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Emergency general surgery (EGS) is a critical component of emergency care in the United States. Due to the time sensitiveness of EGS conditions, ensuring adequate spatial access to EGS services is paramount for reducing patient morbidity and mortality. Past studies have used travel time to measure spatial access to EGS services, which has its limitations. The major purpose of this paper is to evaluate the utility of a gravity-based spatial access model in measuring spatial access to EGS services in California. Our data sources include the American Hospital Association 2015 Annual Survey, the American Community Survey 2013–2017 five-year average dataset, and background geospatial datasets. We implemented both the gravity-based model and the shortest travel time method and compared them in measuring spatial access to EGS-capable hospitals in California at the census block group level. We analyzed each metric’s ability to identify disparities in spatial access for the population as a whole, and subsequently to identify socio-demographic disparities. Overall, we found that both methods identified similar geographic and socio-demographic patterns of the spatial access. Native Americans and rural residents experienced the greatest disadvantage in spatial access to both general EGS services and advanced EGS services. However, the gravity-based model revealed more disparities in spatial access to EGS services than the travel time model, suggesting that using travel cost alone to measure spatial access to EGS services may underestimate the magnitude of disparities. These findings call for the use of gravity-based models that incorporate measures of population demand and hospital capacity when assessing spatial access to surgical services, and have implications for reallocating surgery resources to address disparities in spatial access.

Context plays a key role in impulsive adverse behaviors such as fights, suicide attempts, binge-drinking, and smoking lapse. Several contexts dissuade such behaviors, but some may trigger adverse impulsive behaviors. We define these latter contexts as 'opportunity' contexts, as their passive detection from sensors can be used to deliver context-sensitive interventions. In this paper, we define the general concept of 'opportunity' contexts and apply it to the case of smoking cessation. We operationalize the smoking 'opportunity' context, using self-reported smoking allowance and cigarette availability. We show its clinical utility by establishing its association with smoking occurrences using Granger causality. Next, we mine several informative features from GPS traces, including the novel location context of smoking spots, to develop the SmokingOpp model for automatically detecting the smoking 'opportunity' context. Finally, we train and evaluate the SmokingOpp model using 15 million GPS points and 3,432 self-reports from 90 newly abstinent smokers in a smoking cessation study.

Hurricanes can have a significant impact on the functioning and capacity of healthcare systems. However, little work has been done to understand the extent to which hurricanes influence local residents' spatial access to healthcare. Our study evaluates the change in spatial access to primary care physicians (PCPs) between 2016 and 2018 (i.e., before and after Hurricane Harvey) in Harris County, Texas. We used an enhanced 2-step floating catchment area (E2SFCA) method to measure spatial access to PCPs at the census tract level. The results show that, despite an increased supply of PCPs across the county, most census tracts, especially those in the northern and eastern fringe areas, experienced decreased access during this period as measured by the spatial access ratio (SPAR). We explain this decline in SPAR by the shift in the spatial distribution of PCPs to the central areas of Harris County from the fringe areas after Harvey. We also examined the socio-demographic impact in the SPAR change and found little variation in change among different socio-demographic groups. Therefore, public health professionals and disaster managers may use our spatial access measure to highlight the geographic disparities in healthcare systems. In addition, we recommend considering other social and institutional dimensions of access, such as users' needs, preferences, resource capacity, mobility options, and quality of healthcare services, in building a resilient and inclusive post-hurricane healthcare system.

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.

BackgroundEmergency general surgery (EGS) diseases carry a substantial public health burden, accounting for over 3 million admissions annually. Due to their time-sensitive nature, ensuring adequate access to EGS services is critical for reducing patient morbidity and mortality. Travel-time alone, without consideration of resource supply and demand, may be insufficient to determine a regional health care system’s ability to provide timely access to EGS care. Spatial Access Ratio (SPAR) incorporates travel-time, as well as hospital-specific resources and capacity, to determine healthcare accessibility which may be more appropriate for surgical specialties. We therefore compared SPAR to travel-time in their ability to differentiate spatial access to EGS care for vulnerable populations.MethodsWe constructed a Geographic Information Science (GIS) platform using existing road networks, and mapped population location, race and socioeconomic characteristics, as well as all EGS-capable hospitals in California. We then compared the shortest travel time method to the gravity-based SPAR in their ability to identify disparities in spatial access for the population as a whole, and subsequently to describe socio-demographic disparities. Reduced spatial access was defined at > 60 minutes travel time, or lowest three classes of SPAR.Results283 EGS-capable hospitals were mapped, 142 (50%) of which had advanced resources. Using shortest travel time, 36.98M people (94.8%) were within 20-minutes driving time to any EGS capable hospital, and 33.49M (85.9%) to an advanced-resourced center. Only 166, 950 (0.4%) experienced prolonged (>60 minutes) travel time to any EGS-capable hospital, which increased to 1.05M (2.7%) for advanced-resources. Using SPAR, 11.5M (29.5%) of people had reduced spatial access to any EGS hospital, which increased to 13.9M (35.7%) when evaluating advanced-resource hospitals. The greatest disparities in spatial access to care were found for rural residents and Native Americans for both overall and advanced EGS services.ConclusionsWhile travel time and SPAR showed similar overall patterns of spatial access to EGS-capable hospitals, SPAR showed greater differentiation of spatial access across the state. Nearly one-third of California residents have limited or poor access to EGS hospitals, with the greatest disparities noted for Native American and rural residents. These findings argue for the use of gravity-based models such as SPAR that incorporate measures of population demand and hospital capacity when assessing spatial access to surgical services, and have implications for the allocation of healthcare resources to address disparities.