HGHI launches regionalized capacity estimates. | Read more in ProPublica, The New York Times, and CBS Morning News | Counting every bed, in every major hospital market, to inform community response
Cambridge, MA, March 17, 2020 — When it comes to caring for a surge of COVID-19 patients, a closer look at hospital capacity in communities across the United States reveals significant differences in readiness. A new model that builds on bed capacity data for each of 306 U.S. hospital markets — so called Hospital Referral Regions (HRR) — now provides important localized estimates of available beds, and beds needed to accommodate COVID-19 patients over the coming months. It also illuminates where hospitals might find additional bed and ICU bed capacity as well as other shortages that need to be addressed—from workforce to ventilators.
The model was developed by an experienced team of health system researchers at the Harvard Global Health Institute (HGHI) and the Harvard T.H. Chan School of Public Health, and is launched in collaboration with ProPublica, and in sync with news reports in The New York Times and CBS Morning News.
“Our goal is to give hospital leaders and policy makers a clear sense of when they will hit capacity, and strategic information on how to prepare for rising numbers of patients with COVID-19 needing care,” says Ashish K. Jha, director of the Harvard Global Health Institute (HGHI) and K.T. Li Professor of Global Health at the Harvard T.H. Chan School of Public Health.
“Crucially, we are providing this information at a local, hospital market specific level. National averages are not very helpful in this context. It’s irrelevant to a person in Utah how many hospital beds are available in Boston, we won’t be transferring large numbers of people to different hospitals. But specific, localized data provides a pathway to understanding what we need to do to get hospitals ready.”
The HGHI team collaborated with ProPublica and worked with The New York Times to fact-check, interpret, contextualize and visualize the data for policy makers, hospitalists and citizens alike. “Pandemics are a time when we need to share information fast, but we also need to be accurate and explain what our estimates mean, especially when they are scary estimates,” says Stefanie Friedhoff, director of content and strategy at HGHI and a veteran journalist. “So we felt it was important to work with some of the best journalists in the nation on getting this right.”
Explore the model and what it tells us, and access results for your region:
Specific, localized data provides a pathway to understanding what we need to do to get hospitals ready.
How will “flattening the curve” actually play out over six, twelve, or even eighteen months in hospitals systems across the nation? What if 20% of the population contracts COVID-19? 40%? Even 60%?
We look at the numbers.
To make this project possible in a short amount of time, everyone at HGHI pitched in—you can browse our staff list here. Here are our project leads:
Dr. Jha’s research endeavors focus on improving the quality and costs of healthcare systems with a specialized focus on the impact of policies. He has published over two hundred various papers in prestigious journals and heads a personal blog which focuses on using statistical data research to improve health quality. Dr. Jha is a member of the Institute of Medicine at the National Academies of Sciences, Engineering, and Medicine.
Tsai is a surgeon and health policy researcher in the Department of Surgery at Brigham and Women’s Hospital and in the Department of Health Policy and Management at Harvard T.H. Chan School of Public Health. He is on the faculty and collaborates with colleagues at the Center for Surgery and Public Health, Ariadne Labs, and the Harvard Global Health Institute.
Tsai’s research focuses on understanding the impact of health policy efforts on achieving value in our healthcare system by reducing spending and improving outcomes. Using national Medicare claims data, his work has examined the relationship between hospital quality and readmissions; patient experience as a measure of quality; and racial and socioeconomic disparities in readmission rates.
Dr. Figueroa’s research focuses on improving quality of health care for complex and vulnerable populations. Specifically, his work has examined the drivers of poor clinical outcomes and health care spending for high-risk populations, including frail older adults, people with serious mental illness, disabled populations, and racial and ethnic minorities. His work on segmenting high-need, high-cost populations was highlighted by the National Academy of Medicine, where he served as a national planning committee member for a workshop series on complex populations, ultimately leading to the NAM report, “Effective Care for High-Need Patients.” Dr. Figueroa has also studied the impact of policy interventions and payment reform on health care for these populations using quasi-experimental methods.
Ben graduated from Princeton University in 2019 with a bachelor’s degree in Molecular Biology and a certificate in Computer Science. He conducted his senior thesis research on the phenotypic and epigenetic effects of hydraulic fracking exposure in children. In the future, he hopes to attend medical school and to continue working to make healthcare more equitable, effective, and efficient.
A German-American journalist and content strategist with 25+ years of experience in international media and higher education, Stefanie Friedhoff currently serves as Director of Content and Strategy and Senior Editor at HGHI. She is an expert at creating innovative approaches to engage audiences in critical conversations about global health. Friedhoff has worked as a foreign correspondent, feature writer, editor and photographer on three continents. Her stories have been published in TIME, The Boston Globe, Geo, Sueddeutsche Zeitung, Frankfurter Allgemeine, and many other publications. A 2001 Nieman Foundation for Journalism Fellow, she is also a senior advisor to the Trust for Trauma Journalism and a board member at RiffReporter. Twitter: @Stefanie2000
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