Could out of pocket drug costs be responsible for pandemics? In this Public Health Perspectives article, Marcella Alsan discusses how copayments for antibiotics can cause people in poor areas to turn to unregulated markets.

On May 26, 2016, researchers at the Walter Reed National Military Medical Center reported the first case of what they called a “truly pan-drug resistant bacteria.” By now, the story has been well-covered in the media: a month earlier, a 49 year old woman walked into a clinic in Pennsylvania with what seemed to be a urinary tract infection. But tests revealed something far scarier—both for her and public health officials. The strain of E. Coli that infiltrated her body has a gene that makes it bulletproof to colistin, the so-called last resort antibiotic.

Most have pinned the blame for the impending doom of a “post-antibiotic world” on the overuse of antibiotics and a lack of new ones in the development pipeline. But there’s another superbug incubator that hasn’t gotten the attention it deserves: poverty.

Last month at the IMF meeting in Washington, D.C., UK Chancellor George Osborne warned about the potentially devastating human and economic cost of antimicrobial resistance. He called for “the world’s governments and industry leaders to work together in radical new ways.” But Gerry Bloom, a physician and economist at the Institute for Development Studies, argued that any measures to stop overuse and concoct new drugs must be “complemented by investments in measures to ensure universal access to effective antibiotic treatment of common infections.”

“In many countries, poor people obtain these drugs in unregulated markets,” Bloom said. “They often take a partial course and the products may be sub-standard. This increases the risk of resistance.”

For at least fifteen years, we’ve known about these socioeconomic origins of antimicrobial resistance. Other studies have revealed problems with mislabeled or expired or counterfeit drugs. But the clearest link between poverty and the rise of antimicrobial resistance is that poor people may not see a qualified health care provider or complete a course of quality antibiotics. Instead, they might turn to unregulated markets for substandard drugs.

But why do people resort to unregulated markets or take drugs that aren’t that great if they are available? Marcella Alsan, an assistant professor of medicine at the Stanford School of Medicine who studies the relationship between socioeconomic disparities and infectious diseases, led a study that answered this question. In last October’s Lancet Infectious Diseases, Alsan and her colleagues showed that it might have a lot to do with requiring copayments in the public sector. To show this, they analyzed the WHO’s 2014 Antibacterial Resistance Global Surveillance report with an eye toward the usual suspects, such as antibiotic consumption and antibiotic-flooded livestock.

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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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Anna Lembke, Assistant Professor of Psychiatry and Behavioral Sciences at the Stanford University Medical Center, visited SCPKU for two weeks as a faculty fellow in July 2014.  Below are the highlights of a conversation Professor Lembke had with SCPKU in which she shares more details about her research and how SCPKU helped to advance her work in China.

Q: Describe your research and its connection to China

My research focuses on improving the lives of those with addictive disorders. I am especially interested in the intersection between health care systems and culture, and how this intersection impacts addiction treatment. I became interested in studying drug use disorders in China for a number of reasons. First, I spent a year after college living in China (1989-1990) teaching English as part of the Yale China Program. I have followed events in China with keen interest ever since. Second, the total number of drug users in China may be as high as 7 million, with China predicted to have the most heroin users of any country in the world within 5 years. I was curious to find out how China is addressing its burgeoning drug problem, and didn’t just want the “party line.” I wanted to learn about how people addicted to drugs in China are seeking and getting help.

Q: What got you interested in the study of addiction?

When I first began practicing psychiatry, I was not interested in treating addiction. But over time, I came to realize that if I didn’t treat my patients’ drug and alcohol problems, their other mental health issues were unlikely to improve. I also realized that in targeting and treating addiction, I could help patients transform their lives for the better, as well as the lives of those who love them.

Q: Why did you decide to apply for an SCPKU Faculty Fellowship?

SCPKU gave me the financial and logistical support to pursue a research project in China, an opportunity that would not have been possible without their help.

Q: How valuable was SCPKU's team in supporting your fellowship at SCPKU?

