Surrogate Markers of Transport Distance for Out-of-Hospital Cardiac Arrest Patients

Socioeconomic Status Among Cochlear Implant Candidates and Association With Surgical Pursuance

Importance

Despite the sizeable global burden of hearing loss, cochlear implants have poor penetrance among eligible hearing-impaired individuals. Identifying populations who may benefit from a cochlear implant but among whom penetrance is poor is an important aim in reducing the health-related and economic effects of hearing loss on both individuals and society.

Objectives

To explore the association of socioeconomic status (SES) with cochlear implant candidacy and the decision to undergo cochlear implantation.

Design, Setting, and Participants

This retrospective cohort study was performed in a tertiary academic center. All adult patients evaluated for cochlear implant candidacy from January 1, 1999, through December 31, 2022, were included in the analysis.

Exposures

Household income quintile and rural or urban residence were used as proxies for SES based on zip code linkage to US Census and US Department of Agriculture data.

Main Outcomes and Measures

Odds of cochlear implant candidacy and surgery.

Results

A total of 754 individuals underwent candidacy evaluations and were included in the analysis (386 [51.2%] women; mean [SD] age, 64.0 [15.7] years). Of these, 693 (91.9%) were cochlear implant candidates, and 623 candidates (89.9%) underwent cochlear implantation. Multivariable analyses demonstrated that individuals in the highest income quintile had lower odds of cochlear implant candidacy compared with those in the lowest income quintile (odds ratio [OR], 0.26 [95% CI, 0.08-0.91]), and candidates in the highest income quintile had greater odds of undergoing cochlear implant surgery compared with those in the lowest quintile (OR, 2.59 [95% CI, 1.14-5.86]). Living in a small town or a micropolitan or rural area was associated with lower odds of undergoing cochlear implant surgery compared with living in a metropolitan core (OR, 0.18 [95% CI, 0.04-0.83]) after controlling for distance to the primary implant center.

Conclusions and Relevance

The findings of this cohort study suggest that individuals with higher SES are less likely to qualify for a cochlear implant; however, those who qualify are more likely to undergo surgery compared with those with lower SES. These findings highlight a hearing health care disparity that should be addressed through further studies to guide population-based initiatives.

Challenging terrains: socio-spatial analysis of Primary Health Care Access Disparities in West Virginia

Existing measures of health care access were inadequate for guiding policy decisions in West Virginia, as they identified the entire state as having limited access. To address this, we compiled a comprehensive database of primary health care providers and facilities in the state, developed a modified E2SFCA tool to measure spatial access in the context of West Virginia's rural and mountainous nature, and integrated this with an index of socio-economic barriers to access. The integrated index revealed that the rural areas, especially in the southern part of the state, have especially limited access to primary health care. 1. Introduction. An emerging public health issue which has been exacerbated by the COVID-19 pandemic, is that of healthcare deserts, which are places where basic affordable health care is not accessible for residents. This problem has become worse in rural areas as rural hospitals close. In these areas, including West Virginia, scattered populations suffer from limited access to primary healthcare services. Uneven geographic and socio-economic barriers to accessing primary health care are major contributing factors to these health disparities. West Virginia's unique rural and mountainous settlement patterns, aging population, and economic crisis over the past two decades have resulted in unequal access to the primary healthcare services for its residents. The rural nature of the state makes it difficult to maintain medical facilities accessible to much of the population, especially as rural hospitals have been closing, such as the one in Williamson, WV (Jarvie, 2020). The mountainous terrain slows down travel across winding roads, lengthening travel times to the nearest hospital, while an aging population has increased health care needs. Lastly, an economic crisis and higher poverty rate makes West Virginians less able to pay for health care. As a result, West Virginians are confronting a health crisis. According to a recent report by the West Virginia Health Statistics Center (2019), West Virginians rank first in the country for heart attacks, have the second-highest obesity rate and prevalence of mental health problems in the country, along with the fourth-highest rate of diabetes and fifth-highest rate of cancer. An issue faced by West Virginia's policymakers is the limitations of tools for identifying and assessing healthcare deserts, as they are poorly suited for the unique challenges in West Virginia. Academic research has not analyzed comprehensive primary healthcare accessibility in WV, although previous studies have focused on Appalachia (e.g., Behringer & Friedell 2006; Smith & Holloman, 2011; Elnicki et al., 1995; Donohoe et al., 2015, 2016a, 2016b), and others focus on access to more specialized services (Valvi et al., 2019; Donohoe, 2016a). Existing approaches to identify the healthcare deprived areas, such as Health Professional Shortage Areas (HPSA), are not suitable for guiding West Virginia policies, because every one of the 55 counties within the state has several HPSAs, which makes prioritizing resources difficult. The lack of easily accessible, comprehensive, and up-to-date physician and healthcare facility database creates additional difficulties. Physician license datasets were found to often include inconsistent, misleading, and out-of-date information. The last limitation of the HPSA designation is that it is based on zip code areas and census tracts, which are not ideal as zip code areas lack spatial context and much covariate data, while rural census tracts are too large to capture spatial variation of access. In this context, the WV HealthLink project was begun with joint effort with WV Rural Health Initiative (RHI) to fill gaps in research and support decision making for primary healthcare access in West Virginia. The goals of the projects are: (1) to help West Virginia's three medical schools provide specialized professional training in rural healthcare; (2) to address health disparities by investing in clinical projects in underserved areas; and (3) to retain health professionals in WV. In 2018, to support these goals, HealthLink was invited by the RHI's leadership to analyze disparities in primary health care access in West Virginia and develop tools for rural healthcare decision-making. These goals also create a comprehensive and up-to-date physician and facility database, new analysis tools, and new visualization tools for decision support. The goals of this paper are to assess the spatial and social accessibility of primary health care in West Virginia, and to understand spatial and social determinants that shape this access. To achieve these goals, this paper completes the following objectives: (1) define primary healthcare and access; (2) build an extensive and up-to-date primary healthcare database; (3) develop an assessment framework for WV; and (4) visualize the results for policy makers and practitioners. The structure of this paper is as follows. First, we describe three methodological problems encountered as we define primary health care access. Second, we present the methods used to resolve these problems, and conclude by presenting our modified enhanced two-step floating catchment area (E2FCA hereafter) approach and its results for WV. Our foci in this modification were improving the accuracy of the analysis regarding measuring distance, considering distance decay effect, and more precisely representing the location of supply and demand.

