PLoS ONE plos plosone PLOS ONE 1932-6203 Public Library of Science San Francisco, CA USA 10.1371/journal.pone.0281071 PONE-D-22-22633 Research Article Medicine and health sciencesOncology Medicine and health sciencesOncologyCancers and neoplasms Medicine and health sciencesOncologyCancers and neoplasmsLung and intrathoracic tumors Medicine and health sciencesWomen's healthObstetrics and gynecologyGynecologic cancers Medicine and health sciencesOncologyCancers and neoplasmsBreast tumorsBreast cancer Medicine and health sciencesHealth carePatientsInpatients Medicine and health sciencesOncologyCancer treatment Medicine and health sciencesHealth carePatient advocacy Pre-pandemic geographic access to hospital-based telehealth for cancer care in the United States Geographic access to hospital-based telehealth for cancer care https://orcid.org/0000-0002-5189-4687 Shalowitz David I. Conceptualization Data curation Investigation Methodology Project administration Resources Supervision Writing – original draft Writing – review & editing 1 2 * https://orcid.org/0000-0002-1529-0819 Hung Peiyin Data curation Investigation Writing – original draft Writing – review & editing 3 Zahnd Whitney E. Conceptualization Data curation Formal analysis Investigation Visualization Writing – original draft Writing – review & editing 4 Eberth Jan Conceptualization Investigation Project administration Supervision Writing – review & editing 3 5 Department of Obstetrics and Gynecology, Section on Gynecologic Oncology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America Department of Implementation Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America Rural & Minority Health Research Center, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America Department of Health Management and Policy, University of Iowa College of Public Health, Iowa City, Iowa, United States of America Department of Health Management and Policy, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, United States of America Bhaskar Sonu Editor Global Health Neurology Lab / NSW Brain Clot Bank, NSW Health Pathology / Liverpool Hospital and South West Sydney Local Health District / Neurovascular Imaging Lab, Clinical Sciences Stream, Ingham Institute, AUSTRALIA

Funding and sources of competing interests do not alter our adherence to all PLOS ONE policies on sharing data and materials.

 * E-mail: david.shalowitz@gmail.com 31 1 2023 2023 18 1 e0281071 12 8 2022 14 1 2023 2023 Shalowitz et al This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Importance

Little is known about US hospitals’ capacity to ensure equitable provision of cancer care through telehealth.

 Objective

To conduct a national analysis of hospitals’ provision of telehealth and oncologic services prior to the SARS-CoV-2 pandemic, along with geographic and sociodemographic correlates of access.

 Design, setting, and participants

Retrospective cross-sectional analysis with Geographic Information Systems mapping of 1) 2019 American Hospital Association (AHA) Annual Hospital Survey and IT Supplement, 2) 2013 Urban Influence Codes (UIC) from the United States Department of Agriculture, 3) 2018 Area Health Resources Files from the Health Services and Resources Administration (HRSA).

 Interventions

Hospitals were categorized by telehealth and oncology services availability. Counties were classified as low-, moderate-, or high-access based on availability of hospital-based oncology and telehealth within their boundaries.

 Main outcomes and measures

Geospatial mapping of access to hospital-based telehealth for cancer care. Generalized logistic mixed effects models identified associations between sociodemographic factors and county- and hospital-level access to telehealth and oncology care.

 Results

2,054 out of 4,540 hospitals (45.2%) reported both telehealth and oncology services. 272 hospitals (6.0%) offered oncology without telehealth, 1,369 (30.2%) offered telehealth without oncology, and 845 (18.6%) hospitals offered neither. 1,288 out of 3,152 counties with 26.6 million residents across 41 states had no hospital-based access to either oncology or telehealth. After adjustment, rural hospitals were less likely than urban hospitals to offer telehealth alongside existing oncology care (OR 0.27; 95% CI 0.14–0.55; p < .001). No county-level factors were significantly associated with telehealth availability among hospitals with oncology.

 Conclusions and relevance

Hospital-based cancer care and telehealth are widely available across the US; however, 8.4% of patients are at risk for geographic barriers to cancer care. Advocacy for adoption of telehealth is critical to ensuring equitable access to high-quality cancer care, ultimately reducing place-based outcomes disparities. Detailed, prospective, data collection on telehealth utilization for cancer care is also needed to ensure improvement in geographic access inequities.

 national cancer institute P30CA012197 Shalowitz David Dr. Shalowitz received funding via the Wake Forest Comprehensive Cancer Center NCI cancer support grant (P30CA012197), and has received consulting fees from Nimble Co, LLC (purview.net) unrelated to the current work. the funders of this work had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data Availability The data underlying the results presented in the study are available from the American Hospital Association (https://www.ahadata.com/), the US Department of Agriculture (https://www.usda.gov/), the US Census https://www.census.gov/programs-surveys/geography/data/interactive-maps.html), and the Health Resources and Services Administration (https://data.hrsa.gov/). The authors did not have any special access privileges that others would not have. Datasets are accessible by following instructions on the above URLs. Introduction

Cancer patients in rural areas of the United States experience worse outcomes across all phases of cancer care in comparison to non-rural populations, in part due to geographic barriers to accessing high-quality oncologic care. For example, geographic barriers to care have been associated with decreased likelihood of high-quality treatment for patients with breast [1], colon [2], rectal [3], esophagogastric [4], gynecologic [5], and lung cancers [6]. One challenge in the pursuit of equity in cancer care for rural patients is ensuring appropriate geographic distribution of access points to high-quality cancer care. Prior nationwide analyses have suggested a mismatch between the distribution of oncology care professionals and the patient populations in need of care [7–9]. This mismatch is further exacerbated by contemporary trends toward the consolidation of the most complex cancer care in high-volume centers, in part owing to the improvement in outcomes accompanying treatment in high-volume settings [10]. Rural cancer patients may therefore face substantial travel burdens to reach facilities capable of providing high-quality cancer care.

Telehealth is critical to reducing cancer care disparities across the rural-urban continuum [11]. Telehealth offers referral centers the ability to provide outreach into rural and otherwise underserved areas whose residents may have difficulty traveling for care. For community cancer practices, telehealth likewise offers the potential for expanded geographic outreach, but also allows oncologists to connect with other cancer specialists to extend to patients some of the benefits of subspecialty cancer care while undergoing treatment locally [12].

