Special Issue "GIS in Healthcare"

Special Issue Editor

Prof. Dr. Fazlay S. Faruque
E-Mail Website
Guest Editor
Department of Preventive Medicine, University of Mississippi Medical Center, 2500 North State Street Jackson, MS 39216-4505, USA
Interests: geospatial health; environmental health; landscape epidemiology; population health geography; geospatial health disparities; geospatial analysis of eco-social determinants; application of Earth observation resources in health studies
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Special Issue Information

Dear Colleagues,

The entire healthcare sector, including health businesses, academia, and policy makers, is facing a challenge to become more efficient by reducing costs while reaching out to a broader range of communities. GIS is a proven tool for improving efficiency and planning in different areas of healthcare. From non-critical applications, such as primary care or preventive care, to critical situations, such as emergency care or organ replacement, GIS is increasingly being utilized to develop better business models and make lifesaving decisions. This Special Issue of IJGI is expected to serve as a knowledge exchange platform presenting the latest advancements in GIS applications in a dynamic healthcare landscape.

We invite authors to submit original scientific papers on the application of geospatial technologies in healthcare including, but not limited to, the following topics: 

  • Catchment area;
  • Distance decay;
  • Drive time pattern;
  • Healthcare business model;
  • Healthcare geomatics;
  • Healthcare disparities;
  • Healthcare needs assessment and planning;
  • Healthcare shortage areas;
  • Healthcare utilization;
  • Healthcare resource allocation;
  • Remote patient monitoring;
  • Social medicine;
  • Spatial surveillance;
  • Telehealth.

Prof. Fazlay S. Faruque
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • accessibility
  • geospatial health
  • GIS
  • healthcare
  • healthcare delivery
  • needs assessment
  • service area
  • spatial disparities
  • spatial modeling

Published Papers (8 papers)