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

The efficient operation of emergency medical services is critical for any society. Typically, optimisation and simulation models support decisions on emergency ambulance stations’ locations and ambulance management strategies. Essential inputs for such models are the spatiotemporal characteristics of ambulance trips. Access to data on the movements of ambulances is limited, and therefore modelling efforts often rely on assumptions (e.g., the Euclidean distance is used as a surrogate of the ambulance travel time; the closest available ambulance is dispatched to a call; or the travel time estimates, offered by application programming interfaces for ordinary vehicles, are applied to ambulances). These simplifying assumptions are often based on incomplete data or common sense without being fully supported by the evidence. Thus, data-driven research to model ambulance trips is required. We investigated a unique dataset of global positioning system-based measurements collected from seventeen emergency ambulances over three years. We enriched the data by exploring external sources and designed a rule-based procedure to extract ambulance trips for emergency cases. Trips were split into training and test sets. The training set was used to develop a series of statistical models that capture the spatiotemporal characteristics of emergency ambulance trips. The models were used to generate synthetic ambulance trips, and those were compared with the test set to decide which models are the most suitable and to evaluate degrees to which they fit the statistical properties of real-world trips. As confirmed by the low values of the Kullback–Leibler divergence (0.004–0.229) and by the Kolmogorov–Smirnov test at the significance level of 0.05, we found a very good fit between the probability distributions of spatiotemporal properties of synthetic and real trips. A reasonable modelling choice is a model where the exponential dependency on the population density is used to locate emergency cases, emergency cases are allocated to hospitals following empirical probabilities, and ambulances are routed using the fastest paths. The models we developed can be used in optimisations and simulations to improve their validity.

Effect of Distance to Trauma Centre, Trauma Centre Level, and Trauma Centre Region on Fatal Injuries among Motorcyclists in Taiwan

Background: Studies have suggested that trauma centre-related risk factors, such as distance to the nearest trauma hospital, are strong predictors of fatal injuries among motorists. Few studies have used a national dataset to study the effect of trauma centre-related risk factors on fatal injuries among motorists and motorcyclists in a country where traffic is dominated by motorcycles. This study investigated the effect of distance from the nearest trauma hospital on fatal injuries from two-vehicle crashes in Taiwan from 2017 to 2019. Methods: A crash dataset and hospital location dataset were combined. The crash dataset was extracted from the National Taiwan Traffic Crash Dataset from 1 January 2017 through 31 December 2019. The primary exposure in this study was distance to the nearest trauma hospital. This study performed a multiple logistic regression to calculate the adjusted odds ratios (AORs) for fatal injuries. Results: The multivariate logistic regression models indicated that motorcyclists involved in crashes located ≥5 km from the nearest trauma hospital and in Eastern Taiwan were approximately five times more likely to sustain fatal injuries (AOR = 5.26; 95% CI: 3.69–7.49). Conclusions: Distance to, level of, and region of the nearest trauma centre are critical risk factors for fatal injuries among motorcyclists but not motorists. To reduce the mortality rate of trauma cases among motorcyclists, interventions should focus on improving access to trauma hospitals.

Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

BACKGROUND

Access as a primary indicator of Emergency Medical Service (EMS) efficiency has been widely studied over the last few decades. Most previous studies considered one-way trips, either getting ambulances to patients or transporting patients to hospitals. This research assesses spatiotemporal access to EMS at the shequ (the smallest administrative unit) level in Wuhan, China, attempting to fill a gap in literature by considering and comparing both trips in the evaluation of EMS access.

METHODS

Two spatiotemporal access measures are adopted here: the proximity-based travel time obtained from online map services and the enhanced two-step floating catchment area (E-2SFCA) which is a gravity-based model. First, the travel time is calculated for the two trips involved in one EMS journey: one is from the nearest EMS station to the scene (i.e. scene time interval (STI)) and the other is from the scene to the nearest hospital (i.e. transport time interval (TTI)). Then, the predicted travel time is incorporated into the E-2SFCA model to calculate the access measure considering the availability of the service provider as well as the population in need. For both access measures, the calculation is implemented for peak hours and off-peak hours.

RESULTS

Both methods showed a marked decrease in EMS access during peak traffic hours, and differences in spatial patterns of ambulance and hospital access. About 73.9% of shequs can receive an ambulance or get to the nearest hospital within 10 min during off-peak periods, and this proportion decreases to about 45.5% for peak periods. Most shequs with good ambulance access but poor hospital access are in the south of the study area. In general, the central areas have better ambulance, hospital and overall access than peripheral areas, particularly during off-peak periods.

CONCLUSIONS

In addition to the impact of peak traffic periods on EMS access, we found that good ambulance access does not necessarily guarantee good hospital access nor the overall access, and vice versa.

Analyzing Spatial Variance of Airbnb Pricing Determinants Using Multiscale GWR Approach

A sharing economy accommodation service like Airbnb, which provides trust between strangers to connect them for profiting from underutilized assets, was born and has thrived thanks to the innovations in the platform technology. Due to the unique structure of Airbnb, the pricing strategies of hosts are very different from the conventional hospitality industry. However, existing Airbnb pricing studies have limitations considering the varying scale of operation among hosts, spatial variances in pricing strategies, and crucial geographic information for estimating the influence of the pricing variables, as well as ignoring inter-city variances. In this research, we explored the spatially heterogeneous relationship between price and pricing variables using an innovative spatial approach, Multiscale Geographically Weighted Regression (MGWR). Analysis results for Airbnb listing in Log Angeles and New York in the US showed the effectiveness of MGWR regarding estimating the influence of pricing variables spatially. By revealing spatially heterogeneous and dependent relationships, this research fills gaps in Airbnb pricing research and deepens the understanding of the pricing strategies of the hosts.

Exploring the spatial relationship between primary road distance to antenatal clinics and HIV prevalence in pregnant females of Lilongwe, Malawi

While urbanization in a sub-Saharan African (SSA) context can lead to greater independence in women, various sociological, biological, and geographical factors in urban areas may keep women at a higher risk for HIV than men. Access to major roads during Malawi's transition into rapid urbanization may leave women disproportionately vulnerable to HIV infection. It is not well established whether women who report to health clinics closer to major roads have higher or lower levels of HIV. In this study we explored the spatial heterogeneity of HIV prevalence among pregnant females in Lilongwe District, Malawi. Using Geographic Information Systems, we visually represented patterns of HIV prevalence in relation to primary roads. HIV prevalence data for 2015 were obtained from 44 antenatal clinics (ANC) in Lilongwe District. ANC prevalence data were aggregated to the administrative area and mapped. Euclidean distance between clinics and two primary roads that run through Lilongwe District were measured. A correlation was run to assess the relationship between area-level ANC HIV prevalence and clinic distance to the nearest primary road. ANC HIV prevalence ranged from 0% to 10.3%. Clinic to major road distance ranged from 0.1 to 35 km. Correlation results ( r= -0.622, p = 0.002) revealed a significant negative relationship between clinic distance to primary road and HIV prevalence, indicating that the farther the clinics stood from primary roads, the lower the reported antenatal HIV prevalence. Overall, the clinic catchments through which the major roads run reported higher ANC HIV prevalence. Antenatal HIV prevalence decreases as ANC distance from primary roads increases in Lilongwe, Malawi. As urbanization continues to grow in this region, road distance may serve as a good indicator of HIV burden and help to guide targeted prevention and treatment efforts.