Little is currently known about the capacity of hospitals within the United States to utilize telehealth as a component of cancer care. Moreover, few data exist on the availability of hospital-based telehealth services prior to their rapid adoption during the SARS-CoV-2 pandemic beginning in 2020. We therefore conducted a national analysis of hospitals’ pre-pandemic provision of telehealth and oncology services, along with geographic and sociodemographic correlates of access, and identify opportunities to improve utilization of this critical element of high-quality cancer care.

 Materials and methods Data sources

This study employed data from three sources: 1) 2019 American Hospital Association (AHA) Annual Hospital Survey and IT Supplement, 2) 2018 Area Health Resources Files from the Health Resources and Services Administration (HRSA), and 3) 2013 Urban Influence Codes (UIC) from the United States Department of Agriculture. The AHA survey is an annual survey administered to hospitals and collects information on hospital characteristics, including telehealth adoption, oncology services, hospital ownership, number of staffed beds, system affiliation, accreditation status by Joint Commission or DVN, teaching status, Commission on Cancer accreditation status, and payer mix for Medicare and Medicaid, as well as hospital geographic coordinates. The response rate on the 2019 AHA survey was 75.1%. Data from hospitals that did not respond to telehealth questions were imputed using both 2019 AHA IT Supplement and the historical data from 2015–2018.

Additionally, county-level characteristics including Primary Care Health Professional Shortage Area (HPSA), percent of in-county residents by age group (0–17, 18–39, 40–64, and 65 or older), by gender (female vs. male), by race/ethnicity (non-Hispanic White, non-Hispanic Black/African American, American Indian and Alaska Natives, Asian, Hispanic, Other Races), by poverty level status (100% federal poverty level), by insurance coverage status, by English proficiency, dissimilarity index between non-White and White residents in a county, and percent of households having broadband access were obtained from the 2018 Area Health Resources Files from HRSA [13]. The final analytic data set included 4,540 hospitals located in 3,152 counties across 50 states and Washington, D.C. To establish rurality categories, hospital counties were placed into three categories based upon UICs, a United States Department of Agriculture measure that categorizes counties based upon their population size and adjacency to metropolitan areas: urban (UIC class 1 or 2), rural micropolitan (UIC class 3, 5, or 8), and rural noncore (all other UIC classes).

 Measurement

This cross-sectional study has two primary outcomes: availability of hospital-level telehealth, and availability of hospital-level oncology services. First, we derived hospital-level telehealth availability from the AHA survey, based on each hospital’s responses on whether a hospital owned or provided telehealth services for consultation and office visits in its hospital settings. Second, we identified availability of hospital-level oncology servicesaccording to survey responses on whether a hospital provided on-site “inpatient and outpatient services for patients with cancer, including comprehensive care, support and guidance in addition to patient education and prevention, chemotherapy, counseling and other treatment methods.” Using these two dichotomous measures, we categorized hospitals into four groups (per their self-reported telehealth and oncology services provision): 1) neither telehealth nor oncology services, 2) telehealth but no oncology services, 3) oncology services but no telehealth, and 4) both telehealth and oncology services.

In order to identify geographic regions of the United States most amenable to intervention by county-level accessibility to oncology and telehealth services, we subsequently aggregated hospital-level oncology and telehealth services and categorized counties into three groups: 1) no telehealth or oncology (low access): no hospitals within the county, or hospitals within the county with neither telehealth nor oncology services provided, 2) telehealth or oncology only (moderate access): having hospitals that had either telehealth only or oncology only, 3) both telehealth and oncology (high access): having hospitals that have both telehealth and oncology services.

 Statistical analyses

First, we plotted hospital spatial coordinates and used the “spatial join” tool in ArcGIS Pro to determine the highest level of services available within a hospital in a county. We developed a descriptive map showing the highest level of available services within a hospital in each county with point locations of each hospital. Next, we identified sociodemographic correlates of the populations of counties with low-, moderate-, or high levels of access to telehealth for cancer care. Pearson’s Chi-square tests and two-group t tests were employed as appropriate to calculate the differences in county characteristics between high-access groups and each of the two less-access groups: moderate-access and low-access groups. We used population estimates from the 2019 U.S. Census Bureau American Community Survey to sum the population across counties by their access to telehealth and oncology services within hospitals.

To identify differences in hospital characteristics by oncology and telehealth services provision, we also analyzed hospital characteristics associated with the reported ability to provide oncology services, telehealth services, both services, or neither service, irrespective of geographic location. Pearson’s Chi-square tests were used to compare hospital characteristics across these four groups.

To further examine the role of hospital characteristics in oncology and telehealth services provisions, we constructed two separate generalized logistic mixed effects models treating county-level variables as random effects and hospital-level variables as fixed effects with a random intercept for each county. One model was conditional on a hospital with oncology services to examine the incremental likelihood of having telehealth when a hospital had oncology; the other model was conditional on a hospital with telehealth to examine the likelihood of oncology when a hospital had telehealth. The final hospital-level characteristics include hospital beds (<100, 100–299, 300 or more beds), hospital ownership (public federal, public non-federal, private non-profit, private for-profit hospitals), system affiliation (yes, no), accreditation by Joint Commission or DVN (yes, no), teaching hospitals (yes, no), and the ratios of Medicare and Medicaid inpatient days to total inpatient days, whether rural health clinics co-located at a hospital, and Accountable Care Organization (ACO) status (currently leading an ACO, currently participating in an ACO, previously led or participated in an ACO, or never led or participated in an ACO). In addition to these hospital factors, we also controlled for the indicator of Commission on Cancer accreditation (yes, no) when examining the likelihood of having telehealth among hospitals with oncology.

The final county-level models included hospital location (urban, rural micropolitan, rural noncore areas), Primary Care HPSA status (none, part of the hospital county, whole county), percentages of in-county residents that were 65 years old or older, females, and by race/ethnicity (non-Hispanic white, non-Hispanic Black, American Indian and Alaska Natives, Asian, Hispanic, and other non-Hispanic races), non-White versus White residential segregation (dissimilarity index), percentages of residents not proficient in English, percentages of households with broadband access, and percentages of residents without health insurance, as well as state indicators. All analysis were produced using SAS, version 9.4, Strata, version 13.1, and Microsoft Excel, version 16.43. Institutional Review Board approval was not required for this study as it does not qualify as human subjects research.

