Delineating Hierarchical Hospital Service Areas in Florida

Hospital service area (HSA) and hospital referral region (HRR), known as a hierarchical HSA system, have been used as analysis units in a growing body of large‐scale studies of healthcare spending, utilization, and outcome in the United States. However, the popular Dartmouth HSAs and HRRs were produced more than two decades ago and are unable to represent contemporary healthcare markets. This research uses a revised Huff Model to delineate two levels of hospital service areas in Florida, resulting in sixty‐four HSAs nested in twenty‐one HRRs. Three elements distinguish our method from existing work. First, a best‐fitting distance‐decay function derived from the actual travel pattern of hospitalization is embedded in the Huff Model to strengthen the model's theoretical foundation in individual spatial behavior. Secondly, the hierarchal central place structure is supported by the differing travel‐friction coefficients for general versus specialized patients; general patients experience a steeper gradient and thus a shorter average travel range that supports delineating more HSAs of smaller area size, and specialized patients exhibit a flatter gradient and thus a longer average travel range that leads to fewer HRRs of large‐sized areas. Finally, the delineation method automated in geographic information systems (GIS) can be easily replicated in other regions to define large‐scale and consistent hierarchical HSA systems.     

Evaluating and re-demarcating the Hospital Service Areas in Florida

The Hospital Service Areas (HSAs) better portray underlying local patterns of hospitalization than administrative units, and offer a promising analysis unit for studies of healthcare market. The widely used Dartmouth HSAs in the U.S. were solely based on Medicare inpatient records about two decades ago. Our analysis used all discharge records from Florida hospitals in the 2011 Healthcare Cost and Utilization Project (HCUP) dataset from the Agency for Healthcare Research and Quality (AHRQ). We first matched Medicare-paid hospitalization records in 2011 to the Dartmouth HSAs for demonstrating the temporal variation of the Medicare-derived HSAs. We then compared the HSA configurations based on the overall hospitalization records to Medicare-derived HSAs in the same year (2011) for assessing the representativeness of the Medicare-derived HSAs. Results indicate the boundaries of the Medicare-derived HSAs have significantly shifted over two decades and are inadequate in representing the overall population. The Huff model was used to generate more solid HSAs than traditional approaches.     

Using a Huff-Based Model to Delineate Hospital Service Areas

Hospital service areas (HSAs) are increasingly adopted as a basic analysis unit for health care studies. The popular Dartmouth HSAs were produced more than two decades ago, and the process was far from automated. This research uses a Huff-based model automated in a geographic information systems (GIS) environment to delineate HSAs. Based on the Florida State Inpatient Database (SID) in 2011, a best-fitting distance decay function is derived from the actual travel patterns of hospitalization and then fed into the Huff model to strengthen the model's theoretical foundation in individual spatial behavior. The HSAs derived from the Huff-based model are then compared to the traditional flow-based HSAs defined by the Dartmouth method and assessed in terms of self-containment and heterogeneity of internal socioeconomic structure and urbanicity. The Huff-based model requires fewer data and is easy to implement as an automated toolkit and thus has great potential for replication in other regions to define large-scale and consistent HSAs.     

Planning hierarchical hospital service areas for maternal care using a network optimization approach: A case study in Hubei,China

Improving maternal health is one of the Sustainable Development Goals. Hospital service areas (HSAs), which contain most hospitalization behaviors at the local scale, are crucial for health care planning. However, little attention has been given to HSAs for maternal care and the hierarchy structure. Considering Hubei, central China, as a case study, this study aims to fill these gaps by developing a method for delineating hierarchical HSAs for maternal care using a network optimization approach. The approach is driven by actual patient flow data and has an explicit objective to maximize the modularity. It also establishes the hierarchical structure of maternal care HSAs, which is fundamental for the planning of hierarchical maternal care and referral systems. In our case study, 45 secondary HSAs and 22 tertiary HSAs are delineated to achieve maximal modularity. The HSAs perform well in terms of indices such as the Localization Index and Market Share Index. Furthermore, there is a complementary relationship between secondary and tertiary hospitals, which suggests the need for referral system planning. This study can provide evidence for the validity of the HSA and the planning of maternal care HSAs in China. It also provides transferable methods for planning hierarchical HSAs in other developing countries.     