Barriers for pregnant women living in rural, agricultural villages to accessing antenatal care in Cambodia: A community-based cross-sectional study combined with a geographic information system

Background

Maternal morbidity and mortality is still a major public health issue in low- and middle-income countries such as Cambodia. Improving access to antenatal care (ANC) services for pregnant women has been widely recognized as one of the most effective means of reducing maternal mortality and morbidity. As such, this study examined the barriers for pregnant women living in rural, agricultural villages to accessing ANC based on data collected in the Ratanakiri province, one of the least developed provinces in Cambodia, using a combination of a community-based cross-sectional survey and a geographic information system (GIS).

Methods

A community-based cross-sectional survey was conducted among 377 mothers with children under the age of two living in 62 villages in the Ratanakiri province, Cambodia, in December 2015. Face-to-face interviews were conducted to ask mothers about their ANC service use, knowledge of ANC, barriers to accessing health facilities, and complications they experienced during the most recent pregnancy. At the same time, GIS data were also collected using a Global Positioning System (GPS) to accurately measure actual travel distance of pregnant women to access health facilities and to examine geographical and environmental barriers in greater detail.

Results

Only a third of the mothers met the recommendations made by the World Health Organization (WHO) of receiving ANC four times or more (achieved ANC4+), and a quarter of the mothers had never received ANC during their most recent pregnancy. Factors positively associated with achieving ANC4+ were mother’s secondary or higher education (adjusted odds ratio [AOR] = 5.50, 95% confidence interval [CI]: 1.74, 17.37), being aware that receiving ANC is recommended (AOR = 2.74, 95% CI: 1.25, 6.00), and knowledge about the recommended frequency for ANC (AOR = 2.26, 95% CI: 7.22). Actual travel distance was negatively associated with achieving ANC4+. Mothers who had to travel 10.0–14.9 km were 68% less likely (AOR = 0.32, 95% CI: 0.10, 0.99), and those who had to travel 15.0 km or longer were 79% less likely (AOR = 0.21, 95% CI: 0.07, 0.62) to have achieved ANC 4+, both compared to those who travelled 5.0 km or less. While most previous studies have used a straight-line to measure distance traveled, this study much more accurately measured the actual distance traveled by using a GIS. As a result, there was a statistically significant discrepancy between actual travel distance and straight-line distance.

Conclusions

This study revealed promoting factors and barriers for ANC use among pregnant women living in remote, agricultural villages in Cambodia. Furthermore, this study highlights the importance of measuring travel distances accurately to ensure that targeted interventions for ANC are not misguided by straight-line distances. The methodology used in this study can be applied widely to other developing countries, especially in remote areas with limited road networks where there may be a large discrepancy between actual and straight-line distances.

Assessing spatial patterns of HIV knowledge in rural Mozambique using geographic information systems

OBJECTIVES

To conduct a cross-sectional mapping analysis of HIV knowledge in Zambézia Province, Mozambique, and to examine spatial patterns of HIV knowledge and associated household characteristics.

METHODS

A population-based cluster survey was administered in 2010; data were analysed from 201 enumeration areas in three geographically diverse districts: Alto Molócuè, Morrumbala and Namacurra. We assessed HIV knowledge scores (0-9 points) using previously validated assessment tools. Using geographic information systems (GIS), we mapped hot spots of high and low HIV knowledge. Our multivariable linear regression model estimated HIV knowledge associations with distance to nearest clinic offering antiretroviral therapy, respondent age, education, household size, number of children under five, numeracy, literacy and district of residence.

RESULTS

We found little overall HIV knowledge in all three districts. People in Alto Molócuè knew comparatively most about HIV, with a median score of 3 (IQR 2-5) and 22 of 51 (43%) enumeration areas scoring ≥4 of 9 points. Namacurra district, closest to the capital city and expected to have the best HIV knowledge levels, had a median score of 1 (IQR 0-3) and only 3 of 57 (5%) enumeration areas scoring ≥4 points. More HIV knowledge was associated with more education, age, household size, numeracy and proximity to a health facility offering antiretroviral therapy.

