Health Policy’s Douglas K. Owens, director of the Center for Health Policy and the Center for Primary Care and Outcomes Research.

“The role of the U.S. Preventive Services Task Force (USPSTF) in these discussions has remained unchanged: to empower women with the best scientific data about the benefits and harms associated with breast cancer screening, so they can make an informed decision with their doctor.”

Breast cancer is the second-leading cause of cancer death among women in the United States, according to the National Cancer Institute. In 2015, an estimated 232,000 women were diagnosed with the disease and 40,000 women died. It is most frequently diagnosed among women aged 55 to 64 years, and the median age of death from breast cancer is 68 years.

The task force determined that while screening mammography in women aged 40 to 49 may reduce the risk for breast cancer death, the number of deaths averted is smaller than that in older women and the number of false-positive results and unnecessary biopsies is larger.

The balance of benefits and harms is likely to improve as women move from their early to late 40s, the task force said.

“In addition to false-positive results and unnecessary biopsies, all women undergoing regular screening mammography are at risk for the diagnosis and treatment of noninvasive and invasive breast cancer that would otherwise not have become a threat to their health, or even apparent, during their lifetime,” the Task Force said. “Beginning mammography screening at a younger age and screening more frequently may increase the risk for over-diagnosis and subsequent overtreatment.”

The independent panel of medical experts from around the nation said that women with a parent, sibling, or child with breast cancer are at higher risk for breast cancer and thus may benefit more than average-risk women from beginning screening in their 40s.

Not everyone is pleased with the recommendations.

Florida Congresswoman and chair of the Democratic National Committee, Debbie Wasserman Schultz, issued a statement that suggested the Task Force recommendations could put younger women at risk because their insurance companies may stop paying for their screenings.

“These guidelines indicate that screening for women under 50 is less beneficial in detecting breast cancer than for older women,” said Wasserman Schultz, herself a breast-cancer survivor. “However, because insurance companies often use these guidelines to determine coverage for these critical life-saving screenings, these new recommendations could potentially bar millions of women from getting coverage for screenings they need.”

Judy Salerno, president and CEO of the Susan G. Komen breast cancer charity, said she worries the recommendation could target African-American women in particular.

“A lack of coverage would be most harshly felt in high-risk and underserved populations,” Salerno said. “African-American women, for example, are often diagnosed at younger ages with aggressive forms of breast cancer – and die of breast cancer at rates over 40 percent higher than white women. Screening at younger ages is a critical tool for these women.”

Members of the Task Force, however, emphasized that it was their role to evaluate scientific evidence and not make insurance coverage decisions.

“The USPSTF acknowledges the important role that insurance coverage plays in access to and use of preventive services,” the Task Force said in its editorial. “Coverage decisions are the domain of payers, regulators and legislators. Whatever we may believe about the importance of coverage in shared decision-making about mammography, we cannot exaggerate our interpretation of the science to ensure coverage for a service. This would lead to confusion regarding the state of science versus the politics of coverage.”

Jonathan H. Chen was an intern at Stanford Hospital a few years back, admitting patients with unusual medical syndromes or rare diseases.

He wasn’t always sure how to immediately treat these patients.

“I found myself clueless at times,” said Chen. “I thought to myself, I should review the chart of a similar patient who had an experienced clinician care for him so that I can learn from their care plan.”

That triggered Chen’s eureka moment. 

“Why look at just one person’s chart?” he thought. “Why not look at the last thousand charts to see how all doctors take care of their patients in similar cases?”

Doing so, he would have the potential to crowd-source the collective wisdom of physicians all in one central location.

Already having a PhD in computer science and spending a few years as a software developer before medical school, Chen — a wunderkind who started college when he was 13 — knew he had the rare set of skills to marry medicine and technology.

“I thought about how the Amazon product-recommender algorithm works and thought, `Can we do this for medical decision-making?’” said the 34-year-old Chen, a VA Medical Informatics Fellow at Stanford Health Policy.

So instead of, other people who bought this book also liked this book, how about: Other doctors who ordered this CT scan also ordered this medication.

“What if there was that kind of algorithm available to me at the point of care?” he asked. “It doesn’t tell me the right or wrong answer, but I bet this would be really informative and help me make better decisions for my patients.”

