Kavya Mehul Shah

Amid the COVID-19 pandemic, telemedicine emerged as a promising solution for early disease detection. However, access may remain limited in communities with reduced access to outpatient health facilities key for timely screening. Here, we correspond broadband internet access with access to health facilities and elucidate rural-urban disparities. For 3,133 US counties, we extracted data on the population density of outpatient care centers, diagnostic labs, and nursing/residential care (2017 National Neighborhood Data Archive), broadband access stratified based on the median percentage (9.8%) of households without broadband (2022 FCC Mapping Broadband Health in America), urbanicity level, and sociodemographic covariates (2022 American Community Survey). Two-sample t-tests substantiated the association between broadband access and facility densities. Multivariable linear regressions quantified the association between broadband access and facility densities, adjusting for sociodemographic covariates, and geographical heatmaps visualized trends in broadband access, urbanicity level, poverty rate, and facility densities. Heatmaps revealed that regions with limited healthcare facilities—particularly the Great Plains and Southwest—overlap with areas of low broadband coverage. Compared to counties with high broadband access, those with low access had fewer outpatient care centers (mean 10.46 vs. 11.91 per 100,000 residents, P < 0.001) and diagnostic labs (mean 1.91 vs. 3.95 per 100,000 residents, P < 0.001). They also demonstrated higher poverty rates, older populations, increased rurality, and lower educational attainment, employment, and insurance (all P < 0.001). Multivariable regression confirmed that declining broadband access corresponds with lower densities of outpatient care centers (β = −0.045), diagnostic laboratories (β = −0.024), and nursing/residential care facilities (β = −0.089; all P < 0.001). Ultimately, US communities with the fewest physical health resources—particularly in rural, low-income counties—are also less likely to have broadband access. Addressing this inequity necessitates coordinated investment in broadband expansion and targeted health services deployment.

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Despite telehealth expansion, access may remain lacking in high-burden communities with limited brick-and-mortar health facilities. We aimed to i) examine the relationship between broadband internet access and health facility availability and ii) explore disparities in broadband access. Using data from the 2017 National Neighborhood Data Archive, we obtained data on population density of outpatient care centers, diagnostic labs, and nursing/residential care facilities for 3133 US counties. Broadband access and sociodemographic data were obtained from the 2020 Mapping Broadband Health in America Platform and 2022 American Community Survey. Two-sample t-tests and multivariable linear regressions quantified the association between broadband internet access and health facility density, adjusting for sociodemographic covariates. Counties with low broadband access had 12% fewer outpatient care centers and 48% fewer diagnostic labs than counties with high broadband access (all P < 0.001). A 1% increase in county population without broadband corresponds with a decrease of 0.0451 outpatient care centers, 0.0237 diagnostic labs, and 0.0886 nursing/residential care facilities per 100,000 people (all P < 0.001). Counties with limited in-person health facilities face reduced access to broadband internet, particularly in rural, low-income communities. Expanding broadband infrastructure and health services in these regions is essential.

The recent excitement surrounding artificial intelligence (AI) in health care underscores the importance of physician engagement with new technologies. Future clinicians must develop a strong understanding of data science (DS) to further enhance patient care. However, DS remains largely absent from medical school curricula, even though it is recognized as vital by medical students and residents alike. Here, we evaluate the current DS landscape in medical education and illustrate its impact in medicine through examples in pathology classification and sepsis detection. We also explore reasons for the exclusion of DS and propose solutions to integrate it into existing medical education frameworks.