Evaluation of Weights of Evidence to Predict Epithermal-Gold Deposits in the Great Basin of the Western United States

The weights-of-evidence method provides a simple approach to the integration of diverse geologic information. The application addressed is to construct a model that predicts the locations of epithermal-gold mineral deposits in the Great Basin of the western United States. Weights of evidence is a data-driven method requiring known deposits and occurrences that are used as training sites in the evaluated area. Four hundred and fifteen known hot spring gold–silver, Comstock vein, hot spring mercury, epithermal manganese, and volcanogenic uranium deposits and occurrences in Nevada were used to define an area of 327.4 km² as training sites to develop the model. The model consists of nine weighted-map patterns that are combined to produce a favorability map predicting the distribution of epithermal-gold deposits. Using a measure of the association of training sites with predictor features (or patterns), the patterns can be ranked from best to worst predictors. Based on proximity analysis, the strongest predictor is the area within 8 km of volcanic rocks younger than 43 Ma. Being close to volcanic rocks is not highly weighted, but being far from volcanic rocks causes a strong negative weight. These weights suggest that proximity to volcanic rocks define where deposits do not occur. The second best pattern is the area within 1 km of hydrothermally altered areas. The next best pattern is the area within 1 km of known placer-gold sites. The proximity analysis for gold placers weights this pattern as useful when close to known placer sites, but unimportant where placers do not exist. The remaining patterns are significantly weaker predictors. In order of decreasing correlation, they are: proximity to volcanic vents, proximity to east-west to northwest faults, elevated airborne radiometric uranium, proximity to northwest to west and north-northwest linear features, elevated aeromagnetics, and anomalous geochemistry. This ordering of the patterns is a function of the quality, applicability, and use of the data. The nine-pattern favorability map can be evaluated by comparison with the USGS National Assessment for hot spring gold–silver deposits. The Spearman's ranked correlation coefficient between the favorability and the National Assessment permissive tracts is 0.5. Tabulations of the areas of agreement and disagreement between the two maps show 74% agreement for the Great Basin. The posterior probabilities for 51 significant deposits in the Great Basin, both used and not used in the model, show the following: 26 classified as favorable; 25 classified as permissive; and 1, Florida Canyon, classified as nonpermissive.The Florida Canyon deposit has a low favorability because there are no volcanic rocks near the deposit on the Nevada geologic map used. The largest areas of disagreement are caused by the USGS National Assessment team concluding that volcanic rocks older than 27 Ma in Nevada are not permissive, which was not assumed in this model. The weights-of-evidence model is evaluated as reasonable and delineates permissive areas for epithermal deposits comparable to expert's delineation. The weights-of-evidence model has the additional characteristics that it is well defined, reproducible, objective, and provides a quantitative measure of confidence.     

Potential habitat of Acropora spp. on Florida reefs

Elkhorn and staghorn corals (Acropora palmata, Acropora cervicornis) were listed as threatened species under the Endangered Species Act in 2005. The decline of these species beginning in the late 1970s is unprecedented given the vital role they historically played as major builders of western Atlantic and Caribbean coral reefs. The goal of this study was to create potential-habitat maps for A. palmata and A. cervicornis that would show areas in which these species currently exist, as well as areas that would be suitable for their (re)establishment, using a database of reported in situ observations and existing mapped data. Using the mapped coral reef and hardbottom classifications throughout the Florida reef tract, potential-habitat maps were generated using buffers that incorporated 95% and 99% of reported observations of colonies of Acropora spp. The potential-habitat maps were produced based on benthic substrates throughout the Florida reef tract using GIS software. Locations of 99% of A. palmata observations and 84% of A. cervicornis observations coincided with previously mapped coral reef or hardbottom habitat. These results indicate that potential habitat for A. palmata is currently well defined and that potential habitat for A. cervicornis is more variable and has a wider range than that for A. palmata. This study provides a novel method of combining datasets at various geographic spatial scales and may be used to inform the current NOAA critical habitat map. One of the most important differences between the current NOAA critical habitat map and the new potential-habitat map is observed in the southeast Florida region, where A. cervicornis appears to be thriving outside of mapped reef areas and at latitudes considered marginal for hermatypic corals. Thus, the potential habitat extends further north than the previous critical habitat - and encompasses additional habitat for A. cervicornis and potentially for A. palmata.     