 Results and discussion Hospital-level variations in telehealth and oncology services provision

Of the 4,540 hospitals analyzed as part of the AHA database, 2,054 (45.2%) reported offering both telehealth and oncology services. 272 hospitals (6.0%) offered oncology without available telehealth, 1,369 (30.2%) offered telehealth without oncology services, and 845 (18.6%) hospitals offered neither service. 2,054 (88.3%) of hospitals providing cancer care also provided care by telehealth, whereas 272 hospitals offered cancer care but no telehealth. Hospitals offering both telehealth and oncology services were substantially more likely than hospitals without either of these services to be private, non-profit institutions (75.3% vs. 36.5%, respectively; p<0.001), to have capacity ≥300 beds (32.4% vs 3.3%, respectively; p<0.001), to be affiliated with a hospital system (77.6% vs 47.9%, respectively; p<0.001), and to identify as a teaching hospital (11.9% vs 0.6%, respectively; p<0.001). Hospitals without either oncology or telehealth services were more likely than hospitals with both services to be in counties designated in their entirety as HPSAs (25.4% vs 3.2%, respectively; p<0.001), and to derive the lowest proportion of inpatient reimbursement from Medicaid (40.0% vs 17.5%, respectively; p<0.001: Table 1).

10.1371/journal.pone.0281071.t001 Hospital characteristics by telehealth and oncology services provision status, 2019.
All Hospitals Telehealth and Oncology Services Provision P values for the differences
Neither Oncology Nor Telehealth Telehealth but no Oncology Oncology but no Telehealth Both Oncology and Telehealth
Number of Hospitals  
All 4,540 845 1,369 272 2,054  
Hospital Location N Column Percent < .001
    Urban 2,684 44.5 39.7 70.6 76.5  
    Rural Micropolitan 754 15.3 21.0 16.2 14.3  
    Rural Noncore 1,102 40.2 39.2 13.2 9.2  
Hospital Ownership           < .001
    Public non-federal 952 31.8 26.7 19.9 12.8  
    Private non-profit 2,745 36.5 53.5 58.1 75.3  
    Private for-profit 651 21.9 16.2 16.2 9.7  
    Public federal 192 9.8 3.5 5.9 2.2  
Hospital beds           < .001
    <100 2,306 76.1 77.7 32.0 24.9  
    100–299 1,442 20.6 19.3 47.1 42.7  
    300+ 792 3.3 3.0 21.0 32.4  
System Affiliation           < .001
    Yes 3,069 47.9 64.7 68.0 77.6  
    No 1,471 52.1 35.3 32.0 22.4  
Accreditation by Joint Commission or DVN           < .001
    Yes 3,331 54.6 57.6 87.1 89.8  
    No 1,209 45.4 42.4 12.9 10.2  
Teaching Hospital           < .001
    Yes 270 0.6 0.5 4.8 11.9  
    No 4,270 99.4 99.5 95.2 88.1  
Commission on Cancer Accredited           < .001
    Yes 1,270 - - 51.5 55.0  
    No 3,270 100.0 100.0 48.5 45.0  
Ratio of Medicare Inpatient Days to Total Inpatient Days           < .001
    <45% 1,190 27.6 26.0 23.9 26.1  
    45%-55% 1,379 34.6 24.3 43.4 31.0  
    >55% 1,971 37.9 49.7 32.7 42.9  
Ratio of Medicaid Inpatient Days to Total Inpatient Days           < .001
    Tertile I: <10% 1,273 40.0 38.0 20.2 17.5  
    Tertile II: 10–20% 1,438 25.9 28.4 23.2 37.3  
    Tertile III: >20% 1,829 34.1 33.6 56.6 45.1  
Health Professional Shortage Area—Primary Care, 2020     < .001
    None 367 6.5 6.9 8.8 9.4  
    Part county 3,610 68.1 73.0 88.6 87.4  
    Whole county 563 25.4 20.2 2.6 3.2  
Rural Health Clinics Co-located at Hospital           < .001
    Yes 1,009 16.1 32.8 15.1 18.7  
    No 2,380 18.0 40.3 53.3 74.6  
    Missing 1,150 65.9 27.0 31.6 6.8  
Accountable Care Organization (ACO)           < .001
    Hospital/system current leads an ACO 972 1.8 14.2 11.8 35.6  
    Hospital/system currently participates in an ACO (but not its leader) 747 4.5 17.5 16.5 20.7  
    Hospital/system previously led or participated in an ACO 123 1.0 2.3 1.8 3.9  
    Hospital/system has never participated or led an ACO 2,697 92.8 66.1 69.9 39.9  

Notes: Pearson’s Chi-square tests were employed to calculate the differences in hospital characteristics by oncology and telehealth services provision.

 County-level variations in hospital-based telehealth and oncology services availability

Of 3,152 United States counties, 1,288 had no hospital-based access to either oncology or telehealth services. These low-access counties, with an approximate population of 26.6 million Americans (8.1% nationally), either had no hospital, or hospitals within their borders had neither service. Low-access counties were present in all but 8 states, mostly located in the Northeast (ME, NH, MA, CT, RI, NJ, DE, HI). 754 moderate-access counties, with an approximate population of 27.4 million (8.4% nationally), had access to either telehealth or oncology, but not both. 1,110 high-access counties, with an approximate population of 274.4 million (83.5% nationally), had at least one hospital with both oncology and telehealth services (Fig 1). High-access counties were more likely to be classified as urban than moderate- and low-access counties (59.3% vs. 22.9% and 26.1%, respectively; p<0.001). Low-access counties were substantially more likely to be designated in their entirety as a HPSA than high-access counties (46.3% vs 5.8%, respectively, p<0.001). Likewise, the mean population per primary care physician in low-access counties was 3,447 (SD 2,996), compared to 2,714 (SD 1,940) in moderate-access and 1,706 (SD 1,175) in high-access counties, p<0.001. The distribution of race and ethnicity across high, moderate, and low access counties was notable for a proportionately higher American Indian/Alaska Native population in low access counties compared to moderate- and high-risk counties (10.6% vs 6.0% vs 3.8%, respectively; p<0.001, Table 2).

