Economics and public health have been billed as opposing forces throughout the pandemic. This tension arises from disparate data streams and analyses that fail to incorporate a holistic view of the problem and tradeoffs imposed by potential solutions. Linking data streams across specialties is our best hope for progress.
Dr. Daniel Polsky is a Bloomberg Distinguished Professor of Health Economics in the Carey School of Business and the Bloomberg School of Public Health. Working at the intersection of healthcare and the economy, Dr. Polsky has observed that data scientists and policy advocates too often work in silos, ignoring the tradeoffs with other specialties. We must bridge those divisions to make meaningful progress on health and policy issues that challenge the United States.
We should be thinking about these things together. Policymakers must weigh many competing interests to make the best decisions for social well-being, but they typically receive information from experts in silos. Medical experts provide data on treatments, public health experts on safety, business experts on economic interests. Each of these experts want what is best for societal well-being, but by working in silos they each provide only a piece of what is necessary for informed decision making. As a result, the decision maker is left to weigh these various interests.
We can start bringing these voices together by acknowledging that there are tradeoffs and trying to present the tradeoffs, not leaving that up to the policymakers. The irony with the pandemic is that there weren't tradeoffs. Good public health is good economics. It really was a matter of people arguing for short-term personal economic interest versus the academic view of what's best for the macroeconomy in the long term. In the political sphere, people with the strongest, narrow interests usually scream the loudest.
It would have required an impossible level of collective action to get everyone in their homes for two weeks. In a lockdown, we need to address how we allow people to be home safely, which immediately interacts with economic questions. People need a long list of resources to be able to stay home for two weeks. It's not just about educating them on the public health benefits of staying home. It's about recognizing that there are constraints that they face that are honest and real. If we remain siloed and act with just a public health lens, we aren’t going to address the unemployment insurance system, the Medicaid system, getting medications to people through the post office, and all the other things that are required to stay home safely. We should develop solutions based on data from multiple perspectives, not just public health.
These solutions have worked because they have largely worked around our fragmented health care system. Because the federal government paid for the vaccines, our fragmented health insurance system could be avoided. Because providers needed telemedicine when no one would show up, they embraced this mode of healthcare delivery. These solutions are patches for a broken healthcare system. If we organize our healthcare system to best advance health, it will be better prepared for the next pandemic.
There is much to learn from data about what has worked during this period of adoption of telehealth, but systematic data is hard to come by. One issue with data from telemedicine is that we license providers through a fractured, state-by-state system, and there is no way to track who's delivering these services nationally. We need to put regulatory systems in place for licensing providers and tracking who can and should deliver telemedicine. We can’t collect data if we aren’t regulating it and don’t even know who is delivering these services. There are many problems when data sits everywhere and no one knows who is collecting it.
Surveillance is important, although it has a negative connotation. We need public health infrastructure to monitor infectious diseases and vaccinations, but there are challenges. For example, vaccines are being delivered across hundreds of different types of organizations, and they all have their own information systems. How can information that's collected and all these different sources be shared and standardized? I think there could be a new way of collecting data that isn't based on public health methods from 100 years ago — the electronic medical record equivalent of public health services. Right now, everyone collects information their way, then submits standard forms to the CDC. There could be ways for that to happen automatically through advanced information systems.
We have some infrastructure in place to collect information in a well-established, thorough way. There are health surveillance surveys that may be run through the National Center for Health Statistics, census-style surveys run through the Census Bureau, and economics surveys through the Bureau of Labor Statistics. These surveys are still the foundation of the data we collect, but they don’t connect with each other. It’s frustrating when you go to the American Community Survey and there are opportunities missed to ask things outside of basic socio-economics. I could imagine a task force that brings these already established instruments together.
Also, there are so many private sector datasets that mine data from everywhere. Private companies probably know more about individuals than the government, and researchers can’t access that data. Twitter or Google using data to target ads to you is somehow more acceptable for society than the government collecting those data. The government is accountable to its citizens; who knows who Google is accountable to? These private purveyors of data should share information, possibly through a public health surveillance system that's run by the private sector.