What Can Different Health Care Systems Learn from One Another?

Irene Papanicolas, the director of CHeSS, argues that it is unhelpful to ask which health system is “better.” She says that many comparisons of health systems falsely reduce complex metrics to singular causes, and ignore significant differences between apparently similar systems. “What is the best health care system?” she asks, “Is it the system that has the best population health outcomes, the best cancer care, the best patient experience, that spends the least, or that is free at the point of care?” 

Papanicolas, who is professor of health services, policy and practice, points out that Switzerland, Germany and the Netherlands all have private insurance, yet perform better than the U.S. on life expectancy and spending. “If you take 10 different health system outcomes, there's no country that's going to be consistently the best at all of them.”

Faced with this complexity, CHeSS and its partners are working to frame questions in ways that yield the sort of empirical findings that can inform policy. Where are health care prices increasing fastest? Do some drug combinations significantly increase the risk of dangerous falls in older adults? Are fewer new drugs made available when national health authorities balance health benefit against cost?

Research across Borders

Public health researchers are accustomed to narrowly tailoring their research questions, tidying up the messy world of data in order to isolate a dependent variable—comparing the same disease, similar patients and corresponding care interventions. But the many profound differences between national health systems present unique challenges for researchers who wish to compare systems treating different populations shaped by different cultures, using different resources, deployed by professionals with different training.

Enrique Bernal-Delgado has been collaborating on international health data comparisons for more than 25 years. Bernal-Delgado founded the Data Sciences for Health Services and Policy research group at the Institute for Health Sciences in Aragon (IACS), in Spain, where he now serves as senior scientist. He helped to pioneer the “federated research” methodology that is at the core of CHeSS’s work, in which research “nodes” in different countries can produce findings in response to the same query while maintaining stringent national data privacy standards.

Health data is highly sensitive, which typically prevents researchers from sharing rich data sets across national boundaries. In the absence of a shared data infrastructure and research methodology, researchers are limited to comparing aggregated data. But these sorts of coarse comparisons are often open to interpretation: Even when similar terminology is used, is a “hospitalization” in Sweden comparable to one in the United States?

“So they go to the hospital, how long does it take to have surgery?” says Papanicolas. “How long do they spend in the hospital? Where do they go when they leave the hospital? Do they have rehab? How long do they have rehab? Where does rehab happen? Is it in an institution? Is it at home? Do they have a primary care physician? How often do they see their primary care physician for the year that follows? Do they go back to the hospital? How many times? What drugs are they on? Does their drug regimen change?” This sort of conceptual slippage makes it hard to answer the important questions. “What does their care look like over the course of a year?” 

In 2018, before joining Brown’s faculty, Papanicolas led the formation of the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC), which now brings together research teams in 12 different countries to meet this research need and shape policy through partnership.

To do rigorous comparisons using richer data from linked sources—including time-dependent variables—required a new methodology, one that satisfied national legal requirements as well as what Bernal-Delgado calls “layers of interoperability.”

“Semantic interoperability is not just about speaking the same language—we don’t speak the same language!” says Bernal-Delgado. “But we need the concepts to be the same.” This often means working with clinicians to establish a rigorously consistent vocabulary. Organizational and technologic interoperability ensure that each partner is able to conduct data queries in a consistent and meticulous fashion. “It’s like making a recipe, but you have a different cook for each component of the meal,” says Liana Woskie, who also collaborates with Papanicolas. 

Setting up this federated research infrastructure took an entire year, but Papanicolas hopes that things will move faster going forward: “I can accept the first project taking a year, if the second one takes a month.” 

Natural Experiments

Very occasionally, health systems experience an identical shock that makes comparison a little simpler. During the COVID-19 pandemic, a new virus tested every national health system, yielding widely differing responses. Countries pursued different policies to treat people and contain the spread of the virus, policies shaped by underlying features and capacities of their health systems. With support from The Health Foundation, a British charity, Papanicolas and her partners are studying whether lockdowns and other public health interventions, like school closures and stay-at-home orders, disrupted care. But unlike pundits comparing Sweden to America, they are comparing similar patients in different systems.

