PRAMNET: Pediatric Risk Assessment Mapping Net(work): Mapping the Health Gaps for Children with Complex Medical Needs, Children with Disabilities, and Infectious Pediatric Illnesses Open Access

Goughnour, Kenneth (Spring 2018)

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Background: Georgia’s pediatric mortality rate is one of the highest in the nation (Gentili, Harati, Serban, O'Connor, & Swann, 2017). There are also significant differences in pediatric health across Georgia when measured in terms of geography and race (CDC, 2015). While there is a good deal of available pediatric health data, much of this body of data is complicated by not only: a) a great deal of variation in granularity in its collections (some as fine as on a sub-census tract basis, some more grossly aggregated); and b) the presentation in traditional modes (e.g. tables), while sufficient, could be enhanced by the application of spatial analysis systems that allow for the visual presentation of geographic factors. This thesis argues that particularly within the field of pediatric health, Geographic Information System (GIS) software is an underutilized set of tools which can improve the development of public health outcomes and interventions.

Purpose: The aim of this thesis is to present a practitioner’s exploration of a conceptual model for aggregating and displaying different kinds of geographically-based data (geo-coded data, demographic, behavioral, biometric, etc.) with the proposed used of wearable devices to more demonstrate efficacious, data driven outcomes for pediatric populations in Georgia. Two unrelated digital technologies, when combined, show significant promise for enhancing the pediatric health field. GISs are being employed in the field of pediatric health care and health information systems in new and innovative ways, and wearable technologies including sensors and displays, are be used both to collect a wide variety of health related data, while providing feedback to the user.

Methods: A review of pertinent literature was used to identify key population demographic characteristics for pediatric health conditions (e.g. mother’s age, child’s diabetic status) in metro/urban Atlanta. A GIS software application, ArcGIS, was used to generate proof of concept maps that visually capture “hot spots” of negative pediatric outcomes.

Results: GIS mapping methodologies provide a powerful approach to visually reveal negative pediatric outcomes that might not be readily apparent in traditional tabular and textual presentations. As such, previously obscured population conditions can become visible. The resultant geo-coded longitudinal data can inform health practitioners and policy-makers of unique socioeconomic contexts, differential pediatric exposures, differential health outcomes and differential vulnerabilities. This, in turn, can improve access to appropriate and necessary pediatric care, particularly among pediatric urban/metropolitan populations.

Discussion: This thesis presents a conceptual model that explores the use of GIS spatial analysis using key pediatric health indicators as a way of testing the hypothesis that the visual enhancement and presentation of data can better serve public health professionals and policy makers.

Table of Contents

Table of Contents

Chapter 1. 7

1.1.0: Pediatric Health and Outcome Disparities in Georgia. 7

1.2.0: The Use of Geographical Information Systems and Spatial Analysis and Visualization in Public Health  11

1.3.0: Enhancing Data Collection and Monitoring by Using Mobile Technology (Wearables) in Pediatric Health  12

1.4.0: GIS Mapping of Suboptimal Pediatric Outcomes in Urban/Metro Atlanta. 13

1.5.0: Ensuring Patient Privacy with Geographical Information Systems. 14

1.6.0: Summary: Applications of GIS, and Spatial Data Visualization in Atlanta Pediatric Screening  15

Chapter 2: 17

2.1.0: Pediatric Health and Well-being in Georgia. 17

2.2.0: Geographical Information Systems (GIS) 17

2.3.0: Geographical Information Systems Analysis Platform (ArcGIS) 19

2.4.0: Review of Wearable Technology Literature. 20

2.5.0: Summary. 21

Chapter 3: 22

3.1.0: Methodology. 22

3.2.0: Variables and Project Approach. 22

Chapter 4: 25

4.1.0: Wearable/Geographical Information Systems Technology and Children with Complex Medical Needs and Children with Disabilities  25

4.2.0: Wearable/Geographic Information Systems Technology and Infectious Pediatric Illnesses. 27

4.3.0: Condition of Interest 1: Cystic Fibrosis. 28

4.4.0: Condition of Interest 2: Osteomyelitis. 30

4.5.0: Condition of Interest 3: Asthma. 33

4.6.0: Condition of Interest 4: HIV/AIDS. 36

4.7.0: Summary. 40

Chapter 5: 42

5.1.0: Example Use of Geographical Information Systems to Map Pediatric Conditions in Atlanta  43

5.2.0: Traditional/Tabular Presentations of Data Compared to GIS Visualizations of Data. 45

5.3.0: Results Summary:  Traditional Presentation of Pediatric Health Outcomes versus GIS-Based Data Mapping to Pediatric Health Outcomes  47

Chapter 6: 49

6.1.0: Electronic Health Records and Geographical Information Systems. 49

6.2.0: Integrating a Pediatric Health/GIS Framework with Existing Pediatric Surveillance Methods  49

6.3.0: Enhancing GIS Spatial Analytics for Pediatric Health. 50

6.4.0: Limitations. 51

6.5.0: Conclusion and Recommendations. 52

6.6.0: Definition of Terms and Abbreviations. 53

Chapter 7. 55

7.0.0: Bibliography. 55



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