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Research

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Open AccessArticle
LionVu 2.0 Usability Assessment for Pennsylvania, United States
ISPRS Int. J. Geo-Inf. 2020, 9(11), 619; https://doi.org/10.3390/ijgi9110619 - 23 Oct 2020
Viewed by 766
Abstract
The Penn State Cancer Initiative implemented LionVu 1.0 (Penn State University, United States) in 2017 as a web-based mapping tool to educate and inform public health professionals about the cancer burden in Pennsylvania and 28 counties in central Pennsylvania, locally known as the [...] Read more.
The Penn State Cancer Initiative implemented LionVu 1.0 (Penn State University, United States) in 2017 as a web-based mapping tool to educate and inform public health professionals about the cancer burden in Pennsylvania and 28 counties in central Pennsylvania, locally known as the catchment area. The purpose of its improvement, LionVu 2.0, was to assist investigators answer person–place–time questions related to cancer and its risk factors by examining several data variables simultaneously. The primary objective of this study was to conduct a usability assessment of a prototype of LionVu 2.0 which included area- and point-based data. The assessment was conducted through an online survey; 10 individuals, most of whom had a masters or doctorate degree, completed the survey. Although most participants had a favorable view of LionVu 2.0, many had little to no experience with web mapping. Therefore, it was not surprising to learn that participants wanted short 10–15-minute training videos to be available with future releases, and a simplified user-interface that removes advanced functionality. One unexpected finding was the suggestion of using LionVu 2.0 for teaching and grant proposals. The usability study of the prototype of LionVu 2.0 provided important feedback for its future development. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
Disparities in Geographical Access to Hospitals in Portugal
ISPRS Int. J. Geo-Inf. 2020, 9(10), 567; https://doi.org/10.3390/ijgi9100567 - 29 Sep 2020
Cited by 2 | Viewed by 1612
Abstract
Geographical accessibility to health care services is widely accepted as relevant to improve population health. However, measuring it is very complex, mainly when applied at administrative levels that go beyond the small-area level. This is the case in Portugal, where the municipality is [...] Read more.
Geographical accessibility to health care services is widely accepted as relevant to improve population health. However, measuring it is very complex, mainly when applied at administrative levels that go beyond the small-area level. This is the case in Portugal, where the municipality is the administrative level that is most appropriate for implementing policies to improve the access to those services. The aim of this paper is to assess whether inequalities in terms of access to a hospital in Portugal have improved over the last 20 years. A population-weighted driving time was applied using the census tract population, the roads network, the reference hospitals’ catchment area and the municipality boundaries. The results show that municipalities are 25 min away from the hospital—3 min less than in 1991—and that there is an association with premature mortality, elderly population and population density. However, disparities between municipalities are still huge. Municipalities with higher rates of older populations, isolated communities or those located closer to the border with Spain face harder challenges and require greater attention from local administration. Since municipalities now have responsibilities for health, it is important they implement interventions at the local level to tackle disparities impacting access to healthcare. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
Development of a Novel Framework to Propose New Strategies for Automated External Defibrillators Deployment Targeting Residential Out-Of-Hospital Cardiac Arrests: Application to the City of Milan
ISPRS Int. J. Geo-Inf. 2020, 9(8), 491; https://doi.org/10.3390/ijgi9080491 - 17 Aug 2020
Viewed by 870
Abstract
Public Access Defibrillation (PAD) is the leading strategy in reducing time to first defibrillation in cases of Out-Of-Hospital Cardiac Arrest (OHCA), but PAD programs are underperforming considering their potentiality. Our aim was to develop an analysis and optimization framework, exploiting georeferenced information processed [...] Read more.
Public Access Defibrillation (PAD) is the leading strategy in reducing time to first defibrillation in cases of Out-Of-Hospital Cardiac Arrest (OHCA), but PAD programs are underperforming considering their potentiality. Our aim was to develop an analysis and optimization framework, exploiting georeferenced information processed with Geographic Information Systems (GISs), specifically targeting residential OHCAs. The framework, based on an historical database of OHCAs, location of Automated External Defibrillators (AEDs), topographic and demographic information, proposes new strategies for AED deployment focusing on residential OHCAs, where performance assessment was evaluated using AEDs “catchment area” (area that can be reached within 6 min walk along streets). The proposed framework was applied to the city of Milan, Lombardy (Italy), considering the OHCA database of four years (2015–2018), including 8152 OHCA, of which 7179 (88.06%) occurred in residential locations. The proposed strategy for AEDs deployment resulted more effective compared to the existing distribution, with a significant improvement (from 41.77% to 73.33%) in OHCAs’ spatial coverage. Further improvements were simulated with different cost scenarios, resulting in more cost-efficient solutions. Results suggest that PAD programs, either in brand-new territories or in further improvements, could significantly benefit from a comprehensive planning, based on mathematical models for risk mapping and on geographical tools. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
Exploring Urban Spatial Features of COVID-19 Transmission in Wuhan Based on Social Media Data
ISPRS Int. J. Geo-Inf. 2020, 9(6), 402; https://doi.org/10.3390/ijgi9060402 - 19 Jun 2020
Cited by 10 | Viewed by 2562
Abstract
During the early stage of the COVID-19 outbreak in Wuhan, there was a short run of medical resources, and Sina Weibo, a social media platform in China, built a channel for novel coronavirus pneumonia patients to seek help. Based on the geo-tagging Sina [...] Read more.
During the early stage of the COVID-19 outbreak in Wuhan, there was a short run of medical resources, and Sina Weibo, a social media platform in China, built a channel for novel coronavirus pneumonia patients to seek help. Based on the geo-tagging Sina Weibo data from February 3rd to 12th, 2020, this paper analyzes the spatiotemporal distribution of COVID-19 cases in the main urban area of Wuhan and explores the urban spatial features of COVID-19 transmission in Wuhan. The results show that the elderly population accounts for more than half of the total number of Weibo help seekers, and a close correlation between them has also been found in terms of spatial distribution features, which confirms that the elderly population is the group of high-risk and high-prevalence in the COVID-19 outbreak, needing more attention of public health and epidemic prevention policies. On the other hand, the early transmission of COVID-19 in Wuhan could be divide into three phrases: Scattered infection, community spread, and full-scale outbreak. This paper can help to understand the spatial transmission of COVID-19 in Wuhan, so as to propose an effective public health preventive strategy for urban space optimization. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
Interdependent Healthcare Critical Infrastructure Analysis in a Spatiotemporal Environment: A Case Study
ISPRS Int. J. Geo-Inf. 2020, 9(6), 387; https://doi.org/10.3390/ijgi9060387 - 11 Jun 2020
Viewed by 773
Abstract
During an urban flooding scenario, Healthcare Critical Infrastructure (HCI) represents a critical and essential resource. As the flood levels rise and the existing HCI facilities struggle to keep up with the pace, the under-preparedness of most urban cities to address this challenge becomes [...] Read more.
During an urban flooding scenario, Healthcare Critical Infrastructure (HCI) represents a critical and essential resource. As the flood levels rise and the existing HCI facilities struggle to keep up with the pace, the under-preparedness of most urban cities to address this challenge becomes evident. Due to the disruptions in the interdependent Critical Infrastructures (CI) network (i.e., water supply, communications, electricity, transportation, etc.), during an urban flooding event, the operations at the healthcare CI facilities are inevitably affected. Hence, there is a need to identify cascading CI failure scenarios to visualize the propagation of failure of one CI facility to another CI, which can impact vast geographical areas. The goal of this work is to develop an interdependent HCI simulation model in a spatiotemporal environment to understand the dynamics in real-time and model the propagation of cascading CI failures in an interdependent HCI network. The model is developed based on a real-world cascading CI failure case study on an interdependent HCI network during the flood disaster event in December 2015 at Chennai, TamilNadu, India. The interdependencies between the CI networks are modeled by using the Stochastic Colored Petri Net (SCPN) based modeling approach. SCPN is used to model a real-word process that occurs in parallel or concurrently. Furthermore, a geographic information system-based interface is integrated with the simulation model, to visualize the dynamic behavior of the interdependent HCI SCPN simulation model in a spatiotemporal environment. Such a dynamic simulation model can assist the decision-makers and emergency responders to rapidly simulate ‘what if’ kind of scenarios and consequently respond rapidly. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
A Multi-factor Spatial Optimization Approach for Emergency Medical Facilities in Beijing
ISPRS Int. J. Geo-Inf. 2020, 9(6), 361; https://doi.org/10.3390/ijgi9060361 - 01 Jun 2020
Cited by 1 | Viewed by 779
Abstract
The outcomes for emergency medical services (EMS) are highly dependent on space-time accessibility. Prior research describes the location of EMS needs with low accuracy and has not integrated a temporal analysis of the road network, which accounts for varying mobility in a dynamic [...] Read more.
The outcomes for emergency medical services (EMS) are highly dependent on space-time accessibility. Prior research describes the location of EMS needs with low accuracy and has not integrated a temporal analysis of the road network, which accounts for varying mobility in a dynamic transportation network. In this study, we formulated a network-based location-allocation model (NLAM) and analyzed the spatial characteristics of emergency medical facilities within the fifth ring road in Beijing by considering time, traffic, and population characteristics. The conclusions are as follows: (1) The high demand area for EMS is concentrated in the areas in middle, north, and east during the daytime (8:00–20:00) and in the middle and north during the nighttime (20:00–8:00). From day to night, the centroid of the potential demand distribution shifts in the Western and Southern areas. (2) The road traffic data is sampled 20 times throughout the week, and variations in the average driving speed affect a higher mean driving speed on the weekend. This primarily impacts the main roads, due to these roads experiencing the greatest fluctuation in speed throughout the week of any roadway in the study area. (3) Finally, the 15-min coverage of emergency medical facilities are sampled 20 times in one week and analyzed. Fortunately, there is 100% coverage at night; however, due to traffic congestion, there were a few blind coverage areas in the daytime. The blind area is prevalent in Shijingshan South Station and the Jingxian Bridge in the South fifth ring. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Open AccessArticle
Using GIS for Disease Mapping and Clustering in Jeddah, Saudi Arabia
ISPRS Int. J. Geo-Inf. 2020, 9(5), 328; https://doi.org/10.3390/ijgi9050328 - 18 May 2020
Cited by 3 | Viewed by 1566
Abstract
Geographic information systems (GIS) can be used to map the geographical distribution of the prevalence of disease, trends in disease transmission, and to spatially model environmental aspects of disease occurrence. The aim of this study is to discuss a GIS application created to [...] Read more.
Geographic information systems (GIS) can be used to map the geographical distribution of the prevalence of disease, trends in disease transmission, and to spatially model environmental aspects of disease occurrence. The aim of this study is to discuss a GIS application created to produce mapping and cluster modeling of three diseases in Jeddah, Saudi Arabia: diabetes, asthma, and hypertension. Data about these diseases were obtained from health centers’ registered patient records. These data were spatially evaluated using several spatial–statistical analytical models, including kernel and hotspot models. These models were created to explore and display the disparate patterns of the selected diseases and to illustrate areas of high concentration, and may be invaluable in understanding local patterns of diseases and their geographical associations. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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Review