交通拥堵对急救医疗服务时空可达性的影响——以广州市为例

时间是急救服务的敏感因素,急救服务设施可达性的时空差异对于评估急救设施的选址及急救服务调度的效率,解决公众急救医疗需求与供给之间的矛盾,辅助政府部门的决策都至关重要。交通拥堵是常见的城市问题,尤其是在城市中心区域更为明显,由于交通拥堵带来的时间滞后对急救服务产生的影响不容忽视。本文通过浮动车GPS大数据,分析交通拥堵对广州市中心城区急救医疗设施时空可达性的影响。结果表明：①在考虑道路实际通行状况的情况下,在交通高峰期,社区的急救医疗服务平均可达时间和最长可达时间分别比采用设计时速计算增加20%和25%。②可达性存在明显的时空差异。急救医疗服务可达性以急救医院为中心,沿着路网向四周呈现衰减趋势。急救医院布局较多、路网密集区域的可达性高,反之则低。交通拥堵对路网密集、行车规则设计复杂以及存在通过性交通流的地区影响显著。③对不同阻抗系数下可达性变化的敏感性分析,发现随着阻抗系数的增大,可达性变化的趋势有所放缓,紧急医疗服务可达性的分异变小;这一变化趋势在交通平峰期表现更为明显。因此,在研究城市中心区域急救医疗服务时,考虑交通拥堵对可达性的影响,需要构建基于实时交通状况的可达性评估模型,合理选择模型参数,优化实时急救医疗服务调度,提升急救服务的效率和质量。     

广州SARS流行过程的空间模式与分异特征

根据广州市SARS感染者的家庭住址信息进行空间化处理,得到了不同SARS感染人群在空间上的分布,并用数据模型定量表达了广州市SARS疫区的传播中心及其置信范围,结合SARS接收医院中心点的分布及其变化规律,对不同感染人群传播中心的异质性及其变化规律进行了分析,结果表明:随着疫情的发展,广州市SARS传播中心具有明显的向SARS接收医院中心点接近的趋势,且变化规律与SARS接收医院中心点的迁移规律大致相同,医院传播对广州市SARS传播过程有重要影响,且经历了由强到弱再到强的变化过程。本文研究有助于更好地了解SARS及其他新型传染病在都市区的空间传播扩散过程,并为公共卫生应急预案提供科学依据。     

农业旅游地游客感知结构模型与应用——以西南少数民族地区为例

从旅游者感知视角分析少数民族地区农业旅游地发展中出现的问题并探讨解决方法。采用SEM结构方程对3个西南少数民族地区国家农业旅游示范点地进行研究。结果表明,所构建的农业旅游者感知模型具有跨样本一致性特征,有较强解释力。研究首次运用结构方程单独定量验证少数民族地区特色旅游商品对旅游者满意度与忠诚度的显著影响(γ13＝0.26 ^** ),同时揭示农业旅游地游客满意度与忠诚度的显著关联(β21＝0.88 ^*** ),旅游资源与软件服务对游客满意度的显著影响(γ11＝0.48 ^*** ,γ12＝0.20^*),并且发现旅游硬件服务与游客满意度之间不存在必然联系,少数民族农业旅游地自然风光、乡村风貌、民族风情等主题特色的保持与挖掘是吸引旅游者的关键因素。     

就医空间可达性分析的两步移动搜索法——以江苏省东海县为例

精确评价医疗设施可达性的空间分异样状况是合理配置医疗资源的前提。本文在回顾国内外关于医疗空间可达性研究的基础上, 采用两步移动搜索法, 以江苏省贫困县--东海县为案例, 以行政村和医院为分析单元, 基于迪卡斯特拉算法计算出各村到医院(卫生院)的最短通行时间, 进而分析各村医疗空间可达性分异情况。采用不用服务时间阈值范围进行空间敏感性分析, 综合研判缺医地区分布特点。与传统的医卫人员和人口比值的方法相比, 两步移动搜索法能有效显示县域范围内医疗可达性的空间分异情况。采用较大的时间阈值, 医疗空间可达性分异较为平滑, 采用较小服务阈值则空间分异显著, 缺医范围也较大。东海县医疗空间可达性整体呈单核结构, 并沿主要交通线延伸, 缺医地区多分布于边缘乡镇。提高边缘乡镇的行政村的甲级卫生院等级和乡村道路等级将会改善边缘乡镇的就医可达性。     

Local spatiotemporal dynamics of a simple aridity index in a region susceptible to desertification

Increased aridity is a robust proximate cause of desertification, both indirectly through greater rainfall variability and directly through prolonged droughts. The south of continental Portugal has large areas with high susceptibility to desertification. This study evaluates local dynamics in dryness in the south of Portugal based on the Aridity Intensity Index (AII), which is a numerical indicator of the degree of dryness of the climate and an indirect indicator of soil moisture availability. The AII was computed using daily precipitation data from stations with records within the 1940–1999 period in the south of Portugal. Annual scenarios of the AII were generated from 1940 to 1999 using direct sequential simulation (DSS). Those scenarios were then used to produce an additional set of maps that summarize their underlying space–time patterns. Two desertification indicators accounting for local dryness dynamics are proposed, namely the Dryness Susceptibility Indicator and the Dryness Trend Indicator. The results show that the southeast region is the most threatened by droughts and extreme dryness. Moreover, there is a tendency towards drier climatic conditions in coastal areas and in the centre of the study region. These findings are likely to have profound implications in agricultural planning and water supply management.     

