A comparison of methods for measuring spatial access to health care

Disparities in Spatial Access to Sleep Health Care in the United States: A Population-Based Geospatial Analysis

OBJECTIVES

To examine spatial access to sleep health care in the United States and investigate associations with demographic and socioeconomic characteristics, thereby identifying high-risk communities with limited spatial access to sleep health service.

DESIGN

A cross-sectional population-based geospatial analysis.

SETTINGS AND PARTICIPANTS

Residents in US Census tracts across the 48 contiguous states, Alaska, and Hawaii.

METHODS

The 2020 American Community Survey 5-year estimates, 2010 rural-urban commuting area codes, 2020 Area Deprivation Index, and sleep care provider locations from the National Provider Identifier file were used to assess the spatial access and related demographic/socioeconomic characteristics. Spatial access was measured by spatial access ratio using enhanced 2-step floating catchment area methods. The associations were investigated using logistic regression analysis and multivariate linear regression analysis.

RESULTS

A total of 45.8 million residents experienced low spatial access to sleep health care. Spatial access decreased in rural and high Area Deprivation Index areas, and in areas characterized by higher population with uninsured status, vehicle unavailability, internet unavailability, cognitive difficulties, and hearing difficulties. With a 10% increase in the percentage of the racial minority (non-white) population, metropolitan census tracts experienced an increase in spatial access (3.268%), whereas micropolitan (-1.526%) and rural (-4.493%) areas experienced a decrease in spatial access. Similar findings were observed within the ethnic minority (Hispanic or Latino) population.

CONCLUSIONS AND IMPLICATIONS

Disparities exist in spatial access to sleep health care across the United States, especially for disadvantaged individuals. Racial/ethnic minorities exhibit contrasting spatial access patterns in urban and rural areas, with those in rural areas facing more challenges in spatial access to sleep health care.

Understanding Washington State's Low Uptake of Lung Cancer Screening in Two Steps: A Geospatial Analysis of Patient Travel Time and Health Care Availability of Imaging Sites

BACKGROUND

Early detection of lung cancer reduces cancer mortality; yet uptake for lung cancer screening (LCS) has been limited in Washington State. Geographic disparities contribute to low uptake, but do not wholly explain gaps in access for underserved populations. Other factors, such as an adequate workforce to meet population demand and the capacity of accredited screening facility sites, must also be considered.

RESEARCH QUESTION

What proportion of the eligible population for LCS has access to LCS facilities in Washington State?

STUDY DESIGN AND METHODS

We used the enhanced two-step floating catchment area (E2SFCA) model to evaluate how geographic accessibility in addition to availability of LCS imaging centers contribute to disparities. We used available data on radiologic technologist volume at each American College of Radiology (ACR)-accredited screening facility site to estimate the capacity of each site to meet potential population demand. Spearman rank correlation coefficients of the spatial access ratios were compared with the 2010 Rural-Urban Commuting Area codes and area deprivation index quintiles to identify characteristics of populations at risk for lung cancer with greater and lesser levels of access.

RESULTS

A total of 549 radiologic technologists were identified across the 95 ACR-accredited screening facilities. We observed that 95% of the eligible population had proximate geographic access to any ACR facility. However, when we incorporated the E2SFCA method, we found significant variation of access for eligible populations. The inclusion of the availability measure attenuated access for most of the eligible population. Furthermore, we observed that rural areas were substantially correlated, and areas with greater socioeconomic disadvantage were modestly correlated, with lower access.

INTERPRETATION

Rural and socioeconomically disadvantaged areas face significant disparities. The E2SFCA models demonstrated that capacity is an important component and how geographic access and availability jointly contribute to disparities in access to LCS.

Commercial Insurer Market Power and Medicaid Managed Care Networks

Over 70% of Medicaid beneficiaries are enrolled in Medicaid managed care (MMC). MMC provider networks therefore represent a critical determinant of access to the Medicaid program. Many MMC insurers also participate in commercial insurance markets where prices are high, and some insurers exercise considerable market power. In this paper, we examined the relationship between commercial insurer market power and MMC physician network breadth using linked national enrollment data and provider directory data. Insurers with more commercial market power had broader Medicaid physician networks. Insurers with over 30% market share had 37.3% broader Medicaid networks than insurers in the same county that had no commercial market share. These differences were driven by greater breadth among primary care providers, as well as other specialists including OB/GYNs, surgeons, neurologists, and cardiologists. Commercial insurance market power may have spillovers on access to care for MMC beneficiaries.

