Browsing by Subject "Geographic Information Science"

Now showing 1 - 4 of 4
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    From Hometown to Practice: Mapping and Analyzing the Medical Student Pipeline at the Indiana University School of Medicine
    (2019-10) Fancher, Laurie Michelle; Wilson, Jeffrey; Kochhar, Komal; Lulla, Vijay
    Indiana University School of Medicine (IUSM) teaches approximately 350 medical students each year. These students come from varied backgrounds and eventually end up practicing in a vast array of clinical specialties and settings. It is extremely important to monitor specialties and practice locations to understand exactly how IUSM is fulfilling physician workforce needs. This knowledge can help policymakers and school administrators shape programs and policies to better fulfill physician workforce needs. Geographic information technologies provide a framework to organize, analyze and visualize medical student data. Maps are a convenient and easily understandable method of conveying information with a location-based component. This project represents a step towards creating a coherent student database visualized with maps. Using data about the graduating classes from 2011-2018, a database was created that linked together geographic information of students from the various segments of their medical education such as residency, fellowship, and practice location. ArcGIS 10.5 was used to produce maps visualizing segments of this database. These maps also served to answer questions about the medical student graduates at IUSM, such as how many came from an in-state location and how many practice in-state. SPSS 25 was also used to compare results of various segments of the medical education pipeline. The database proves to be an incredibly necessary tool for keeping track of all IUSM graduates. Coherent, clean, and complete data is necessary for researchers at all levels as well as administrators. Keeping data up to date and centralized is essential and this project provides an easily updateable and useable format. The maps created from this database are also useful in showing trends across the graduates of IUSM, such as the Indiana counties that the graduates are most likely to practice in or the likelihood of practicing in specific shortage areas.
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    Medical Imaging Centers in Central Indiana: Optimal Location Allocation Analyses
    (2016-01) Seger, Mandi J.; Banerjee, Aniruddha; Wilson, Jeffrey S.; Lulla, Vijay O.; Wiehe, Sarah Elizabeth
    While optimization techniques have been studied since 300 B.C. when Euclid first considered the minimal distance between a point and a line, it wasn’t until 1966 that location optimization was first applied to a problem in healthcare. Location optimization techniques are capable of increasing efficiency and equity in the placement of many types of services, including those within the healthcare industry, thus enhancing quality of life. Medical imaging is a healthcare service which helps to determine medical diagnoses in acute and preventive care settings. It provides physicians with information guiding treatment and returning a patient back to optimal health. In this study, a retrospective analysis of the locations of current medical imaging centers in central Indiana is performed, and alternate placement as determined using optimization techniques is considered and compared. This study focuses on reducing the drive time experienced by the population within the study area to their nearest imaging facility. Location optimization models such as the P-Median model, the Maximum Covering model, and Clustering and Partitioning are often used in the field of operations research to solve location problems, but are lesser known within the discipline of Geographic Information Science. This study was intended to demonstrate the capabilities of these powerful algorithms and to increase understanding of how they may be applied to problems within healthcare. While the P-Median model is effective at reducing the overall drive time for a given network set, individuals within the network may experience lengthy drive times. The results further indicate that while the Maximum Covering model is more equitable than the P-Median model, it produces large sets of assigned individuals overwhelming the capacity of one imaging center. Finally, the Clustering and Partitioning method is effective at limiting the number of individuals assigned to a given imaging center, but it does not provide information regarding average drive time for those individuals. In the end, it is determined that a capacitated Maximal Covering model would be the preferred method for solving this particular location problem.
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    Ryan White: A Geospatial Analysis of his Correspondence
    (2020-05) Shaeffer, Haley Lynn; Johnson, Daniel; Wilson, Jeffrey; Lulla, Vijay
    The letters Ryan White received over the course of his diagnosis, illness, and eventual death show a spatial distribution that reflected the United States’ response to Ryan’s condition. Ryan was diagnosed with AIDS in December of 1984 at the height of the epidemic, and the panic that surrounded it. In 2000, the Children’s Museum of Indianapolis accessioned a selection of letters sent to Ryan White and his mother, from 1980 to 1993. The expanded incorporation of these letters into the museum’s “Power of Children” gallery will introduce museum visitors to the public view on Ryan and the role he played in developing the public perception and awareness of AIDS in the 1980’s. Originally, it was anticipated that the distribution and number of letters Ryan received directly related to the concentration and spread of AIDS cases around the US. This research assumed that the AIDS community would have been more supportive and empathetic of Ryan’s diagnosis, resulting in those populations sending a higher number of letters. This assumption was also informed by the fact that the highest number of AIDS cases were in areas with large populations such as New York City, Los Angeles, and Miami. Yet findings showed relatively few letters were coming from the populated coasts where AIDS was more prevalent, and many more letters than expected came from areas with lower populations across the US. Ryan was one of the first children to go public with his AIDS diagnosis, which sparked strong reactions among people throughout the United States. Ryan’s correspondence and the outpouring of support he received allows insight into the multifaceted reaction to the AIDS crisis, especially from young people. Before Ryan became associated with the AIDS epidemic, this disease was seen primarily as an urban, gay, and drug-user related issue. The goal of this research is to gain further understanding of society’s shifting response to Ryan and AIDS during the 1980’s, by placing these letters in their social and geographic context.
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    Spatiotemporal analysis of extreme heat events in Indianapolis and Philadelphia for the years 2010 and 2011
    (2014-03-12) Beerval Ravichandra, Kavya Urs; Johnson, Daniel P. (Daniel Patrick), 1971-; Wilson, Jeffrey S. (Jeffrey Scott), 1967-; Bein, Frederick L. (Frederick Louis), 1943-
    Over the past two decades, northern parts of the United States have experienced extreme heat conditions. Some of the notable heat wave impacts have occurred in Chicago in 1995 with over 600 reported deaths and in Philadelphia in 1993 with over 180 reported deaths. The distribution of extreme heat events in Indianapolis has varied since the year 2000. The Urban Heat Island effect has caused the temperatures to rise unusually high during the summer months. Although the number of reported deaths in Indianapolis is smaller when compared to Chicago and Philadelphia, the heat wave in the year 2010 affected primarily the vulnerable population comprised of the elderly and the lower socio-economic groups. Studying the spatial distribution of high temperatures in the vulnerable areas helps determine not only the extent of the heat affected areas, but also to devise strategies and methods to plan, mitigate, and tackle extreme heat. In addition, examining spatial patterns of vulnerability can aid in development of a heat warning system to alert the populations at risk during extreme heat events. This study focuses on the qualitative and quantitative methods used to measure extreme heat events. Land surface temperatures obtained from the Landsat TM images provide useful means by which the spatial distribution of temperatures can be studied in relation to the temporal changes and socioeconomic vulnerability. The percentile method used, helps to determine the vulnerable areas and their extents. The maximum temperatures measured using LST conversion of the original digital number values of the Landsat TM images is reliable in terms of identifying the heat-affected regions.