10.1371/journal.pone.0281071.g001 </caption> <graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0281071.g001" xlink:type="simple"/> </fig> <table-wrap id="pone.0281071.t002" position="float"> <object-id pub-id-type="doi">10.1371/journal.pone.0281071.t002</object-id> <label>Table 2</label> <caption><title>County characteristics by telehealth and oncology services provision status, 2019.
No Oncology or Telehealth(N = 1,288) Compared to Counties with Both Telehealth or Oncology Only(n = 754) Compared to Counties with Both Both Oncology and Telehealth(n = 1,110)
N Col % P N Col % P N Col %
County Rurality†     < .001     < .001    
Urban (n = 1,167) 336 26.1% 173 22.9% 658 59.3%
Rural Micropolitan (n = 650) 188 14.6% 190 25.2% 272 24.5%
Rural Noncore (n = 1,335) 764 59.3%   391 51.9%   180 16.2%
Health Professional Shortage Area—Primary Care, 2020     < .001     < .001    
None (n = 334) 129 10.0% 68 9.0% 137 12.3%
Part county (n = 1,946) 563 43.7% 474 62.9% 909 81.9%
Whole county (n = 872) 596 46.3%   212 28.1% 64 5.8%
Mean Std Mean Std Mean Std
% in-County Residents by Age, 2018                
    Age 0–17 21.3% 3.9% 0.208 22.1% 3.2% < .001 21.5% 2.9%
    Age 18–39 23.6% 3.4% < .001 24.3% 3.1% < .001 26.6% 4.0%
    Age 40–64 31.8% 3.3% 0.004 31.2% 2.7% 0.043 31.5% 2.8%
    Age 65+ 23.3% 6.4% < .001 22.4% 5.1% < .001 20.5% 4.8%
% In-County Residents that are Females, 2018 49.4% 2.8% < .001 49.7% 2.0% < .001 50.5% 1.5%
% In-County Residents by Race/Ethnicity, 2018                
    Non-Hispanic White 76.0% 21.7% 0.474 76.9% 19.9% 0.090 75.4% 18.6%
    Non-Hispanic Black 9.9% 16.2% 0.110 7.5% 13.6% 0.016 9.0% 12.3%
    American Indian and Alaska Natives 3.2% 10.6% < .001 2.3% 6.0% < .001 1.4% 3.8%
    Asian 0.9% 2.1% < .001 1.0% 1.6% < .001 2.7% 4.0%
    Hispanic 8.7% 14.1% 0.030 10.9% 15.8% 0.100 9.9% 11.9%
    Other Races 2.1% 2.1% < .001 2.2% 1.9% 0.2% 2.5% 2.2%
% Residents in Poverty, 2018 16.5% 6.9% < .001 15.5% 5.6% < .001 13.4% 5.0%
Median Household Income, 2018 $ 49,365 $ 12,368 < .001 $ 50,094 $ 10,577 < .001 $ 58,573 $ 15,543
Non-White/White Residential Segregation, 2015–2019 27.8% 14.0% < .001 29.2% 12.8% < .001 34.9% 11.4%
% not Proficient in English, 2015–2019 1.4% 2.9% < .001 1.7% 2.7% 0.035 2.0% 2.7%
% with Broadband Access, 2015–2019 71.9% 9.1% < .001 74.0% 8.1% < .001 80.4% 6.5%
% In-County Residents Uninsured, 2018 12.5% 5.1% < .001 12.4% 5.2% < .001 9.7% 4.4%
% In-County Residents Covered by Medicare, 2018 24.6% 5.8% < .001 23.9% 5.0% < .001 21.9% 5.1%
Ratio of population to primary care physicians, 2018 3,447 2,996 < .001 2,714 1,940 < .001 1,706 1,175

Notes: Pearson’s Chi-square tests and two-group t tests were employed as appropriate to calculate the differences in county characteristics by oncology and telehealth services provision† Hospital counties were categorized based on 12-group Urban Influence Codes (UIC) into three locations: Urban (UIC class 1 or 2), rural micropolitan (UIC class 3, 5, or 8), and rural noncore (all other UIC classes).

After adjustment, rural hospitals were less likely than urban hospitals to offer telehealth services alongside cancer care (OR 0.27; 95% CI 0.14–0.55; p < .001; Table 3). Telehealth availability in hospitals providing oncology care was associated with ≥300 hospital beds compared to <100 beds (OR 2.26; 95% CI 1.31–3.87; p = 0.002), private non-profit ownership vs. public hospitals (OR 1.67; 95% CI 1.10–2.53; p = 0.015), system affiliation (OR 1.61; 95% CI 1.11–2.33; p = 0.04), Commission on Cancer accreditation (OR 2.12; 95% CI 1.43–3.15; p<0.001), and hospital leadership of an ACO compared to never participating in an ACO (OR 2.52; 95% CI 1.58–4.02; p<0.001). Similarly, among hospitals with telehealth, the likelihoods of oncology services provisions were higher among larger hospitals (≥300 beds vs. <100 beds; OR 36.78; 95% CI 22.43–60.32; p < .001), accredited hospitals (OR 2.54; 95% CI 1.92–3.35; p < .001), hospitals with higher ratios of Medicare and Medicaid inpatient days, and those that are currently leading an ACO (OR 1.44; 95% CI 1.07–1.92; p = 0.014). There were no significant county-level factors associated with telehealth availability among hospitals with oncology services, whereas county-level poverty rates and uninsured rates were associated with lower odds of having oncology services among hospitals that offered telehealth.

