Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

BACKGROUND: Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. OBJECTIVE: This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. METHODS: We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. RESULTS: The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. CONCLUSIONS: These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

Disparities in Spatial Access to Emergency Surgical Services in the US.

Importance: Hospitals with emergency surgical services provide essential care for a wide range of time-sensitive diseases. Commonly used measures of spatial access, such as distance or travel time, have been shown to underestimate disparities compared with more comprehensive metrics. Objective: To examine population-level differences in spatial access to hospitals with emergency surgical capability across the US using enhanced 2-step floating catchment (E2SFCA) methods. Design, Setting, and Participants: A cross-sectional study using the 2015 American Community Survey data. National census block group (CBG) data on community characteristics were paired with geographic coordinates of hospitals with emergency departments and inpatient surgical services, and hospitals with advanced clinical resources were identified. Spatial access was measured using the spatial access ratio (SPAR), an E2SFCA method that captures distance to hospital, population demand, and hospital capacity. Small area analyses were conducted to assess both the population with low access to care and community characteristics associated with low spatial access. Data analysis occurred from February 2021 to July 2022. Main Outcomes and Measures: Low spatial access was defined by SPAR greater than 1.0 SD below the national mean (SPAR <0.3). Results: In the 217 663 CBGs (median [IQR] age for CBGs, 39.7 [33.7-46.3] years), there were 3853 hospitals with emergency surgical capabilities and 1066 (27.7%) with advanced clinical resources. Of 320 million residents, 30.8 million (9.6%) experienced low access to any hospital with emergency surgical services, and 82.6 million (25.8%) to advanced-resource centers. Insurance status was associated with low access to care across all settings (public insurance: adjusted rate ratio [aRR], 1.21; 95% CI, 1.12-1.25; uninsured aRR, 1.58; 95% CI, 1.52-1.64). In micropolitan and rural areas, high-share (>75th percentile) Hispanic and other (Asian; American Indian, Alaska Native, or Pacific Islander; and 2 or more racial and ethnic minority groups) communities were also associated with low access. Similar patterns were seen in access to advanced-resource hospitals, but with more pronounced racial and ethnic disparities. Conclusions and Relevance: In this cross-sectional study of access to surgical care, nearly 1 in 10 US residents experienced low spatial access to any hospital with emergency surgical services, and 1 in 4 had low access to hospitals with advanced clinical resources. Communities with high rates of uninsured or publicly insured residents and racial and ethnic minority communities in micropolitan and rural areas experienced the greatest risk of limited access to emergency surgical care. These findings support the use of E2SFCA models in identifying areas with low spatial access to surgical care and in guiding health system development.

Use of the spatial access ratio to measure geospatial access to emergency general surgery services in California.

BACKGROUND: Emergency general surgery (EGS) encompasses a spectrum of time-sensitive and resource-intensive conditions, which require adequate and timely access to surgical care. Developing metrics to accurately quantify spatial access to care is critical for this field. We sought to evaluate the ability of the spatial access ratio (SPAR), which incorporates travel time, hospital capacity, and population demand in its ability to measure spatial access to EGS care and delineate disparities. METHODS: We constructed a geographic information science platform for EGS-capable hospitals in California and mapped population location, race, and socioeconomic characteristics. We compared the SPAR to the shortest travel time model in its ability to identify disparities in spatial access overall and for vulnerable populations. Reduced spatial access was defined as >60 minutes travel time or lowest three classes of SPAR. RESULTS: A total of 283 EGS-capable hospitals were identified, of which 142 (50%) had advanced resources. Using shortest travel time, only 166,950 persons (0.4% of total population) experienced prolonged (>60 minutes) travel time to any EGS-capable hospital, which increased to 1.05 million (2.7%) for advanced-resource centers. Using SPAR, 11.5 million (29.5%) had reduced spatial access to any EGS hospital, and 13.9 million (35.7%) for advanced-resource centers. Rural residents had significantly decreased access for both overall and advanced EGS services when assessed by SPAR despite travel times within the 60-minute threshold. CONCLUSION: While travel time and SPAR showed similar overall geographic patterns of spatial access to EGS hospitals, SPAR identified a greater a greater proportion of the population as having limited access to care. Nearly one third of California residents experience reduced spatial access to EGS hospitals when assessed by SPAR. Metrics that incorporate measures of population demand and hospital capacity in addition to travel time may be useful when assessing spatial access to surgical services. LEVEL OF EVIDENCE: Cross-sectional study, level VI.