Linking Spatial and Temporal Variation at Multiple Scales in a Heterogeneous Landscape*

Anthropogenic, ecological, and land‐surface processes interact in landscapes at multiple spatial and temporal scales to create characteristic patterns. The relationships between temporally and spatially varying processes and patterns are poorly understood because of the lack of spatiotemporal observations of real landscapes over significant stretches of time. We report a new method for observing joint spatiotemporal landscape variation over large areas by analyzing multitemporal Landsat data. We calculate the spatiotemporal variation of the Normalized Difference Vegetation Index (NDVI) in the area covered by one Landsat scene footprint in north central Florida, over spatial windows of 10⁴–10⁸ m² and time steps of two to sixteen years. The correlations, slopes, and intercepts of spatial versus temporal regressions in the real landscape all differ significantly from results obtained using a null model of a randomized landscape. Spatial variances calculated within windows of 10⁵–10⁷ m² had the strongest relationships with temporal variances (regressions with both larger and smaller windows had lower coefficients of determination), and the relationships were stronger with longer time steps. Slopes and y‐intercepts increased with window size and decreased with increased time step. The spatial and temporal scales at which NDVI signals are most strongly related may be the characteristic scales of the processes that most strongly determine landscape patterns. For example, the important time and space windows correspond with areas and timing of fires and tree plantation harvests. Observations of landscape dynamics will be most effective if conducted at the characteristic scales of the processes, and our approach may provide a tool for determining those scales.     

JAMGIS,the first Jamaican Government comprehensive multi-data geographical information system Achievements and problems

Abstract

JAMGIS, the first comprehensive multi-data geographical information system (GIS) in Jamaica, has been developed by the Ministry of Agriculture in cooperation with USAID and two universities in the U.S.A. The system and its database are described and a number of problems encountered in its development and practical application are discussed. The most valuable products to date have been the delineation of areas of crop suitability, two series of twelve land use/cover maps at 1:50000 scale and statistical analyses of soil and land resources.     

Mapping and assessing crop diversity in the irrigated Fergana Valley,Uzbekistan

Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.     

Highly variable sediment distribution in shallow, wind-stressed lakes: a case for sediment-mapping surveys in paleolimnological studies

We examine sediment distribution patterns in seven Florida lakes and discuss implications for paleolimnological studies of shallow, subtropical lakes. The study lakes are highly productive and should exhibit thick organic sediment deposits, but organic sediments are often grossly lacking because basins are shallow, and frequent mixing, lack of stratification, and warm temperatures lead to breakdown of organic material.Organic sediment distribution patterns are highly variable. We observe three types of distribution patterns. When organic sediments are abundant, there may be (1) uniform sediment distribution. In lakes lacking organic sediments, there are (2) distribution to deeper areas if present, or (3) distribution to peripheral areas and embayments when deep waters are absent. We advocate the use of systematic mapping surveys to locate optimal coring sites for paleolimnological studies of shallow, wind-stressed lakes. Because numerous factors affect diagenesis and sediment redistribution, sediment abundance and location are not predictable. Sediment chronologies may be discontinuous and disturbed even in accumulation zones. The extent to which sedimentary records are discontinuous or disturbed is not quantifiable in any practical manner. ²¹⁰Pb and ¹³⁷Cs radioisotopic profiles provide qualitative evidence of the degree of stratigraphic disturbance. Total excess ²¹⁰Pb inventories show that sediments are focused into depositional zones when sediment distribution is uneven. Excess ²¹⁰Pb inventories are not informative about the completeness of sedimentary profiles unless small inventories suggest discontinuous sedimentation or erosional events. We present examples of disturbed and undisturbed profiles, and discuss how we use radioisotopic and geochemical evidence, and multiple cores to assess stratigraphic continuity.Journal Series No. R-04815 of the Florida Agricultural Experiment Station.     

