Dataset Information

GIS in Health and Human Services

ABSTRACT: The chapter begins with a general overview of how GIS has evolved in the health and human services over the last several decades providing readers with important definitions and descriptions (Sects. 29.1, 29.2). Sections 29.3, 29.4 uncovers how GIS became an important tool for epidemiologists in the work of tracking infectious diseases and perfecting the study of population health. Readers will also learn that GIS adoption by hospital marketers and planners in the United States accelerated rapidly after the 1970, when US Census data became relatively freely available in digital form. The importance of the legendary work of the Dartmouth Health Care Atlas Project and its founder Jack Wennberg. In areas where high GIS adoption rates occurred, such as in public health, we feature key applications such as immunization management, disease tracking, outbreak analysis, disease surveillance, syndromic surveillance, emergency preparedness and response, community health assessment, environmental health, chronic disease prevention, and animal and veterinary health. The final Sect. 29.5 describes how GIS education has expanded across the academic fields of public health, healthcare administration, and social services. It is pointed out that the material presented in this chapter is not intended to be an exhaustive examination of the history of GIS, but rather, a brief introduction and overview which will generate further interest and self-discovery.

SUBMITTER: Kresse W

PROVIDER: S-EPMC7121355 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Geospatial habitat suitability index (HSI) models have emerged as powerful tools that integrate pertinent spatial information to guide habitat restoration efforts, but have rarely accounted for spatial variation in ecosystem service provision. In this study, we utilized satellite-derived chlorophyll a concentrations for Pamlico Sound, North Carolina, USA in conjunction with data on water flow velocities and dissolved oxygen concentrations to identify potential restoration locations that would maximize the oyster reef-associated ecosystem service of water filtration. We integrated these novel factors associated with oyster water filtration ecosystem services within an existing, 'Metapopulation Persistence' focused GIS-based, HSI model containing biophysical (e.g., salinity, oyster larval connectivity) and logistical (e.g., distance to nearest restoration material stockpile site) factors to identify suitable locations for oyster restoration that maximize long-term persistence of restored oyster populations and water filtration ecosystem service provision. Furthermore, we compared the 'Water Filtration' optimized HSI with the HSI optimized for 'Metapopulation Persistence,' as well as a hybrid model that optimized for both water filtration and metapopulation persistence. Optimal restoration locations (i.e., locations corresponding to the top 1% of suitability scores) were identified that were consistent among the three HSI scenarios (i.e., "win-win" locations), as well as optimal locations unique to a given HSI scenario (i.e., "tradeoff" locations). The modeling framework utilized in this study can provide guidance to restoration practitioners to maximize the cost-efficiency and ecosystem services value of habitat restoration efforts. Furthermore, the functional relationships between oyster water filtration and chlorophyll a concentrations, water flow velocities, and dissolved oxygen applied in this study can guide field- and lab-testing of hypotheses related to optimal conditions for oyster reef restoration to maximize water quality enhancement benefits.

Project description:Injury is a leading cause of the global disease burden, accounting for 10 percent of all deaths worldwide. Despite 90 percent of these deaths occurring in low and middle-income countries (LMICs), the majority of trauma research and infrastructure development has taken place in high-income settings. Furthermore, although accessible services are of central importance to a mature trauma system, there remains a paucity of literature describing the spatial accessibility of emergency services in LMICs. Using data from the Service Provision Assessment component of the Demographic and Health Surveys of Namibia and Haiti we defined the capabilities of healthcare facilities in each country in terms of their preparedness to provide emergency services. A Geographic Information System-based network analysis method was used to define 5- 10- and 50-kilometer catchment areas for all facilities capable of providing 24-hour care, higher-level resuscitative services or tertiary care. The proportion of a country's population with access to each level of service was obtained by amalgamating the catchment areas with a population layer. A significant proportion of the population of both countries had poor spatial access to lower level services with 25% of the population of Haiti and 51% of the population of Namibia living further than 50 kilometers from a facility capable of providing 24-hour care. Spatial access to tertiary care was considerably lower with 51% of Haitians and 72% of Namibians having no access to these higher-level services within 50 kilometers. These results demonstrate a significant disparity in potential spatial access to emergency services in two LMICs compared to analogous estimates from high-income settings, and suggest that strengthening the capabilities of existing facilities may improve the equity of emergency services in these countries. Routine collection of georeferenced patient and facility data in LMICs will be important to understanding how spatial access to services influences outcomes.