Measuring Spatial Access of Vulnerable Population to HIV Testing Facilities in the Baton Rouge Metropolitan Statistical Area, Louisiana

Ensuring adequate and equitable access to affordable HIV testing is a crucial step toward ending the HIV epidemic (EHE). Using the high-burden Baton Rouge Metropolitan Statistical Area (MSA) as an example, we measure spatial access to HIV testing facilities for vulnerable populations and assess whether their access would improve if eliminating a considerable barrier-costs. Locations and status (free, low-cost, and full cost) of HIV testing facilities are searched on the Internet and confirmed through a field survey. Vulnerable populations include the uninsured and people living with HIV (PLWH), disaggregated from county-level HIV prevalence data. Spatial access is computed by a normalized urban-rural two-step floating catchment area (NUR2SFCA) method. Our survey confirms that only 11% and 37% of the 103 Internet-searched HIV testing facilities are indeed free and low-cost. Making more facilities cheaper or free increases the average access of PLWH, the uninsured, and the entire population but their geographic patterns vary. Free testing facilities, clustered in Baton Rouge city, are highly accessible to 82.6%, 69.4%, and 70.2% of three population groups living in East and West Baton Rouge Parish. In comparison, making all low-cost facilities free increases access in most outlying parishes but at the cost of reducing access in East Baton Rouge Parish, leaving west Livingston, north Iberville, and east Pointe Coupee Parish with the poorest access. Making all full-cost facilities cheaper or free exhibits a similar pattern. The study has important policy implications for where and how to improve access to HIV testing for vulnerable populations.

Rural and frontier access to mental health prescribers and nonprescribers: A geospatial analysis in Oregon Medicaid

OBJECTIVE

Medicaid enrollees in rural and frontier areas face inadequate access to mental health services, but the extent to which access varies for different provider types is unknown. We assessed access to Medicaid-participating prescribing and nonprescribing mental health clinicians, focusing on Oregon, which has a substantial rural population.

METHODS

Using 2018 Medicaid claims data, we identified enrollees aged 18-64 with psychiatric diagnoses and specialty mental health providers who billed Medicaid at least once during the study period. We measured both 30- and 60-minute drive time to a mental health provider, and a spatial access score derived from the enhanced 2-step floating catchment area (E2SFCA) approach at the level of Zip Code Tabulation Areas (ZCTAs). Results were stratified for prescribers and nonprescribers, across urban, rural, and frontier areas.

RESULTS

Overall, a majority of ZCTAs (68.6%) had at least 1 mental health prescriber and nonprescriber within a 30-minute drive. E2SFCA measures demonstrated that while frontier ZCTAs had the lowest access to prescribers (84.3% in the lowest quintile of access) compared to other regions, some frontier ZCTAs had relatively high access to nonprescribers (34.3% in the third and fourth quartiles of access).

CONCLUSIONS

Some frontier areas with relatively poor access to Medicaid-participating mental health prescribers demonstrated relatively high access to nonprescribers, suggesting reliance on nonprescribing clinicians for mental health care delivery amid rural workforce constraints. Efforts to monitor network adequacy should consider differential access to different provider types, and incorporate methods, such as E2SFCA, to better account for service demand and supply.

Spatial methods for measuring access to health care

Access to health care is a universal human right and key indicator of health system performance. Spatial access encompasses geographic factors mediating with the accessibility and availability of health services. Equity of health service access is a global issue, which includes access to the specialized nursing workforce. Nursing research applying spatial methods is in its infancy. Given the use of spatial methods in health research is a rapidly developing field, it is timely to provide guidance to inspire greater application in cardiovascular research. Therefore, the objective of this methods paper is to provide an overview of spatial analysis methods to measure the accessibility and availability of health services, when to consider applying spatial methods, and steps to consider for application in cardiovascular nursing research.

Spatial accessibility of pre-exposure prophylaxis (PrEP): different measure choices and the implications for detecting shortage areas and examining its association with social determinants of health

PURPOSE

We examine how various pre-exposure prophylaxis (PrEP) accessibility measures impact the detection of PrEP shortage areas and the relation of shortage areas to social determinants of health (SDOH).

METHODS

Using ZIP Code Tabulation Areas (ZCTAs) in New York City as a case study, we compared 25 measures of spatial PrEP accessibility across four categories, including density, proximity, two-step floating catchment area (2SFCA), and Gaussian 2SFCA (G2SFCA). Bayesian spatial regression models were used to examine how PrEP accessibility is associated with SDOH.

RESULTS

Using density to measure PrEP accessibility for small areas such as ZCTAs poses challenges to statistical modeling because the measured accessibility values are highly skewed with excess zeros, leading to the necessity of using complex models such as the two-part mixture model. When G2SFCA measures are used, which account for distance decay effects and the competition from the PrEP demand side, findings on PrEP shortage area detection and the association between PrEP accessibility and SDOH were more consistent and less sensitive to spatial scales (i.e., varying from 10- to 30-minute driving).

CONCLUSIONS

This research adds to the nascent research on PrEP accessibility measurement and sheds light on selecting an appropriate measure to assess spatial disparities in PrEP accessibility and its associations with SDOH.

Greater spatial access to care is associated with lower mortality for emergency general surgery

BACKGROUND

Emergency general surgery (EGS) diseases are time-sensitive conditions that require urgent surgical evaluation, yet the effect of geographic access to care on outcomes remains unclear. We examined the association of spatial access with outcomes for common EGS conditions.

METHODS

A retrospective analysis of twelve 2014 State Inpatient Databases, identifying adults admitted with eight EGS conditions, was performed. We assessed spatial access using the spatial access ratio (SPAR)-an advanced spatial model that accounts for travel distance, hospital capacity, and population demand, normalized against the national mean. Multivariable regression models adjusting for patient and hospital factors were used to evaluate the association between SPAR with (a) in-hospital mortality and (b) major morbidity.

RESULTS

A total of 877,928 admissions, of which 104,332 (2.4%) were in the lowest-access category (SPAR, 0) and 578,947 (66%) were in the high-access category (SPAR, ≥1), were analyzed. Low-access patients were more likely to be White, male, and treated in nonteaching hospitals. Low-access patients also had higher incidence of complex EGS disease (low access, 31% vs. high access, 12%; p < 0.001) and in-hospital mortality (4.4% vs. 2.5%, p < 0.05). When adjusted for confounding factors, including presence of advanced hospital resources, increasing spatial access was protective against in-hospital mortality (adjusted odds ratio, 0.95; 95% confidence interval, 0.94-0.97; p < 0.001). Spatial access was not significantly associated with major morbidity.

CONCLUSION

This is the first study to demonstrate that geospatial access to surgical care is associated with incidence of complex EGS disease and that increasing spatial access to care is independently associated with lower in-hospital mortality. These results support the consideration of spatial access in the development of regional health systems for EGS care.

LEVEL OF EVIDENCE

Prognostic and Epidemiologic; Level III.

Estimated travel time and staffing constraints to accessing the Ethiopian health care system: A two-step floating catchment area analysis

Background

Despite large investments in the public health care system, disparities in health outcomes persist between lower- and upper-income individuals, as well as rural vs urban dwellers in Ethiopia. Evidence from Ethiopia and other low- and middle-income countries suggests that challenges in health care access may contribute to poverty in these settings.

Methods

We employed a two-step floating catchment area to estimate variations in spatial access to health care and in staffing levels at health care facilities. We estimated the average travel time from the population centers of administrative areas and adjusted them with provider-to-population ratios. To test hypotheses about the role of travel time vs staffing, we applied Spearman's rank tests to these two variables against the access score to assess the significance of observed variations.

Results

Among Ethiopia's 11 first-level administrative units, Addis Ababa, Dire Dawa, and Harari had the best access scores. Regions with the lowest access scores were generally poorer and more rural/pastoral. Approximately 18% of the country did not have access to a public health care facility within a two-hour walk. Our results suggest that spatial access and staffing issues both contribute to access challenges.

Conclusion

Investments both in new health facilities and staffing in existing facilities will be necessary to improve health care access within Ethiopia. Because rural and low-income areas are more likely to have poor access, future strategies for expanding and strengthening the health care system should strongly emphasize equity and the role of improved access in reducing poverty.

Geographic information science and the United States opioid overdose crisis: A scoping review of methods, scales, and application areas

BACKGROUND

The Opioid Overdose Crisis (OOC) continues to generate morbidity and mortality in the United States, outpacing other prominent accident-related reasons. Multiple disciplines have applied geographic information science (GIScience) to understand geographical patterns in opioid-related health measures. However, there are limited reviews that assess how GIScience has been used.