10.1371/journal.pone.0281071.t003 Factors associated with availability of telehealth care in hospitals providing oncology services in 2019.
Among Hospitals with Oncology Care Among Hospitals with Telehealth
Telehealth vs. No Telehealth Oncology vs. No Oncology
Hospital Location
    Urban ref. ref.
    Rural Micropolitan 0.36 (0.21, 0.65)*** 0.80 (0.57, 1.11)
    Rural Noncore 0.27 (0.14, 0.55)*** 0.43 (0.30, 0.63)***
Hospital Beds    
    <100 ref. ref.
    100–299 1.50 (0.99, 2.29) 6.66 (4.96, 8.94)***
    300+ 2.26 (1.31, 3.87)** 36.78 (22.43, 60.32)***
Hospital Ownership    
    Public ref. ref.
    Private non-profit 1.67 (1.10, 2.53)* 1.12 (0.84, 1.49)
    Private for-profit 1.63 (0.92, 2.88) 0.65 (0.44, 0.96)*
System Affiliation    
    Yes vs. No 1.61 (1.11, 2.33)* 0.74 (0.57, 0.96)*
Accreditation by Joint Commission or DVN    
    Yes vs. No 1.11 (0.67, 1.86) 2.54 (1.92, 3.35)***
Commission on Cancer Accredited    
    Yes vs. No 2.12 (1.43, 3.15)*** -
Ratio of Medicare Inpatient Days to Total Inpatient Days    
    <45% ref. ref.
    45%-55% 0.69 (0.45, 1.06) 1.77 (1.31, 2.38)***
    >55% 0.72 (0.45, 1.15) 1.49 (1.11, 2.00)**
Ratio of Medicaid Inpatient Days to Total Inpatient Days    
    Tertile I: <10% ref. ref.
    Tertile II: 10–20% 1.12 (0.71, 1.76) 1.90 (1.45, 2.49)***
    Tertile III: >20% 0.82 (0.52, 1.29) 1.41 (1.05, 1.89)*
Health Professional Shortage Area—Primary Care, 2020    
    None ref. ref.
    Part county 1.94 (0.67, 5.62) 0.30 (0.18, 0.49)***
    Whole county 1.05 (0.60, 1.85) 0.67 (0.46, 0.98)*
Rural Health Clinics Co-located at Hospital    
    Yes 1.56 (0.98, 2.49) 1.35 (1.03, 1.76)*
    No ref. ref.
    Missing 0.13 (0.08, 0.23)*** 0.11 (0.08, 0.17)***
Accountable Care Organization (ACO)    
    Hospital/system current leads an ACO 2.52 (1.58, 4.02)*** 1.44 (1.07, 1.92)*
    Hospital/system currently participates in an ACO (but not its leader) 1.25 (0.82, 1.90) 1.18 (0.90, 1.56)
    Hospital/system previously led or participated in an ACO 1.97 (0.73, 5.32) 1.48 (0.81, 2.71)
    Hospital/system has never participated or led an ACO ref. ref.
County Characteristics of Hospital Location
% In-County Residents Age 65 or Older, 2018 1.09 (0.70, 1.70) 1.18 (0.90, 1.55)
% In-County Residents that are Females, 2018 1.17 (0.29, 4.67) 1.79 (0.81, 3.98)
% In-County Residents by Race/Ethnicity, 2018    
    Non-Hispanic White  
    Non-Hispanic Black 0.94 (0.80, 1.11) 1.00 (0.89, 1.12)
    American Indian and Alaska Natives 2.18 (0.79, 6.03) 1.01 (0.78, 1.31)
    Asian 0.98 (0.63, 1.51) 0.99 (0.67, 1.44)
    Hispanic 0.82 (0.65, 1.03) 0.95 (0.81, 1.13)
    Other Races 0.66 (0.32, 1.35) 0.85 (0.47, 1.53)
% Residents in Poverty, 2018 0.79 (0.46, 1.36) 0.70 (0.50, 0.97)*
Non-White/White Residential Segregation, 2015–2019 1.03 (0.88, 1.22) 1.19 (1.08, 1.31)***
% not Proficient in English, 2015–2019 1.02 (0.38, 2.69) 1.07 (0.50, 2.30)
% with Broadband Access, 2015–2019 1.02 (0.66, 1.57) 1.49 (1.17, 1.89)**
% In-County Residents Uninsured, 2018 1.22 (0.77, 1.94) 0.61 (0.45, 0.83)**

Notes: Two separate generalized logistic mixed-effects regressions were conducted with random effects for hospital counties.

Telehealth is a critical component of strategies designed to improve health equity by reducing rural-urban disparities in cancer outcomes. Our national study found that nearly half of hospitals have both oncology and telehealth capabilities, and an additional 30% of hospitals had telehealth without oncology care capacity. Hospitals may utilize telehealth to deliver cancer treatment, monitor for toxicities, offer survivorship care, or provide palliative and postoperative care when travel for an in-person visit is not feasible. However, we found that with increasing rurality or freestanding status, there is an increased likelihood of lacking telehealth within a county or hospital, and that tens of millions of Americans live in counties without either telehealth or oncology services available at hospitals. As hospitals in counties with lower income and higher uninsured rates were less likely to have oncology care alongside existing telehealth capacity, expansion of oncology services to these hospitals may help address cancer care access deficiencies. Although data are lacking on sustained, post-pandemic implementation of telehealth for cancer care, it is likely that access disparities continue for rural populations.

It is crucial to encourage hospitals caring for cancer patients without the availability of telehealth to sustainably adopt this critical adjunct to cancer care, if they have not already done so post-pandemic. Telehealth for cancer care might include virtual clinic visits, virtual supervision of therapy, remote patient monitoring, or clinician-to-clinician consultation [14]. Our analysis indicates that hospitals caring for cancer patients without the benefits of telehealth are more likely to be rural or micropolitan, and not affiliated with a hospital system. These findings suggest that rural hospitals might benefit from advocacy for connection via telehealth to referral centers so that their patients have the benefit of subspecialty consultation when needed, without burdensome long-distance travel for care. Importantly, connections between referral centers and rural hospitals requires commitments to outreach care from both practice settings to ensure patients have adequate access to cancer telehealth. While both patient-to-clinician and clinician-to-clinician applications of telehealth have the potential to improve rural cancer care, clinician-to-clinician telemedical communication may have the highest yield for integration of oncologic referral centers with outlying community cancer centers. Specific applications warranting further investigation include remote “curbside” consultation, telementoring, multidisciplinary tumor boards, and care coordination.