Project description:One of the biggest environmental worries in the world today is the risk of arsenic (As) contamination in groundwater. The Atomic Absorption Spectrometer (AAS) was used in this work to assess the As content in groundwater samples from 38 shallow (27 m) tubewells in northwest Bangladesh to determine the existing situation, potential source(s), and likely health risk of As and other important water quality parameters. The range of arsenic concentrations (μgL-1) was troublesome and greater than the WHO recommended level for drinking water, ranging from 0.50 to 164 (mean ± SD: 20.22 ± 36.46). In groundwater, the concentrations of Fe, and Mn vary from 0.04 to 52.75 mgL-1 (mean ± SD: 4.23 ± 9.68), and 0.23 to 3.27 mgL-1 (mean ± SD: 1.10 ± 0.67). The obtained groundwater samples have pH values ranging from 5.9 to 7.1, which indicates a somewhat acidic to neutral character. Major cations have an average abundance that is as follows: Ca2+ > Mg2+ > Na+ > K+, while major anions have an average abundance that is as follows: HCO3- > Cl- > SO42- > NO3-; Ca2+ and HCO3- are the main cation and anion, respectively. The groundwater in the Rajarampur village was deemed unfit for drinking or irrigation based on analyses of water quality performed using the entropy water quality index. The Ca-HCO3 type of water, in which Ca2+ and HCO3- are the main positive ions and negative ions, is suggested by the Piper tri-linear diagram. It was discovered that silicate weathering regulates the hydro-geochemical activities in groundwater using a bi-variate examination of several hydro-chemical variables. Four major clusters were observed for the water sample. According to reductive dissolution processes and principal component analysis, the arsenic in groundwater is geogenic in origin. Arsenic is discharged from sediment to groundwater by reductive dissolution of FeOOH and MnOOH, as shown by the modest connection between As, Fe, and Mn. The United Nations Environmental Protection Agency's (USEPA) suggested value for probable cancer risk assessment was 10-6, however the probable cancer risk assessment found a higher value, indicating that the population in the study region was at high risk for cancer. Remedial measures for arsenic mitigation include removing arsenic from groundwater after it is extracted, searching for alternative aquifers, and implementing various water-supply technologies such as dugwells, deep tubewells, pond-sand filters, and rainwater harvesting systems.

Project description:Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the nine BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data - often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols.

Project description:IntroductionSupervision training aims to develop workplace supervisory competencies. Despite extensive supervision literature, including literature reviews, the processes through which supervision training interventions produce their effects, for whom and under what circumstances is not clearly delineated. The purpose of this study is to explain the effect of contextual factors on the underpinning mechanisms of supervision training outcomes.Methods and analysisWe propose to examine supervision training interventions across the health and human services workforce using realist methods. Pawson's five stages for undertaking a realist synthesis will be followed: (1) clarifying the scope of the review; (2) determining the search strategy; (3) study selection; (4) extracting data and (5) synthesising the evidence and drawing conclusions. Extracted data will include study characteristics, characteristics of participant cohort, intervention type, contextual factors, underlying mechanisms and supervision training outcomes. Patterns in context-mechanism-outcome configurations will be identified. Initial programme theories will be developed based on a comprehensive search of the literature, which will include key terms relating to supervision and training. The search strategy will involve: (1) electronic database searching using Medline, Cumulative Index to Nursing and Allied Health Literature, Social Services Abstracts, Educational Resources Information Center, PsycINFO and Australian Public Affairs Information Service and (2) hand and citation searching. We will also contact authors where necessary and discuss identified literature among the project team with extensive expertise in supervision training.Ethics and disseminationThe realist synthesis will propose an evidence-informed theory of supervision training interventions (ie, what interventions work for whom and why). The findings will be disseminated in peer-reviewed journals and presentations and through discussions with relevant organisations and stakeholders. The research will be used by educators to develop evidenced-based supervision training interventions. It will also help workplace supervisors to better understand what types of supervision training might work most optimally for them and their colleagues. Other researchers could use the synthesis findings to guide future supervision research.Prospero registration numberCRD42018094186.

Project description:Healthcare accessibility and site suitability analysis is an elongated and complex task that requires evaluation of different decision factors. The main objective of the present study was to develop a hybrid decision-making approach with geographic information systems to integrate spatial and non-spatial data to form a weighted result. This study involved three-tier analyses for assessing accessibility and selecting suitable sites for healthcare facilities, and analysing shortest-path network. The first tier of analysis stressed the spatial distance, density and proximity from existing healthcare to find more deprived and inaccessible areas in term of healthcare facilities. The result revealed that spatial discrepancy exists in the study area in term of access to healthcare facilities and for achieving equal healthcare access, it is essential to propose new plans. Thus, require finding suitable sites for put forward new healthcare service, which was highlighted in the second tier of analysis based on land use land cover, distancing to road and rail, proximity to residential areas, and weighted overlay of accessibility as decision factors. Finally, in the third tier of analysis, the most suitable site among the proposed healthcare was identified using the technique for order of preference by similarity to ideal solution. The road network analysis was also performed in this study to determine the shortest and fastest route from these healthcare facilities to connect with district medical hospital. The present study found some suitable sites throughout the district on inaccessible zones where people are deprived from better healthcare facilities. This attempt will highly helpful for preparing a spatial decision support system which assists the health authorities regarding the healthcare services in inaccessible, underprivileged, and rural areas. Electronic supplementary material The online version of this article (10.1007/s41324-020-00330-0) contains supplementary material, which is available to authorized users.

Dataset Information

GIS in Health and Human Services

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets