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E-raamat: GIS Automated Delineation of Hospital Service Areas [Taylor & Francis e-raamat]

(Louisiana State University, Baton Rouge, USA),
  • Formaat: 224 pages, 17 Tables, black and white; 77 Line drawings, black and white; 28 Halftones, black and white; 105 Illustrations, black and white
  • Ilmumisaeg: 18-Oct-2021
  • Kirjastus: CRC Press
  • ISBN-13: 9780429260285
Teised raamatud teemal:
  • Taylor & Francis e-raamat
  • Hind: 147,72 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 211,02 €
  • Säästad 30%
GIS Automated Delineation of Hospital Service AreasSuurem pilt
  • Formaat: 224 pages, 17 Tables, black and white; 77 Line drawings, black and white; 28 Halftones, black and white; 105 Illustrations, black and white
  • Ilmumisaeg: 18-Oct-2021
  • Kirjastus: CRC Press
  • ISBN-13: 9780429260285
Teised raamatud teemal:
Taylor & Francis e-raamatudRohkem infot Taylor & Francis e-raamatute kohta
Raamatu kodulehekülg: https://www.taylorfrancis.com/books/9780429260285
"This book intends to mainly serve professionals in geography, urban and regional planning, public health, and related fields. It is also useful for scholars in the above fields who have research interests related to GIS and spatial analysis applicationsin health care. It can be used as a supplemental text for graduate students in a course related to GIS and Health"--

Hospital Service Areas are the foundation for healthcare evaluation. This book represents the state-of-the-art approach in delineating HSA using GIS automated processes. It provides the best practices and solutions for defining HSA in scientific and geographically accurate manners and in real-time.

Longer travel times to hospitals and other medical resources are associated with decreasing health outcomes and increasing mortality risk. Hospital Service Areas (HSAs) and Hospital Referral Regions (HRRs) are considered more appropriate units for analyzing the performance of healthcare markets and policy implementation; both serve as the foundation for healthcare evaluation. This book represents the state-of-the-art approach in delineating HSA by using GIS automated processes. It provides the best practices for defining such areas scientifically, in a geographically accurate manner, and in real-time. Geographers and GIS practitioners widely recognize the methods used.

This book intends to mainly serve professionals in geography, urban and regional planning, public health, and related fields. It is also useful for scholars in the above fields who have research interests related to GIS and spatial analysis applications in health care. It can be used as a supplemental text for graduate students in a course related to GIS and Health.



Hospital Service Areas are the foundation for healthcare evaluation. This book represents the state-of-the-art approach in delineating HSA using GIS automated processes. It provides the best practices and solutions for defining HSA in scientific and geographically accurate manners and in real-time.