The team here at Stanford was helpful with drafting the initial proposal, creating the budget, which was especially challenging, due to my lack of familiarity with what things cost in China, and making contact with the SCPKU staff in Beijing. The team in Beijing was helpful in setting up temporary housing and meals in Beijing, as well as providing maps, information on how to take the subway, and logistical support getting back to the airport.

Q: What were your fellowship objectives and were they met? 

My fellowship objective was to interview treatment-seeking heroin users in China to learn more about the state of addiction treatment in China. My research assistant, Dr. Niushen Zhang, and I planned to publish our findings in a peer-reviewed journal.

We learned that individuals in China addicted to drugs experience intense social stigma. They are reluctant to utilize government-sponsored treatment, because of fear of loss of anonymity and the ensuing social and economic consequences that follow when they are publicly identified as “addicts,” not to mention the potential loss of their personal freedom. (Addicted persons in China are sent against their will to forced detention centers, or “rehabilitation through labor camps.”) As a result, drug addicted persons in China are deeply mistrusting of government-sponsored treatment, and willing to sacrifice large sums of their own money for anonymous, confidential treatment.

Dr. Niushen Zhang and I recently published our findings in Addiction Science and Clinical Practice, 2015, “A qualitative study of treatment-seeking heroin users in contemporary China.” (To access the article online go to http://www.ascpjournal.org/content/10/1/23)

Q: Describe some highlights of your stay in China/SCPKU. 

The highlight for me was hearing the life stories of heroin-addicted patients at New Hospital in Beijing, and attending an Alcoholics Anonymous meeting, conducted entirely in Chinese. The AA members we met told us their participation in this grass-roots 12-step movement literally saved their lives. I also met many wonderful doctors and nurses working with addicted patients in China. Finally, Dr. Zhang and I became good friends. We had hardly known each other before venturing off to do research in China.

Q: List at least THREE words or thoughts that come to mind which best describe your experience at SCPKU. 

Compassion, endurance, overcoming adversity
 

Q: Any future plans in China? 

I’m thinking about taking a group of Stanford residents and/or medical students to China for a total immersion 3-week course to learn about addiction in China.  But not right away.

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.”

Every Halloween there seems to be another animated brushing campaign to save children from their own sweet tooths. For most, the goal is simple: better oral hygiene for kids.

PLAQUEMONSTER is different.

Developed by Jason Wang, director of the Center for Policy, Outcomes and Prevention (CPOP) and a Center for Health Policy/Center for Primary Care and Outcomes Research (CHP/PCOR) core faculty member, and his team, PLAQUEMONSTER does encourage children to practice good oral hygiene. However, the true purpose of the app is to provide feedback on the user’s engagement that can be used for future forays into mobile health.

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Using the game’s team mechanic, the app urges children to encourage their friends to brush and floss. Teammates can release a tooth pet from jail, so kids must hold each other accountable if they want their team to progress.

“The social aspect really does make a difference,” said Zara Abraham, a digital media specialist at CPOP and one of the app’s designers. She found that the app’s first child testers “would always be on the phone making sure that each one was doing their work, checking on their teeth.”

The social aspect is likely to engage children more than the average brushing and flossing campaign, according to Abraham. The app’s storyline also helps set PLAQUEMONSTER apart.

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However, PLAQUEMONSTER is more than just a game, more even than a campaign for oral hygiene. Wang’s team hopes to use health literacy games along with demographic and engagement information to develop other mobile health apps. Ultimately, PLAQUEMONSTER is a tool for discovering how people engage with health on a mobile platform and how mobile health apps can improve health care.

Wang unveiled the mHealth app at Stanford Medicine's Population Health Sciences Colloquium last week.

“The spirit that Jason brings to the app is the game mechanics of behavioral economics,” said Manuel Rivera, product manager at CPOP.

Eventually, Wang’s team hopes to develop other mHealth apps that could aid patients with serious conditions, helping them to track their health and engage in their care plan. Wang’s long-term goal is for “people who are of working age and elderly to improve their quality of life and health trajectories” using mobile health.

If all goes well, PLAQUEMONSTER could be a first step toward active engagement between patients and health care using mobile platforms.

This project is supported by an NIH Director's New Innovator Award.