Our analysis identifies geographic areas of the United States whose residents are at elevated risk for barriers to high-quality cancer care. 26.6 million people in 41 states reside within low-access counties without any hospital-based access to cancer care or telemedical infrastructure that might connect them to oncologists. It is critical for advocates for health equity at the state and federal levels to ensure that mechanisms are in place to improve local care for these counties’ residents or ensure that they are able to access resources in nearby counties. Even if counties do not have ready access to oncology care, telehealth may facilitate tele-oncology services, virtual tumor boards and the like to help ensure that patients receive quality cancer diagnosis and treatment [11]. The loosening of Medicare telehealth regulations and promotion of payment parity during the SARS-CoV-2 pandemic, the potential for those regulations to be extended beyond the pandemic, the flow of pandemic-related telehealth funding, and teleoncology innovations may help incentivize expansion of telehealth services in the future [15,16]. Importantly, telehealth expansion should occur in the context of broader efforts to improve digital health equity, including increasing availability of broadband internet access for rural populations.

Our findings found specifically that American Indian/Alaska Native populations have less access to telemedicine for cancer care, consistent with earlier work on this populations’ barriers to high-quality oncologic services [7,8,17]. While rural populations have higher cancer-related mortality rates than urban patients, among rural populations, American Indian/Alaska Native populations have the highest rural-urban disparity in cancer mortality [18,19]. Given the added complexities of the Indian Health Service system and related requirements for tribal affiliation and/or residence on reservation lands, American Indian/Alaska Native residents may be particularly burdened to find culturally competent and low-cost care locally [20].

Hospitals that report offering both telehealth and oncology services may not currently be offering telehealth specifically for cancer care. These institutions should strongly consider including oncology in their telehealth services; we anticipate that the investment required for expansion of telehealth to cancer care is likely less than that required for health systems to adopt telehealth de novo. Additionally, available hospital-based data currently do not distinguish between clinician-patient applications of telehealth (e.g., virtual clinic visits and remote patient monitoring) and clinician-clinician applications (e.g., remote “curbside” consultations, or multidisciplinary cancer treatment conferences). These limitations of available data suggest an opportunity to improve datasets, like those generated by the AHA survey, to capture detailed information on specific telehealth applications to guide expansion of access to remote cancer care and other service lines amenable to telehealth.

Our analysis is limited in several key aspects, related to the data available through the AHA. First, our focus on hospitals who provide outpatient and/or consultative care via telehealth may exclude hospitals that provide telehealth only in the context of eICU, inpatient, or addiction services; however, we believe that these latter use cases are somewhat less relevant to access to cancer care. Second, hospitals’ reported use of telehealth service does not specify whether the hospital is the originator or acceptor of telehealth consultations (or both). To the extent that there might be telemedical communication among hospitals, we are therefore unable to determine which hospitals function as “hubs” or “spokes” for outreach care. Third, some rural hospitals may have responded to the AHA survey jointly with larger parent hospitals within their health system, thereby overestimating the resources available in rural hospitals. Fourth, while arguably representing the best data available, the AHA respondent set does not represent the entirety of cancer care delivery in the United States. While we imputed data for 2019 non-responders to the AHA survey from prior years, not all cancer care locations are categorized as hospitals. Finally, the 2019 AHA survey does not capture changes in the utilization of telehealth services attributable to the SARS-CoV-2 pandemic beginning in early 2020. Importantly, however, our analysis both represents the most contemporary data available on hospital-based telehealth infrastructure, and serves as a necessary pre-pandemic baseline for future investigations into this important topic. Overall telehealth utilization appears to have peaked in April, 2020 with claims decreasing by approximately half soon thereafter, and continuing to decrease in early 2022 [21,22]. Additionally, in early 2021, oncology was estimated to account for only 8% of all telehealth claims, suggesting that even if hospital-based infrastructure increased during the pandemic, utilization remains low [22].

 Conclusions

While hospital-based cancer care and telehealth resources are widely available across the United States, a substantial minority of patients across 42 states as well as American Indian/Alaska Native residents are at risk for geographic barriers to high-quality cancer care. We recommend continuing to monitor the impact of SARS-CoV-2 pandemic-related policies and innovations on the availability of telehealth services for oncology care. Furthermore, improvements in data collection, and advocacy to prioritize adoption of telehealth as a critical element of cancer care, will improve health equity by decreasing disparities attributable to place of residence.