The National Institutes of Health agrees. Chen was recently awarded a five-year NIH grant as the principal investigator behind OrderRex, a digital platform that data-mines electronic medical records to learn clinical practice patterns and outcomes to inform concrete medical decisions.

Chen is designing and coding OrderRex with the help of his chief mentor, Russ Altman, a professor of bioengineering, genetics and medicine and director of Stanford’s Biomedical Informatics Training Program. Stanford Health Policy professors of medicine, Mary Goldstein and Steven Asch, round out his core team of grant mentors. Grant collaborators Nigam Shah, Lester Mackey, and Mike Baiocchi are providing additional critical expertise.

“I think OrderRex is a first step towards an entirely new way to provide decision support to physicians,” said Altman. “We will not only have a large database of patients from which we can collect similar patients to create virtual cohorts, but we will also have a database of the decisions that their physicians have made in different clinical situations.”

Altman added: “Each of these capabilities would be transformative — but together they would really change what is possible for a provider sitting with a patient, making decisions about diagnosis and therapy.”

The NIH’s Big Data-to-Knowledge grant will allow Chen to develop and test the platform. Stanford Medicine’s Center for Clinical Informatics provided Chen a year’s worth of Stanford Hospital records, including every medical order for every patient. The more medical data he loads, the more patterns begin to form.

Chen has been using a derivative of Amazon’s algorithm to make his platform scalable with millions of patient records. The broad vision is to eventually integrate this tool with hospital computer networks to assist physicians with their decisions.

“Imagine, technology allowing medical decisions to be informed by the collective experience of thousands of other physicians right at the point-of-care,” Chen said.

There are naysayers who worry such a product will further alienate physicians from their patients and allow doctors to jump to crowd-sourced conclusions about treatment. Chen emphasizes OrderRex would only serve as a tool, which does not substitute for human contact, calculations and conclusions.

“Tools like this are simply to augment the medical decision-making process and hopefully — and I know this is a big goal — improve the quality and efficiencies of health care.”

Altman says the lacking-human-touch argument is imprecise and potentially unethical.

“Of course, providers will always be real people and of course they should be empathetic, listen to the patient, examine the patient, and think about what’s best in the big picture,” he said. “But if there are technological tools that they can use to improve their decision-making, it is probably unethical to replace data-driven decision-making with `touch’ and ‘intuition’ — which often perpetuates the status quo and contributes to variability in practice and variability in outcomes.”

Stanford Medicine is already leading the revolution in precision health and big data to overcome human error and misdiagnosis.

In a 2014 Health Affairs article, Stanford pediatrician Christopher A. Longhurst along with Nigam Shah, MBBS, PhD, assistant professor of biomedical research and assistant director of the Stanford Center for Biomedical Informatics Research, and Robert Harrington, MD, professor and chair of medicine, outlined a vision for drawing medical guidance from day-to-day medical practice in hospitals and doctors’ offices. They called it the Green Button.

The idea is to give doctors access —a green button — to patient data from a vast collection of electronic medical records. They wrote that the instant access to EMRs isn’t a substitute for a clinical trials, but better than resorting to the physician’s own bias-prone memory of one or two previous encounters with similar patients.

Chen is working with those professors, but notes the Green Button concept is to look for “patients like mine” and ask questions about different treatment options that may yield different results. His approach looks for “doctors like me,” and anticipates what the doctor wants before they ask for it.

“The conceit of my approach is that all practicing doctors are already trying to make our best-guess decision to improve our patients' outcomes,” he said. “Rather than trying to directly predict how to change a patient outcome, I look to the records of physician decision-making that already represent a wealth of expertise we are not leveraging in a systematic way.”

Could that wealth of expertise one day make Chen a wealthy man, perhaps the Jeff Bezos of the medical informatics world?

“I wouldn’t complain if I was,” Chen said with a grin. “But if I just wanted to make money, I wouldn’t have gone to medical school,” He gave up a lucrative living as a software developer.

He does recognize, however, that for OrderRex to have a big impact, commercial applications such as licensing the product as an add-on to EMR systems are likely.

“So, having a broad impact that will serve the mission of improving quality and efficiency — that is the ultimate goal.”