CONCLUSIONS

HIV knowledge is critical for its prevention and treatment. By pinpointing areas of poor HIV knowledge, programme planners can prioritize educational resources and outreach initiatives within the context of antiretroviral therapy expansion.

Surgical patients travel longer distances than non-surgical patients to receive care at a rural hospital in Mozambique

BACKGROUND

Surgical care is increasingly recognised as an important component of global health delivery. However, there are still major gaps in knowledge related to access to surgical care in low-income countries. In this study, we compare distances travelled by surgical patients with patients seeking other medical services at a first-level hospital in rural Mozambique.

METHODS

Data were collected on all inpatients at Hospital Rural de Chókwè in rural Mozambique between 20 June 2012 and 3 August 2012. Euclidean distances travelled by surgical versus non-surgical patients using coordinates of each patient's city of residence were compared. Data were analysed using ArcGIS 10 and STATA.

RESULTS

In total, 500 patients were included. Almost one-half (47.6%) lived in the city where the hospital is based. By hospital ward, the majority (62.0%) of maternity patients came from within the hospital's city compared with only 35.2% of surgical patients. The average distance travelled was longest for surgical patients (42 km) compared with an average of 17 km for patients on all other wards.

CONCLUSIONS

Patients seeking surgical care at this first-level hospital travel farther than patients seeking other services. While other patients may have access to at community clinics, surgical patients depend more heavily on the services available at first-level hospitals.

Methods to measure potential spatial access to delivery care in low- and middle-income countries: a case study in rural Ghana

BACKGROUND

Access to skilled attendance at childbirth is crucial to reduce maternal and newborn mortality. Several different measures of geographic access are used concurrently in public health research, with the assumption that sophisticated methods are generally better. Most of the evidence for this assumption comes from methodological comparisons in high-income countries. We compare different measures of travel impedance in a case study in Ghana's Brong Ahafo region to determine if straight-line distance can be an adequate proxy for access to delivery care in certain low- and middle-income country (LMIC) settings.

METHODS

We created a geospatial database, mapping population location in both compounds and village centroids, service locations for all health facilities offering delivery care, land-cover and a detailed road network. Six different measures were used to calculate travel impedance to health facilities (straight-line distance, network distance, network travel time and raster travel time, the latter two both mechanized and non-mechanized). The measures were compared using Spearman rank correlation coefficients, absolute differences, and the percentage of the same facilities identified as closest. We used logistic regression with robust standard errors to model the association of the different measures with health facility use for delivery in 9,306 births.

RESULTS

Non-mechanized measures were highly correlated with each other, and identified the same facilities as closest for approximately 80% of villages. Measures calculated from compounds identified the same closest facility as measures from village centroids for over 85% of births. For 90% of births, the aggregation error from using village centroids instead of compound locations was less than 35 minutes and less than 1.12 km. All non-mechanized measures showed an inverse association with facility use of similar magnitude, an approximately 67% reduction in odds of facility delivery per standard deviation increase in each measure (OR = 0.33).

CONCLUSION

Different data models and population locations produced comparable results in our case study, thus demonstrating that straight-line distance can be reasonably used as a proxy for potential spatial access in certain LMIC settings. The cost of obtaining individually geocoded population location and sophisticated measures of travel impedance should be weighed against the gain in accuracy.

A geographical perspective on access to sexual and reproductive health care for women in rural Africa

Utilization of sexual and reproductive health (SRH) services can significantly impact health outcomes, such as pregnancy and birth, prenatal and neonatal mortality, maternal morbidity and mortality, and vertical transmission of infectious diseases like HIV/AIDS. It has long been recognized that access to SRH services is essential to positive health outcomes, especially in rural areas of developing countries, where long distances as well as poor transportation conditions, can be potential barriers to health care acquisition. Improving accessibility of health services for target populations is therefore critical for specialized healthcare programs. Thus, understanding and evaluation of current access to health care is crucial. Combining spatial information using geographical information system (GIS) with population survey data, this study details a gravity model-based method to measure and evaluate access to SRH services in rural Mozambique, and analyzes potential geographic access to such services, using family planning as an example. Access is found to be a significant factor in reported behavior, superior to traditional distance-based indicators. Spatial disparities in geographic access among different population groups also appear to exist, likely affecting overall program success.