“We're identifying patients with similar needs. And the one thing that varies is where they happen to live and the system that cares for them,” Papanicolas says. “If you take all of the data that we have, we have 20 million patients that happen to live in 11 countries, not 11 data points.” 

The pandemic cast a unique spotlight on the strengths and weaknesses of national health systems. CHeSS and its partners are identifying other opportunities for rigorous comparison by comparing patients with similar, clearly specified conditions. For example, hip fracture in patients aged 65 and older is a condition that is both unambiguous and widespread. The CDC reports, from the near comprehensive data collected by Medicare, that over 300,000 older Americans are hospitalized with hip fractures every year. 

Comparing hip fracture patients in different systems yields results that complicate the “best health system” question. Patients who use four or more prescription drugs daily—sometimes called “polypharmacy”—are at greater risk of the falls that cause most hip fractures. “We have looked at different types of patients, and how many drugs they are on as an average. When you rank order the countries, they are consistently in the exact same order. Different types of patients use different numbers of medications, but the countries are in the same order,” says Papanicolas. The United States system is not an outlier, she says. “The French are always taking the most drugs. Australia has the least, the USA is somewhere in the middle.”

Shaping Policy

Does this mean that French seniors should have fewer prescriptions so as to reduce the risk of falls? Or that Australians aren’t getting enough medications? No, because prescribing policy is a component of an entire system. “You can’t just copy and paste policies,” says Jon Cylus, a CHeSS research partner and adjunct faculty at the School of Public Health, who also leads the London Hubs of the European Observatory on Health Systems and Policies and is a Senior Health Economist at WHO. Data help to specify the challenges people face in using the health care system, but data alone can’t tell you what to do about these challenges. By giving national systems context to compare policy choices and outcomes, international comparisons can point the way towards policy improvements. 

Cylus worked at CMS during the rollout of Obamacare, but became disillusioned with the pace of health care policy reform in the United States, and moved to Europe, where he saw greater willingness to iterate on policy based on data from other countries. In his work at the WHO and European Observatory, Cylus meets with national policymakers from Finland to Tajikistan, to discuss health systems shaped by decades of policy choices reflecting different cultures, resources and populations. “You can’t just go from the system you have to the system you want,” says Cylus. “It takes relentless evidence.”

In talking to policymakers, Cylus often begins with affordable access to care. The WHO Barcelona Office on Health Financing has good data on access, and countries have committed to affordable access as a Sustainable Development Goal. He can then work with policymakers to understand where care is unaffordable and what makes it so. Is routine care prohibitively expensive, or are people being bankrupted by major health events? Are medicines or provider services contributing more to costs? Using these questions, policymakers can drill down to specific policy questions, and look at comparative data from other countries that have faced similar challenges.

This is what Papanicolas intends to do with their study of hip fracture patients. “Patients want to go home, not be in an institution,” Papanicolas says. “What are the care processes that enable patients to go home sooner?” If health systems can learn from each other in a way that doesn't compromise outcomes, “That's a win-win,” says Papanicolas.

“A More Humane Model of Care”

“Comparative work is often an extension of work that's already going on,” says Papanicolas. “You find something fascinating and you wonder if this happens elsewhere. And if it doesn't, why doesn't it?” CHeSS aims to bring together ongoing research in different countries under a single roof. “We would love Brown to be the place where people who have that curiosity come.”

Ritesh Maharaj, a British critical care physician, is one of those curious people. As visiting associate professor in the School of Public Health, he is working with Papanicolas and others to understand how different systems of long-term care shape access and equity. Maharaj speaks quietly and modestly, but something changes when he talks about the goals of his research: “I want to find a more humane model of care.” 

