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Grant Details

Grant Number: 1R21CA212687-01A1 Interpret this number
Primary Investigator: Onega, Tracy
Organization: Dartmouth College
Project Title: Automated Delineation of Cancer Service Areas
Fiscal Year: 2017


ABSTRACT For over 20 years, health care delivery in the U.S. has been informed by methodologies that create “service areas”, such as Hospital Service Areas (HSAs) of the Dartmouth Atlas Project, to evaluate how health care resources are distributed across the population and how that impacts health outcomes. Policy makers have used these units to assess regional variation in health care utilization and quality to design strategies for improving health and health care systems. Delivery of cancer care in the United States represents a unique set of patients, technologies, clinical specialization, and patient- centered perspectives, distinct from other patient populations. The Institute of Medicine and the American Society of Clinical Oncology have recently noted that there is a “crisis” in cancer care delivery, and highlighted the need for meaningful ways to assess quality. We propose to develop a novel method to generate Cancer Service Areas (CSAs) – geospatial units analogous to HSAs, but specific to cancer care – in order to create a framework for assessing regional cancer care delivery, quality, and outcomes. Based on health care utilization captured through all-payer claims and Medicare claims, we will extend and refine the Dartmouth HSA model. The derived CSAs have several key distinctions from existing service area delineations: a) focus on cancer-specific patient population/diagnoses; b) inclusion of outpatient claims, in addition to inpatient, to capture continuum of care; c) refinement of a complex network-based community detection method to account for spatial patterns of patient care while attaining geographic contiguity of the CSAs; and d) creation of an automated program in a Geographic Information Systems (GIS) environment that adapts to user-defined sets of services, diagnoses, or clinical phenotypes. Our specific aims are to: 1) Develop Cancer Service Areas (CSAs)- unique, cancer-specific geographic units of healthcare utilization to evaluate cancer care through a refined methodologic approach; 2) Evaluate the CSAs versus Dartmouth HSAs to assess their spatial specificity to the population of interest; and 3) Demonstrate the utility of CSAs as unique spatial units with respect to the cancer population. Creation of CSAs is an urgent need for policymakers (e.g. Congress), decision leaders (e.g. ASCO), health care systems, and ultimately patients who seek reliable, reportable information on quality cancer care. It is a first step towards these goals, and promises to serve broad service area methodologies at the same time.


The interaction of rurality and rare cancers for travel time to cancer care.
Authors: Onega T. , Alford-Teaster J. , Leggett C. , Loehrer A. , Weiss J.E. , Moen E.L. , Pollack C.C. , Wang F. .
Source: The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association, 2023 Mar; 39(2), p. 426-433.
EPub date: 2022-07-12.
PMID: 35821496
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Multiscale analysis of cancer service areas in the United States.
Authors: Wang C. , Onega T. , Wang F. .
Source: Spatial and spatio-temporal epidemiology, 2022 Nov; 43, p. 100545.
EPub date: 2022-10-28.
PMID: 36460451
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Delineation of Cancer Service Areas Anchored by Major Cancer Centers in the United States.
Authors: Wang C. , Wang F. , Onega T. .
Source: Cancer research communications, 2022 May; 2(5), p. 380-389.
EPub date: 2022-05-24.
PMID: 36875712
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GIS-Automated Delineation of Hospital Service Areas in Florida: From Dartmouth Method to Network Community Detection Methods.
Authors: Wang C. , Wang F. .
Source: Annals of GIS, 2022; 28(2), p. 93-109.
EPub date: 2022-02-01.
PMID: 35937312
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Spatial Behavior of Cancer Care Utilization in Distance Decay in the Northeast Region of the U.S.
Authors: Wang C. , Wang F. , Onega T. .
Source: Travel behaviour & society, 2021 Jul; 24, p. 291-302.
EPub date: 2021-05-15.
PMID: 34123728
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Network Optimization Approach to Delineating Health Care Service Areas: Spatially Constrained Louvain and Leiden Algorithms.
Authors: Wang C. , Wang F. , Onega T. .
Source: Transactions in GIS : TG, 2021 Apr; 25(2), p. 1065-1081.
EPub date: 2020-12-30.
PMID: 34456609
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From 2SFCA to i2SFCA: integration, derivation and validation.
Authors: Wang F. .
Source: International journal of geographical information science : IJGIS, 2021; 35(3), p. 628-638.
EPub date: 2020-08-28.
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Estimating a Large Travel Time Matrix Between Zip Codes in the United States: A Differential Sampling Approach.
Authors: Hu Y. , Wang C. , Li R. , Wang F. .
Source: Journal of transport geography, 2020 Jun; 86, .
EPub date: 2020-06-15.
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Automated delineation of cancer service areas in northeast region of the United States: A network optimization approach.
Authors: Wang F. , Wang C. , Hu Y. , Weiss J. , Alford-Teaster J. , Onega T. .
Source: Spatial and spatio-temporal epidemiology, 2020 Jun; 33, p. 100338.
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Differential effects of distance decay on hospital inpatient visits among subpopulations in Florida, USA.
Authors: Jia P. , Wang F. , Xierali I.M. .
Source: Environmental monitoring and assessment, 2019-06-28; 191(Suppl 2), p. 381.
EPub date: 2019-06-28.
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Evaluating Breast Cancer Care Coordination at a Rural National Cancer Institute Comprehensive Cancer Center Using Network Analysis and Geospatial Methods.
Authors: Moen E.L. , Kapadia N.S. , O'Malley A.J. , Onega T. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2019 Mar; 28(3), p. 455-461.
EPub date: 2018-10-30.
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Disparities in Geographic Accessibility of National Cancer Institute Cancer Centers in the United States.
Authors: Xu Y. , Fu C. , Onega T. , Shi X. , Wang F. .
Source: Journal of medical systems, 2017-11-11; 41(12), p. 203.
EPub date: 2017-11-11.
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