HMN 2025: How Telehealth boomed during COVID, but in some areas, its promise fell short

Telehealth boomed during COVID, but in some areas, its promise fell short
Proposed methodology framework. Credit: Operational Research (2025). DOI: 10.1007/s12351-025-00978-2

While telehealth use surged during the COVID-19 pandemic, some U.S. counties struggled to use resources efficiently, revealing widespread misallocation of health care infrastructure, workforce and technology, according to new research from the University at Buffalo School of Management.

Recently published in Operational Research, the study found significant inefficiencies with telehealth in the Midwest and across rural regions of the U.S., largely tied to limited broadband access, workforce shortages and challenges in people’s everyday lives that make it harder to stay healthy.

“Telehealth was vital during the pandemic, but despite similar policy support nationwide, efficiency varied dramatically,” says study co-author Raj Sharman, Ph.D., professor of management science and systems in the UB School of Management.

“For example, while counties in California had more urgent care centers and longer staff hours, structural shortages in the workforce, and with facilities and connectivity in states like Montana prevented efficient use, even with favorable policies.”

The researchers used data envelopment analysis (a method of measuring efficiency) and machine learning to examine Medicare fee-for-service claims from more than 3,000 counties across the U.S. and found that several states, including Missouri, Montana, Nebraska, North Dakota and Wyoming, showed the lowest telehealth efficiency, while California, Florida, Massachusetts, New Jersey and Rhode Island ranked among the most efficient.

Their findings show that the top factor in both urban and rural areas was limited English proficiency among residents. Counties with more residents who struggle with English consistently exhibited lower telehealth efficiency, underscoring the need for expanded multilingual support and culturally competent care. Other major predictors of telehealth inefficiency included median income, education levels, incentive program disbursements and political orientation.

In the future, Sharman says policymakers should tailor resources to local needs rather than relying on one-size-fits-all broadband initiatives.

“Telehealth cannot solve health care inequalities without targeted investment in workforce capacity, patient education, language accessibility and community-aligned planning,” says Sharman. “Expanding access is not the same as ensuring effective telehealth use.”

More information

Ying-Chih Sun et al, Optimizing telehealth utilization during COVID-19: enhancing efficiency and equity through data envelopment analysis and machine learning, Operational Research (2025). DOI: 10.1007/s12351-025-00978-2

Key medical concepts

Telemedicine
Barrier, Language


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