As a physician, Maharaj provides critical care for patients after major health events like heart attacks or hip fractures. But once he stabilizes patients, they still face a long path to full recovery, requiring extended physical rehabilitation. They may need help with basic activities like getting dressed for some period of time. The challenge, says Maharaj, is that this sort of long-term or post-acute care is largely siloed from the acute care that he provides. Patients may have to pay to access it, even under the British National Health Service (NHS). The NHS covers the cost of acute care, but funding for long-term care has fallen in recent years, forcing the local authorities to allocate increasingly scarce resources. Local authorities with smaller tax bases have required “self-funding” to access components of long-term care, putting them out of reach for a growing number of low-income patients. But going without proper long-term care puts patients at risk of further injury and hospitalization, bringing them back to Maharaj’s care.

“When you start thinking about the entire patient episode, you realize that a lot of the very great work that you might do in the acute care setting doesn't translate into meaningful outcomes for patients,” says Maharaj. He believes there is a better way. “It doesn't mean we have to spend more, it just means that we have to be able to identify people and ensure they get to the appropriate care setting.” Maharaj is studying the U.S. system of long-term care funding to see how it differs in areas like equitable provision of care, with the goal of supporting better, more integrated care. “If we can learn from each other around how we structure the system, and how we fund the system,” he said, “that's ultimately going to be the determining factor in bringing value to patients.” 

Liana Woskie, assistant professor of community health at Tufts University and adjunct faculty at Brown’s School of Public Health, uses transnational data to understand U.S. reproductive health policy choices. Using pharmaceutical data from 77 countries over more than 20 years, Woskie is examining regulatory pathway for mifepristone, a widely used medication for pharmaceutical abortion. 

Since the Supreme Court’s 2022 Dobbs decision that overturned Roe v. Wade and eliminated federal protections for abortion rights, mifepristone has been the target of litigation that reached the Supreme Court in March 2024. 

Woskie, with the CHeSS team, is exploring how mifepristone has been regulated in different countries over time. By examining policy variation in Europe, Woskie hopes to shed light on which policies have the greatest influence on price, use, and health outcomes. This research is particularly important as US states set their own abortion-related policies following the Dobbs decision. By comparing the regulatory pathway of mifepristone—from initial approval through inclusion on the World Health Organization’s Essential Medicines List and diffusion to other countries—with drugs with similar risk profile, as well as with other “socially contentious” medications like methadone, this analysis can pull back the curtains on the social and cultural drivers of pharmaceutical policy.

Learning from One Another

The goal of CHeSS and its partners is to help health systems meet the growing challenges they face by providing rigorous comparative data to inform policy choices and enable sustainability. “Health systems are at a point where they're facing a lot of similar challenges,” says Papanicolas. “All countries are facing aging populations, all countries are facing increasing multi-morbidity. All systems are grappling with how much of their budget they spend on health and whether this is sustainable.” CRISPR and other techniques offer cures for previously untreatable diseases. “Systems are having to make really difficult decisions about how they pay for these technologies, and what they don't fund to be able to pay for these technologies.” 

At the same time, systems face the same threats from pandemics and climate change. “These are global crises that are affecting all health systems,” says Papanicolas. “So why aren't we learning about all of the different approaches that countries take to face these challenges? It seems like this incredible, massive opportunity to learn from each other.”

The strategies may be shaped by culture as much as health policy. “I come from Greece. We’ve always had hot summers, and now we have hotter summers,” she says. But Greek people have experience staying safe in the heat. “Buildings were built so that they can cool down quickly. You have a siesta, you don't go out in the middle of the day when it's hot in the summer. There's all of these practices of daily life to combat the heat. This must be true in the way medicine is delivered also.”

CHeSS works to help systems adapt better and faster by learning from each other rather than reinventing the wheel. “We've spent too long looking inwards and trying to find solutions in our own data,” Papanicolas says. “These new challenges ask us to learn from one another to become stronger individually, and collectively.”