Foreword ix
Preface xi
Authors xiii
List of Major GIS Datasets and Program Files
xv
1 Why Hospital Service Areas?
1(10)
1.1 Hospital Service Area (HSA) as a Functional Region
1(1)
1.2 Value of HSAs
2(2)
1.3 Study Area and Data
4(3)
1.4 Overview of Remaining
Chapters
7(4)
2 Estimating Distance and Travel Time Matrices in GIS
11(28)
2.1 Measures of Distance and Travel Time
11(2)
2.2 Computing Distance and Drive Time Matrices in ArcGIS Pro
13(6)
2.2.1 Computing Euclidean and Geodesic Distance Matrices in ArcGIS Pro
14(1)
2.2.2 Computing a Drive Time Matrix in ArcGIS Pro
15(4)
2.3 Estimating a Transit Travel Time Matrix in ArcGIS Pro
19(6)
2.4 Estimating Drive Time and Transit Time Matrices by Google Maps API
25(7)
2.5 Estimating a Large Drive Time Matrix by a Differential Sampling Approach
32(5)
2.5.1 Estimating Preliminary Inter-zonal Times
33(1)
2.5.2 Calibrating Inter-zonal Times on Randomly Sampled OD Pairs by Google Maps API
34(1)
2.5.3 Appending Intra-zonal Times
35(2)
2.6 Summary
37(2)
3 Analysis of Spatial Behavior of Health Care Utilization in Distance Decay
39(22)
3.1 Distance Decay Functions
40(1)
3.2 Value of Analyzing Distance Decay Effects in Health Care Studies
41(3)
3.3 Deriving the Distance Decay Functions by the Spatial Interaction Model
44(9)
3.3.1 Estimating the Spatial Interaction Model
44(3)
3.3.2 Distance Decay Effects across Geographic Areas in Florida
47(6)
3.4 Deriving the Distance Decay Functions by a Complementary Cumulative Distribution Curve
53(6)
3.4.1 Estimating the Complementary Cumulative Distribution Function
53(1)
3.4.2 Distance Decay Effects Across Population Groups in Florida
54(5)
3.5 Summary
59(2)
4 Delineating Hospital Service Areas by the Dartmouth Method
61(32)
4.1 History and Applications of Dartmouth HSAs and HRRs
61(2)
4.2 The Dartmouth Method for Defining HSAs and HRRs
63(6)
4.2.1 Defining HSAs by the Refined Dartmouth Method
63(4)
4.2.2 Defining HRRs by the Refined Dartmouth Method
67(2)
4.3 Automating the Refined Dartmouth Method for HSA & HRR Delineations
69(8)
4.4 Delineating HSAs and HRRs in Florida by the Refined Dartmouth Method
77(13)
4.4.1 Delineating HSAs and HRRs in Florida by the Automated Toolkit
77(5)
4.4.2 Calculating Indices for 1993 Dartmouth HSAs and HRRs in Florida by the Toolkit
82(3)
4.4.3 Evaluating HSAs and HRRs by the Refined Dartmouth Method
85(5)
4.5 Summary
90(3)
5 Delineating Hospital Service Areas by the Huff Model
93(28)
5.1 The Proximal Area Method and Its Implementation in GIS
94(7)
5.1.1 Defining Proximal Areas in Euclidean Distance in GIS
94(3)
5.1.2 Defining Proximal Areas in Travel Time in GIS
97(4)
5.2 The Huff Model and Extensions
101(3)
5.2.1 From Reilly's Law to the Huff Model
101(2)
5.2.2 Extensions to the Huff Model
103(1)
5.3 Implementing the Huff Model for Delineating HSAs in ArcGIS Pro
104(7)
5.4 Automated Delineation of HSAs by Integrating the Huff Model and Dartmouth Method
111(8)
5.5 Summary
119(2)
6 Delineating Hospital Service Areas by Network Community Detection Methods
121(32)
6.1 Community Detection Methods: From Louvain to Leiden
122(3)
6.2 Spatially Constrained Louvain and Leiden Methods
125(4)
6.3 Automated Delineation of HSAs and HRRs and a Case Study in Florida
129(10)
6.3.1 Automating the ScLouvain and ScLeiden Methods in ArcGIS Pro
129(2)
6.3.2 Delineating HSAs and HRRs in Florida by the ScLouvain and ScLeiden Methods
131(5)
6.3.3 Computational Performances of the ScLouvain and ScLeiden Methods
136(3)
6.4 Comparing HSAs and HRRs by ScLouvain, ScLeiden, and Refined Dartmouth Methods
139(11)
6.5 Summary
150(3)
7 Delineating Cancer Service Areas in the Northeast Region of the USA
153(20)
7.1 Study Area and Cancer Care Data
154(1)
7.2 Interpolating Suppressed Service Volumes
155(3)
7.3 Delineating CSAs by ScLouvain and ScLeiden in the Northeast Region
158(5)
7.4 Variation of Distance Decay Behavior across CSAs in the Northeast Region
163(7)
7.5 Summary
170(3)
Appendix A User Guide: Estimating a Large OD Drive Time Matrix 173(14)
Appendix B User Guide: How to Create Curved-Line and Straight-Line Network Flow Maps 187(10)
References 197(6)
Index 203
Fahui Wang, PhD, (ORCID #0000-0001-7765-3024) is Cyril & Tutta Vetter Alumni Professor in the Department of Geography and Anthropology, Louisiana State University. He earned a BS degree in geography from Peking University, China, an MA degree in economics and a PhD degree in city and regional planning from The Ohio State University. His research interests cover human geography (urban, economic, and transportation), public policy (crime and health) and planning. He has published 4 books, 2 edited volumes, and over 140 refereed articles (including co-authorship

Changzhen Wang (ORCID #0000-0002-3065-1168) is PhD Candidate of Geography in the Department of Geography and Anthropology, Louisiana State University. She earned a BS degree from Southwest Jiaotong University and MEng degree from Wuhan University, both in GIS, in China. Her research focuses on development and applications of GIS, computational methods, network analysis and geo-visualization in public health, urban studies, and transportation.
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