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This episode from the podcast 99 Percent Invisible reflects on how the COVID-19 pandemic exposed the American public to a long-standing problem: the disjointed nature of the U.S. health system. Because state and local health departments largely operate independently and use their own data collection and analysis tools, health systems across the country lack standardized data definitions and systems. These inconsistencies made it nearly impossible to collect and analyze comprehensive, standardized data on COVID-19 cases, deaths, and vaccines administered amid the pandemic. Health experts featured on this episode believe that the pandemic made the need for an overhaul of America’s informatics system very apparent. When rebuilding this system, it’s important to focus on remedying existing inequalities in data collection and classification that in some cases render the health status of certain populations – think Native American communities and other communities of color – completely invisible in the data. By virtue of being small populations, it can be difficult for health departments to collect sufficient and/or statistically significant data on minority communities. Another issue discussed in this episode is the use of broad racial categories like “other,” “multiple races,” or even “Asian American,” which, if not disaggregated, obscures the health status of diverse populations who are grouped under the same category. Without comprehensive and inclusive health data, it’s difficult to identify disparities and implement policies and programming that promote social mobility and health equity.

The article discusses the challenges and frustrations surrounding Long COVID research in the United States. Despite substantial investments and numerous research efforts, progress in understanding and treating Long COVID has been slow and disappointing. Experts and patient advocates have criticized the research community for its focus on disease development rather than direct patient care, duplication of studies, and a lack of clinical trials. The authors propose a new hypothesis that Long COVID may be a form of post-infectious syndrome or chronic fatigue syndrome, suggesting that traditional biomedical research approaches may not yield meaningful results. Instead, they advocate for a shift towards health services research and measures that directly impact patients’ welfare, including prevention, improved prognosis, access to empathetic care, and quality of life issues. They emphasize the need for collaboration between researchers, patients, and advocacy groups to reset the research agenda effectively.