 References Khan-Gates JA, Ersek JL, Eberth JM, Adams SA, Pruitt SL. Geographic Access to Mammography and Its Relationship to Breast Cancer Screening and Stage at Diagnosis: A Systematic Review. Womens Health Issues. 2015;25: 482–493. doi: 10.1016/j.whi.2015.05.010 26219677 Lin CC, Bruinooge SS, Kirkwood MK, Olsen C, Jemal A, Bajorin D, et al. Association between geographic access to cancer care, insurance, and receipt of chemotherapy: Geographic distribution of oncologists and travel distance. J Clin Oncol. 2015;33: 3177–3185. doi: 10.1200/JCO.2015.61.1558 26304878 Lin CC, Bruinooge SS, Kirkwood MK, Hershman DL, Jemal A, Guadagnolo BA, et al. Association Between Geographic Access to Cancer Care and Receipt of Radiation Therapy for Rectal Cancer. Int J Radiat Oncol Biol Phys. 2016;94: 719–728. doi: 10.1016/J.IJROBP.2015.12.012 26972644 Yee EK, Coburn NG, Zuk V, Davis LE, Mahar AL, Liu Y, et al. Geographic impact on access to care and survival for non-curative esophagogastric cancer: a population-based study. Gastric Cancer. 2021;24: 790–799. doi: 10.1007/s10120-021-01157-w 33550518 Reade C, Elit L. Trends in gynecologic cancer care in North America. Obstet Gynecol Clin North Am. 2012;39: 107–29. doi: 10.1016/j.ogc.2012.02.003 22640706 Kale MS, Wisnivesky J, Taioli E, Liu B. The Landscape of US Lung Cancer Screening Services. Chest. 2019;155: 900–907. doi: 10.1016/J.CHEST.2018.10.039 30419236 Hung P, Deng S, Zahnd WE, Adams SA, Olatosi B, Crouch EL, et al. Geographic disparities in residential proximity to colorectal and cervical cancer care providers. Cancer. 2020;126: 1068–1076. doi: 10.1002/cncr.32594 31702829 Onega T, Alford-Teaster J, Wang F. Population-based geographic access to parent and satellite National Cancer Institute Cancer Center Facilities. Cancer. 2017;123: 3305–3311. doi: 10.1002/cncr.30727 28464212 Kelsey Kirkwood M, Hanley A, Bruinooge SS, Garrett-Mayer E, Levit LA, Schenkel C, et al. The State of Oncology Practice in America, 2018: Results of the ASCO Practice Census Survey. J Oncol Pract. 2018;14: e412–e420. doi: 10.1200/JOP.18.00149 29906211 Sheetz KH, Chhabra KR, Smith ME, Dimick JB, Nathan H. Association of Discretionary Hospital Volume Standards for High-risk Cancer Surgery With Patient Outcomes and Access, 2005–2016. JAMA Surg. 2019;154: 1005–1012. doi: 10.1001/jamasurg.2019.3017 31411663 Charlton M, Schlichting J, Chioreso C, Ward M, Vikas P. Challenges of Rural Cancer Care in the United States. Oncol (willist Park. 2015;29: 633–40. 26384798 National Advisory Committee On Rural Health and Human Services. Telehealth in Rural America. 2015. Available: https://www.hrsa.gov/sites/default/files/hrsa/advisory-committees/rural/publications/2015-telehealth.pdf. Health Resources and Services Administration. Area Health Resources Files. Available: https://data.hrsa.gov/topics/health-workforce/ahrf. Shalowitz DI, Moore CJ. Telemedicine and Gynecologic Cancer Care. Obstetrics and Gynecology Clinics of North America. W.B. Saunders; 2020. pp. 271–285. doi: 10.1016/j.ogc.2020.02.003 32451018 Royce TJ, Sanoff HK, Rewari A. Telemedicine for Cancer Care in the Time of COVID-19. JAMA Oncol. 2020;6: 1698–1699. doi: 10.1001/jamaoncol.2020.2684 32672821 Murphy A, Kirby A, Lawlor A, Drummond FJ, Heavin C. Mitigating the Impact of the COVID-19 Pandemic on Adult Cancer Patients through Telehealth Adoption: A Systematic Review. Sensors (Basel). 2022;22. doi: 10.3390/s22093598 35591287 Kruse CS, Bouffard S, Dougherty M, Parro JS. Telemedicine Use in Rural Native American Communities in the Era of the ACA: a Systematic Literature Review. J Med Syst. 2016;40. doi: 10.1007/s10916-016-0503-8 27118011 Henley SJ, Anderson RN, Thomas CC, Massetti GM, Peaker B, Richardson LC. Invasive Cancer Incidence, 2004–2013, and Deaths, 2006–2015, in Nonmetropolitan and Metropolitan Counties—United States. MMWR Surveill Summ. 2017;66: 1–13. doi: 10.15585/mmwr.ss6614a1 28683054 Probst JC, Zahnd WE, Hung P, Eberth JM, Crouch EL, Merrell MA. Rural-Urban Mortality Disparities: Variations Across Causes of Death and Race/Ethnicity, 2013–2017. Am J Public Health. 2020;110: 1325–1327. doi: 10.2105/AJPH.2020.305703 32673111 Eberth JM, Hung P, Benavidez GA, Probst JC, Zahnd WE, McNatt MK, et al. The Problem Of The Color Line: Spatial Access To Hospital Services For Minoritized Racial And Ethnic Groups. Health Aff. 2022;41: 237–246. doi: 10.1377/hlthaff.2021.01409 35130071 FAIRHealth. Monthly Telehealth Regional Tracker. In: https://www.fairhealth.org/states-by-the-numbers/telehealth. McKinsey and Company. Telehealth: A quarter-trillion-dollar post-COVID-19 reality? In: https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/telehealth-a-quarter-trillion-dollar-post-covid-19-reality. 2021. 10.1371/journal.pone.0281071.r001 Decision Letter 0 Bhaskar Sonu Academic Editor 2023 Sonu Bhaskar This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 0

28 Nov 2022

PONE-D-22-22633Geographic Access to Hospital-Based Telehealth for Cancer CarePLOS ONE

Dear Dr. Shalowitz,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I have now received reports from three reviewers. Based on the assessment and taking into consideration the feedback, I would like to invite you to revise your manuscript and provide a point-by-point rebuttal to all the comments.

Please submit your revised manuscript by Jan 12 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Sonu Menachem Maimonides Bhaskar, MD PhD

Academic Editor

PLOS ONE

Journal Requirements

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

3. Please amend your current ethics statement to include the full name of the ethics committee/institutional review board(s) that approved your specific study. 

4. Thank you for stating the following financial disclosure: 

Dr. Shalowitz received funding via the Wake Forest Comprehensive Cancer Center NCI cancer support grant (P30CA012197), and has received consulting fees from Nimble Co, LLC (purview.net) unrelated to the current work.

Please state what role the funders took in the study.  If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 

If this statement is not correct you must amend it as needed. 

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

5. Thank you for stating the following in the Competing Interests section: 

Dr. Shalowitz received funding via the Wake Forest Comprehensive Cancer Center NCI cancer support grant (P30CA012197), and has received consulting fees from Nimble Co, LLC unrelated to the current work. 

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared. 

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

6. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

7. Please include a caption for figure 1.

8. We note that Figure 1 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.  

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

9. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files

Additional Editor Comments:

I have now received reports from three reviewers. Based on the assessment and taking into consideration the feedback, I would like to invite you to revise your manuscript and provide a point-by-point rebuttal to all the comments.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This manuscript provides an interesting overview of the telehealth and oncology services in US hospitals prior to the pandemic. The authors are to be commended for the readable and logical organization of the manuscript. A few comments relating to the methods and certain key design decisions are noted below.

1. It is not clear if the availability of telehealth services correlate with the quality of the care provided at a given hospital. Could the authors comment on the quality of the services provided by these hospitals?

2. Do the hospitals that provide telehealth services, use telehealth to provide oncology care? Are there data to show what the telehealth services in these hospitals were used for in the pre-pandemic era?

3. It is difficult to assess policy/clinical implications of this work without knowing how the lack of availability of services/care relate to cancer outcomes--how do the differences in availability of services translate to disparities in cancer outcomes?

