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      A cancer geography paradox? Poorer cancer outcomes with longer travelling times to healthcare facilities despite prompter diagnosis and treatment: a data-linkage study

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          Abstract

          Background:

          Rurality and distance from cancer treatment centres have been shown to negatively impact cancer outcomes, but the mechanisms remain obscure.

          Methods:

          We analysed the impact of travel time to key healthcare facilities and mainland/island residency on the cancer diagnostic pathway (treatment within 62 days of referral, and within 31 days of diagnosis) and 1-year mortality using a data-linkage study with 12 339 patients.

          Results:

          After controlling for important confounders, mainland patients with more than 60 min of travelling time to their cancer treatment centre ((OR 1.42; 95% CI 1.25–1.61) and island dwellers (OR 1.32; 95% CI 1.09–1.59) were more likely to commence cancer treatment within 62 days of general practitioner (GP) referral and within 31 days of their cancer diagnosis compared with those living within 15 min. Island-dweller patients were more likely to have their diagnosis and treatment started on the same or next day (OR 1.72; 95% CI 1.31–2.25). Increased travelling time to a cancer treatment centre was associated with increased mortality to 1 year (30–59 min (HR 1.21; 95% CI 1.05–1.41), >60 min (HR 1.18; 95% CI 1.03–1.36), island dweller (HR 1.17; 95% CI 0.97–1.41).

          Conclusions:

          Island dwelling and greater mainland travel burden was associated with more rapid cancer diagnosis and treatment following GP referral even after adjustment for advanced disease; however, these patients also experienced a survival disadvantage compared with those living nearer. Cancer services may need to be better configured to suit the different needs of dispersed populations.

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          Most cited references36

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          Managing patients with multimorbidity in primary care.

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            Geographic access to health care for rural Medicare beneficiaries.

            Patients in rural areas may use less medical care than those living in urban areas. This could be due to differences in travel distance and time and a utilization of a different mix of generalists and specialists for their care. To compare the travel times, distances, and physician specialty mix of all Medicare patients living in Alaska, Idaho, North Carolina, South Carolina, and Washington. Retrospective design, using 1998 Medicare billing data. Travel time was determined by computing the road distance between 2 population centroids: the patient's and the provider's zone improvement plan codes. There were 2,220,841 patients and 39,780 providers in the cohort, including 6,405 (16.1%) generalists, 24,772 (62.3%) specialists, and 8,603 (21.6%) nonphysician providers. There were 20,693,828 patient visits during the study. The median overall 1-way travel distance and time was 7.7 miles (interquartile range 1.9-18.7 miles) and 11.7 minutes (interquartile range 3.0-25.7 minutes). The patients in rural areas needed to travel 2 to 3 times farther to see medical and surgical specialists than those living in urban areas. Rural residents with heart disease, cancer, depression, or needing complex cardiac procedures or cancer treatment traveled the farthest. Increasing rurality was also related to decreased visits to specialists and an increasing reliance on generalists. Residents of rural areas have increased travel distance and time compared to their urban counterparts. This is particularly true for rural residents with specific diagnoses or those undergoing specific procedures. Our results suggest that most rural residents do not rely on urban areas for much of their care.
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              Geographic access to cancer care in the U.S.

              Although access to cancer care is known to influence patient outcomes, to the authors' knowledge, little is known regarding geographic access to cancer care, and how it may vary by population characteristics. This study estimated travel time to specialized cancer care settings for the continental U.S. population and calculated per capita oncologist supply. The closest travel times were estimated using a network analysis of the road distance weighted by travel speeds from the population or geographic centroid of every ZIP area in the continental U.S. to that of the nearest cancer care setting under consideration: National Cancer Institute (NCI)-designated Cancer Centers, academic medical centers, and oncologists. Alaska and Hawaii were excluded because travel in these states is often not road-based. Population and geographic characteristics including race/ethnicity, income, education, and region were derived from U.S. Census 2000 data and from rural-urban commuting area classifications. Oncologist supply per 100,000 residents in Hospital Referral Regions (pHRRs) was estimated by region. Travel times of
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                Author and article information

                Journal
                Br J Cancer
                Br. J. Cancer
                British Journal of Cancer
                Nature Publishing Group
                0007-0920
                1532-1827
                25 July 2017
                22 June 2017
                : 117
                : 3
                : 439-449
                Affiliations
                [1 ]Institute of Applied Health Sciences, University of Aberdeen , Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK
                [2 ]School of Geosciences , Drummond Street, Edinburgh EH8 9XP, UK
                [3 ]Information Services Division, NHS National Services Scotland, Gyle Square , 1 South Gyle Crescent, Edinburgh EH12 9EB, UK
                Author notes
                Article
                bjc2017180
                10.1038/bjc.2017.180
                5537495
                28641316
                e47b5f68-27ff-454d-ad6f-8a0e8be04dca
                Copyright © 2017 Cancer Research UK

                From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/

                History
                : 25 January 2017
                : 28 April 2017
                : 26 May 2017
                Categories
                Epidemiology

                Oncology & Radiotherapy
                diagnosis,treatment,travel,mortality,healthcare facilities
                Oncology & Radiotherapy
                diagnosis, treatment, travel, mortality, healthcare facilities

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