Facility allocation strategies and the sustainability of service delivery: Modelling library patronage patterns and their related CO2-emissions

Service accessibility and urban transportation choices are crucial in cities' endeavours for securing social equality and environmental sustainability. They are particularly relevant when the public service network is to be rationalized. In this paper we provide a practical example of comparing the impacts of current varying service allocation strategies on travel behaviour and the resulting carbon dioxide (CO₂) emissions. We take libraries as a local public service to examine the CO₂ emissions resulting from residents' library trips in the capital region of Finland. Our analyses are based on data on library use (library loan database, N = 420,000), accessibility (comparable models of travel-time by car, public transportation and non-motorized transport) and customer transport choices (survey, n = 584). Our results show that (1) 52% of library customers use a library that is accessible from their home with minimum CO₂ emissions (the “climate-optimal” facility provider), (2) the remaining 48% that choose a non-optimal facility provider produce nearly 90% of the total CO₂-emissions related to library customer flows and (3) the service allocation strategies of the different municipalities lead to markedly different CO₂-emission patterns resulting from service usage. To conclude, sustainability measures (in our case the CO₂ burden) provide useful information on the impact of a service network structure which may be used alongside economic rationales.     

Statistical analysis of drainage density from digital terrain data

Drainage density (D_d), defined as the total length of channels per unit area, is a fundamental property of natural terrain that reflects local climate, relief, geology, and other factors. Accurate measurement of D_d is important for numerous geomorphic and hydrologic applications, yet it is a surprisingly difficult quantity to measure, particularly over large areas. Here, we develop a consistent and efficient method for generating maps of D_d using digital terrain data. The method relies on (i) measuring hillslope flow path distance at every unchanneled site within a basin, and (ii) analyzing this field as a random space function. As a consequence, we measure not only its mean (which is half the inverse of the traditional definition of drainage density) but also its variance, higher moments, and spatial correlation structure. This yields a theoretically sound tool for estimating spatial variability of drainage density. Averaging length-to-channel over an appropriate spatial scale also makes it possible to derive continuous maps of D_d and its spatial variations. We show that the autocorrelation length scale provides a natural and objective choice for spatial averaging. This mapping technique is applied to a region of highly variable D_d in the northern Apennines, Italy. We show that the method is capable of revealing large-scale patterns of variation in D_d that are correlated with lithology and relief. The method provides a new and more general way to quantitatively define and measure D_d, to test geomorphic models, and to incorporate D_d variations into regional-scale hydrologic models.     

Geographical accessibility and Kentucky's heart-related hospital services

Cardiovascular diseases (CVDs) are a leading cause of mortality in the US. Rates of mortality vary spatially and demographically, influenced not only by individual patient characteristics but also by levels of accessibility to hospital services and facilities. In 2000, Kentucky ranked third in the nation for heart-related deaths. The purpose of this paper is to assess geographical accessibility and service utilization related to ambulatory care sensitive CVDs in Kentucky. This study utilizes the Kentucky Hospital Discharge Database to evaluate service utilization and the Compressed Mortality File to examine mortality related to CVDs. A spatial statistical comparison of the geographical distribution of service usage and travel time to hospitals assists in assessing the relationship between accessibility and health. Our findings suggest that the distribution of utilization and mortality is geographically variable. People living in rural areas travel further to services; populations residing more than 45 min from health facilities are more likely to be socially and economically marginalized. Spatial clustering of high rates of hospital utilization occurs in areas with lower accessibility.     

Assessing linkages between ecosystem services,land-use and well-being in an agroforestry landscape using public participation GIS

While a number of studies have applied public participation GIS (PPGIS) approaches to the spatial assessment of ecosystem services, few have considered the associations between the spatial distribution of ecosystem services and the context-specific nature of self-reported well-being. In this study, we engage the general public to identify and map a range of ecosystem services that originate in place-based, local knowledge and explore the context-dependent nature of subjective well-being. We conducted a PPGIS survey with 219 local residents in a Spanish agroforestry (dehesa) landscapes and analysed the spatial patterns of mapped ecosystem services, their relation to land cover, protected area and common land patterns. In addition, we explored the landscape values contributing to people’s well-being; and the relationships between ecosystem services in different land covers, landscape values and socio-demographic characteristics. A mosaic of landscape types (i.e., the landscape) provided more ecosystem services (especially cultural and provisioning) to people compared with the individual land system of agroforestry. However, land tenure and public access significantly guided the spatial practices and values of the people beyond the preferred landscape types. The contribution of the landscape to well-being is largely related to values based on interactions among people and the landscape, as tranquillity/relaxation and people-people interactions such as being with family and friends. We discuss the specific contribution of agroforestry landscapes to the provision of ecosystem services and human well-being. We conclude that the integration of the applied methods of social-cultural assessment on the one hand links to ecosystem services frameworks but on the other hand represents a more holistic conceptualisation of people’s benefits from landscapes.