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Open AccessEditor’s ChoiceReview
Issues of Healthcare Planning and GIS: A Review
ISPRS Int. J. Geo-Inf. 2020, 9(6), 352; https://doi.org/10.3390/ijgi9060352 - 27 May 2020
Cited by 3 | Viewed by 1396
Abstract
Introduction: For the past 2400 years, the spatial relationship between health and location has been a concern for researchers. Studies have been conducted for decades to understand such a relationship, which has led to the identification of a number of healthcare planning issues. [...] Read more.
Introduction: For the past 2400 years, the spatial relationship between health and location has been a concern for researchers. Studies have been conducted for decades to understand such a relationship, which has led to the identification of a number of healthcare planning issues. Geographic Information Systems (GIS) technology has contributed to addressing such issues by applying analytical approaches at the level of epidemiological surveillance and evaluating the spatial inequality of access to healthcare. Consequently, the importance of reviewing healthcare planning issues and recognition of the role of GIS are integral to relevant studies. Such research will contribute to increasing the understanding of how to apply analytical approaches for dealing with healthcare planning issues using GIS. Methods: This paper aims to provide an examination of healthcare planning issues and focuses on reviewing the potential of GIS in dealing with such issues by applying analytical approaches. The method of a typical literature review was used through collecting data from various studies selected based on temporal and descriptive considerations. Results: Researchers have focused on developing and applying analytical approaches using GIS to support two important aspects of healthcare planning: first, epidemic surveillance and modeling, despite a lack of health information and its management, and, second, evaluating the spatial inequality of access to healthcare in order to determine the optimum distribution of health resources. Conclusion: GIS is an effective tool to support spatial decision-making in public health through applying the evolving analytical approaches to dealing with healthcare planning issues. This requires a literature review before preparing relevant studies, particularly because of the continuous development of GIS technologies. Full article
(This article belongs to the Special Issue GIS in Healthcare)
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