Advertisement

Travel Times for Screening Mammography

Impact of Geographic Expansion by a Large Academic Health System

      Rationale and Objectives

      This study aims to assess the impact of off-campus facility expansion by a large academic health system on patient travel times for screening mammography.

      Materials and Methods

      Screening mammograms performed from 2013 to 2015 and associated patient demographics were identified using the NYU Langone Medical Center Enterprise Data Warehouse. During this time, the system's number of mammography facilities increased from 6 to 19, reflecting expansion beyond Manhattan throughout the New York metropolitan region. Geocoding software was used to estimate driving times from patients' homes to imaging facilities.

      Results

      For 147,566 screening mammograms, the mean estimated patient travel time was 19.9 ± 15.2 minutes. With facility expansion, travel times declined significantly (P < 0.001) from 26.8 ± 18.9 to 18.5 ± 13.3 minutes (non-Manhattan residents: from 31.4 ± 20.3 to 18.7 ± 13.6). This decline occurred consistently across subgroups of patient age, race, ethnicity, payer status, and rurality, leading to decreased variation in travel times between such subgroups. However, travel times to pre-expansion facilities remained stable (initial: 26.8 ± 18.9 minutes, final: 26.7 ± 18.6 minutes). Among women undergoing mammography before and after expansion, travel times were shorter for the postexpansion mammogram in only 6.3%, but this rate varied significantly (all P < 0.05) by certain demographic factors (higher in younger and non-Hispanic patients) and was as high as 18.2%–18.9% of patients residing in regions with the most active expansion.

      Conclusions

      Health system mammography facility geographic expansion can improve average patient travel burden and reduce travel time variation among sociodemographic populations. Nonetheless, existing patients strongly tend to return to established facilities despite potentially shorter travel time locations, suggesting strong site loyalty. Variation in travel times likely relates to various factors other than facility proximity.

      Key Words

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Academic Radiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Humphrey L.L.
        • Helfand M.
        • Chan B.K.
        • et al.
        Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force.
        Ann Intern Med. 2002; 137: 347-360
        • DeSantis C.
        • Siegel R.
        • Bandi P.
        • et al.
        Breast cancer statistics, 2011.
        CA Cancer J Clin. 2011; 61: 409-418
        • Schueler K.M.
        • Chu P.W.
        • Smith-Bindman R.
        Factors associated with mammography utilization: a systematic quantitative review of the literature.
        J Womens Health (Larchmt). 2008; 17: 1477-1498
        • Alexandraki I.
        • Mooradian A.D.
        Barriers related to mammography use for breast cancer screening among minority women.
        J Natl Med Assoc. 2010; 102: 206-218
        • Jones A.R.
        • Caplan L.S.
        • Davis M.K.
        Racial/ethnic differences in the self-reported use of screening mammography.
        J Community Health. 2003; 28: 303-316
        • Breen N.
        • Wagener D.K.
        • Brown M.L.
        • et al.
        Progress in cancer screening over a decade: results of cancer screening from the 1987, 1992, and 1998 National Health Interview Surveys.
        J Natl Cancer Inst. 2001; 93: 1704-1713
        • McLafferty S.
        • Wang F.
        Rural reversal? Rural-urban disparities in late-stage cancer risk in Illinois.
        Cancer. 2009; 115: 2755-2764
        • Onega T.
        • Lee C.I.
        • Benkeser D.
        • et al.
        Travel burden to breast MRI and utilization: are risk and sociodemographics related?.
        J Am Coll Radiol. 2016; 13: 611-619
        • Onega T.
        • Hubbard R.
        • Hill D.
        • et al.
        Geographic access to breast imaging for US women.
        J Am Coll Radiol. 2014; 11: 874-882
        • Onega T.
        • Cook A.
        • Kirlin B.
        • et al.
        The influence of travel time on breast cancer characteristics, receipt of primary therapy, and surveillance mammography.
        Breast Cancer Res Treat. 2011; 129: 269-275
        • Henry K.A.
        • Boscoe F.P.
        • Johnson C.J.
        • et al.
        Breast cancer stage at diagnosis: is travel time important?.
        J Community Health. 2011; 36: 933-942
        • Celaya M.O.
        • Berke E.M.
        • Onega T.L.
        • et al.
        Breast cancer stage at diagnosis and geographic access to mammography screening (New Hampshire, 1998–2004).
        Rural Remote Health. 2010; 10: 1361
        • Alford-Teaster J.
        • Lange J.M.
        • Hubbard R.A.
        • et al.
        Is the closest facility the one actually used? An assessment of travel time estimation based on mammography facilities.
        Int J Health Geogr. 2016; 15: 8
        • Wang F.
        • Luo L.
        • McLafferty S.
        Healthcare access, socioeconomic factors and late-stage cancer diagnosis: an exploratory spatial analysis and public policy implication.
        Int J Public Pol. 2010; 5: 237-258
        • United States Census Bureau
        County classification lookup table.
        (Available at:) (Accessed December 11, 2016)
        • Fleishon H.B.
        • Itri J.N.
        • Boland G.W.
        • et al.
        Academic medical centers and community hospitals integration: trends and strategies.
        J Am Coll Radiol. 2017; 14: 45-51
        • Onitilo A.A.
        • Liang H.
        • Stankowski R.V.
        • et al.
        Geographical and seasonal barriers to mammography services and breast cancer stage at diagnosis.
        Rural Remote Health. 2014; 14: 2738
        • National Institutes of Health
        National Cancer Institute.
        (NCI-Designated Cancer Centers; Available at:) (Accessed December 21, 2016)
        • Ellenbogen P.H.
        Imaging 3.0: what is it?.
        J Am Coll Radiol. 2013; 10: 229
        • Onega T.
        • Duell E.J.
        • Shi X.
        • et al.
        Geographic access to cancer care in the U.S.
        Cancer. 2008; 112: 909-918
        • Berke E.M.
        • Shi X.
        Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods.
        Int J Health Geogr. 2009; 8: 23
        • Elkin E.B.
        • Ishill N.M.
        • Snow J.G.
        • et al.
        Geographic access and the use of screening mammography.
        Med Care. 2010; 48: 349-356
        • Peipins L.A.
        • Miller J.
        • Richards T.B.
        • et al.
        Characteristics of US counties with no mammography capacity.
        J Community Health. 2012; 37: 1239-1248
        • Kempe K.L.
        • Larson R.S.
        • Shetterley S.
        • et al.
        Breast cancer screening in an insured population: whom are we missing?.
        Perm J. 2013; 17: 38-44
        • Huang B.
        • Dignan M.
        • Han D.
        • et al.
        Does distance matter? Distance to mammography facilities and stage at diagnosis of breast cancer in Kentucky.
        J Rural Health. 2009; 25: 366-371
        • Lian M.
        • Struthers J.
        • Schootman M.
        Comparing GIS-based measures in access to mammography and their validity in predicting neighborhood risk of late-stage breast cancer.
        PLoS ONE. 2012; 7 (e43000)