4. The results show that larger hospitals are 37 times more likely to provide oncology services among those hospitals that provide telehealth. Most of the smaller/rural hospitals are less likely to provide oncology care or access to telehealth services—perhaps these hospitals are more likely to refer cancer patients to nearby larger hospitals for cancer care? If that is true, the availability of telehealth services in larger hospitals that provide oncology services could perhaps help reduce cancer care deficiencies.

Overall, it is not clear if the greatest improvement in health outcomes depend on increasing oncology and telehealth services in rural hospitals OR further increasing the telehealth capacity in existing larger hospitals. It is not clear how a policy-maker could use this study to improve care for the population.

Reviewer #2: Reviewer name: Alma Nurtazina

Geographic Access to Hospital-Based Telehealth for Cancer Care

Corresponding author: David Shalowitz, M.D.. MSHP

Wake Forest University School of Medicine

Winston-Salem, NC UNITED STATES

The authors present the results of a cross-sectional study based on the data from three main surveys conducted in 2013-2019 in the USA. In total, data from 4540 hospitals were analyzed for telehealth and oncology services.

The title is expected to contain a place of study because of the high variability of telehealth services across different countries. The abstract describes the essential information in the work. The paper’s goal is within the scope of the journal. The introductory section adequately explains the framework of the research. The importance of the research idea is evident. The authors have applied an appropriate methodology to their research and clearly described it. The presentation of the study is complete for a scientific paper. The results are described and analyzed adequately. The article is written clearly and logically consistently. The conclusion is logically supported by the obtained results.

There are a few minor limitations:

1. The title does not contain the place of the study.

2. The authors did not mention study design which is a cross-sectional.

3. There are several errors in the tables’ design and data presentation.

4. The reference list is incomplete.

Reviewer #3: Thank you for giving me the opportunity to review this research, which evaluates US hospitals’ ability to provide equitable access to oncology services via telehealth. This is an important study that highlights the number of Americans with cancer who had to attend all cancer appointments in person prior to the pandemic. This is a well-written manuscript. However, considering that the data for telehealth utilization are pre-pandemic (and therefore of limited utility to today’s researchers and policymakers), the authors need to ensure that they are appropriately contextualizing the research to highlight its relevance. Please see below for specific areas for improvement.

Major

1. Thank you for acknowledging that these data are pre-pandemic and therefore likely do not represent the current use of telemedicine in hospitals. This is a significant limitation given what we know about the uptake of telemedicine in the US since 2020, and should be reflected in the title. Further, in order to make this relevant to today’s researchers and policy makers, the authors should consider bringing this limitation to the forefront of the discussion-- currently it is not mentioned until late in the discussion. For example, in the first discussion paragraph, when you discuss increasing rurality being associated with lower telehealth rates, I suggest you discuss how this disparity is likely still the case today (some data should be available to support this), even though your analysis is pre-COVID.

2. In the second discussion paragraph, the authors write about how it is “crucial to encourage hospitals caring for cancer patients” to adopt telehealth. Again, this needs to be framed in the understanding that this may have already happened. Further, there should be more specifics included. For example, what do the authors mean by “encourage?” Through national policy? Medicare reform? There is a robust discussion currently around making certain telemedicine reimbursement waivers permanent beyond the Public Health Emergency, and this might be a good place to bring in some of these arguments to describe how hospitals would be encouraged to adopt these technologies.

3. The authors point out that only 8% of telehealth claims were for oncology in 2021. This statement needs to be contextualized in comparison to other specialties, and regarding what percent is appropriate for oncology. For example, my understanding is that an initial visit for a cancer diagnosis needs to be done with an in person exam. Are there initial visits that are appropriate for telemedicine? Further, rural patients who are on active treatment typically have their visits stacked on the same day as infusion, radiation, or radiology visits (see: DeGuzman et al, (2015). Identifying barriers to navigation needs of cancer survivors in rural areas. Journal of Oncology Navigation & Survivorship, 6, 34-42), so a telehealth visit may not make sense in these cases.

4. It may be worthwhile to consider discussing that even as telehealth becomes more ubiquitous in hospitals, those living in rural areas often lack broadband, which raises its own set of challenges. Since COVID-19, alternative origination sites (such as public libraries), and the need to extend federal regulations that support reimbursement for telemedicine services.

Minor

1. In the section on Data Sources (page 4), it would be clearer to list the data sources in the same order that you explain them in that section (i.e. switch #2 and #3)

2. On page 5, line 133, it would be clearer to state what the outcomes are before explaining you they were derived: “Thus study has two primary outcomes: x and y.”

3. On page 5 lines 140-141, it would be clearer to put the statement “per their self-reported telehealth and oncology services provisions” in parenthesis

4. On page 8, line 199, although I was able to figure out where you got the number 2326 from in your table (hospitals providing cancer care), it took a while to figure it out and I wonder if this could be explained clearer.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Alma Nurtazina

Reviewer #3: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

 10.1371/journal.pone.0281071.r002 Author response to Decision Letter 0 Submission Version 1

29 Dec 2022

See separately uploaded file labeled "Response to Reviewers."

Submitted filename: Geographic Access Telemedicine Revisions Letter PLoS ONE.docx

 10.1371/journal.pone.0281071.r003 Decision Letter 1 Bhaskar Sonu Academic Editor 2023 Sonu Bhaskar This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 1

16 Jan 2023

Pre-Pandemic Geographic Access to Hospital-Based Telehealth for Cancer Care in the United States

PONE-D-22-22633R1

Dear Dr. Shalowitz,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Sonu Bhaskar, MD PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for submitting the revised version of your manuscript. I am pleased to accept the manuscript in its current form. Thank you for submitting your work to PLOS One.

Reviewers' comments:

 10.1371/journal.pone.0281071.r004 Acceptance letter Bhaskar Sonu Academic Editor 2023 Sonu Bhaskar This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

23 Jan 2023

PONE-D-22-22633R1

Pre-Pandemic Geographic Access to Hospital-Based Telehealth for Cancer Care in the United States

Dear Dr. Shalowitz:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Sonu Bhaskar

Academic Editor

PLOS ONE