OBJECTIVES

This scoping review investigates how GIScience has been used to conduct research on the OOC. Specific sub-objectives involve identifying bibliometric trends, the location and scale of studies, the frequency of use of various GIScience methodologies, and what direction future research can take to address existing gaps.

METHODS

The review was pre-registered with the Open Science Framework ((https://osf.io/h3mfx/) and followed the PRISMA-ScR guidelines. Scholarly research was gathered from the Web of Science Core Collection, PubMed, IEEE Xplore, ACM Digital Library. Inclusion criteria was defined as having a publication date between January 1999 and August 2021, using GIScience as a central part of the research, and investigating an opioid-related health measure.

RESULTS

231 studies met the inclusion criteria. Most studies were published from 2017 onward. While many (41.6%) of studies were conducted using nationwide data, the majority (58.4%) occurred at the sub-national level. California, New York, Ohio, and Appalachia were most frequently studied, while the Midwest, north Rocky Mountains, Alaska, and Hawaii lacked studies. The most common GIScience methodology used was descriptive mapping, and county-level data was the most common unit of analysis across methodologies.

CONCLUSIONS

Future research of GIScience on the OOC can address gaps by developing use cases for machine learning, conducting analyses at the sub-county level, and applying GIScience to questions involving illicit fentanyl. Research using GIScience is expected to continue to increase, and multidisciplinary research efforts amongst GIScientists, epidemiologists, and other medical professionals can improve the rigor of research.

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.

Disparities in geographic access to medical oncologists

OBJECTIVE

The objective of this study is to identify disparities in geographic access to medical oncologists at the time of diagnosis.

DATA SOURCES/STUDY SETTING

2014-2016 Pennsylvania Cancer Registry (PCR), 2019 CMS Base Provider Enrollment File (BPEF), 2018 CMS Physician Compare, 2010 Rural-Urban Commuting Area Codes (RUCA), and 2015 Area Deprivation Index (ADI).

STUDY DESIGN

Spatial regressions were used to estimate associations between geographic access to medical oncologists, measured with an enhanced two-step floating catchment area measure, and demographic characteristics.

DATA COLLECTION/EXTRACTION METHODS

Medical oncologists were identified in the 2019 CMS BPEF and merged with the 2018 CMS Physician Compare. Provider addresses were converted to longitude-latitude using OpenCage Geocoder. Newly diagnosed cancer patients in each census tract were identified in the 2014-2016 PCR. Census tracts were classified based on rurality and socioeconomic status using the 2010 RUCA Codes and the 2015 ADI.

PRINCIPAL FINDINGS

Large towns and rural areas were associated with spatial access ratios (SPARs) that were 6.29 lower (95% CI -16.14 to 3.57) and 14.76 lower (95% CI -25.14 to -4.37) respectively relative to urban areas. Being in the fourth ADI quartile (highest disadvantage) was associated with a 12.41 lower SPAR (95% CI -19.50 to -5.33) relative to the first quartile. The observed difference in a census tract's non-White population from the 25th (1.3%) to the 75th percentile (13.7%) was associated with a 13.64 higher SPAR (Coefficient = 1.10, 95% CI 11.89 to 15.29; p < 0.01), roughly equivalent to the disadvantage associated with living in the fourth ADI quartile, where non-White populations are concentrated.

CONCLUSIONS

Rurality and low socioeconomic status were associated with lower geographic access to oncologists. The negative association between area deprivation and geographic access is of similar magnitude to the positive association between larger non-White populations and access. Policies aimed at increasing geographic access to care should be cognizant of both rurality and socioeconomic status.

Medicaid Managed Care: Access To Primary Care Providers Who Prescribe Buprenorphine

Medicaid managed care insurers play a crucial role in facilitating access to buprenorphine to treat opioid use disorder. Using a novel set of provider directory and prescription claims data, we examined variation in access to in-network buprenorphine-prescribing primary care providers among Medicaid managed care enrollees. Approximately 32.2 percent of enrollees had fewer than one in-network buprenorphine prescriber per 100,000 county residents. On average, there were a greater number of in-network buprenorphine-prescribing primary care providers in states with higher compared with lower overdose death rates. However, most enrollees lived in areas with a shortage of these providers. We found that a 25 percent higher network participation rate by prescribers compared with nonprescribers could improve the probability that enrollees see a prescriber by approximately 25 percent. Policies to improve access within Medicaid managed care include using primary care provider assignment algorithms to match patients with buprenorphine prescribers and requiring that networks include a minimum number of buprenorphine prescribers.