The influence of visiting consultant clinics on measures of access to cancer care: evidence from the state of Iowa

Interventions to improve access to cancer care in underserved populations in high income countries: a systematic review

Background

Underserved populations both globally and in Canada face serious cancer inequities that result from systemic economic, environmental, and social conditions. These pose barriers in access to cancer care and lead to suboptimal cancer care experiences and outcomes. Knowledge of effective interventions to improve access to cancer care is needed to inform the design of tailored interventions for these populations.

Aim

To identify interventions and programs to improve access to cancer care for underserved populations in high income countries with universal health coverage (UHC) and the United States (US) throughout the cancer care continuum.

Methods

We conducted a systematic review following the PRISMA standards. We searched Medline, EMBASE, PsycINFO, CINAHL, Scopus, and the Cochrane Library. Inclusion criteria: quantitative and qualitative studies published in English in the last 10 years (2013-2023), describing interventions/programs to improve access to cancer care for underserved populations (18 years and over). We included studies in the US given the body of scholarship on equity in cancer care in that country. Screening, data extraction and analysis were undertaken by two independent reviewers.

Results

Our search yielded 7,549 articles, and 74 met the inclusion criteria. Of these, 56 were conducted in the US, 8 in Australia, 6 in Canada, and 4 in the United Kingdom. Most (90.5%) were quantitative studies and 47.3% were published between 2020-2023. Seven types of interventions were identified: patient navigation, education and counselling, virtual health, service redesign, financial support, improving geographical accessibility and multicomponent interventions. Interventions were mainly designed to mitigate language, distance, financial, lack of knowledge and cultural barriers. Most interventions focused on access to cancer screening, targeted rural populations, racialized groups and people with low socioeconomic status, and were conducted in community-based settings. The majority of interventions or programs significantly improved access to cancer care.

Conclusion

Our systematic review findings suggest that interventions designed to remove specific barriers faced by underserved populations can improve access to cancer care. Few studies came from countries with UHC. Research is required to understand tailored interventions for underserved populations in countries with UHC.

The Association Between Oncology Outreach and Timely Treatment for Rural Patients with Breast Cancer: A Claims-Based Approach

BACKGROUND

Oncology outreach is a common strategy for increasing rural access to cancer care, where traveling oncologists commute across healthcare settings to extend specialized care. Examining the extent to which physician outreach is associated with timely treatment for rural patients is critical for informing outreach strategies.

METHODS

We identified a 100% fee-for-service sample of incident breast cancer patients from 2015 to 2020 Medicare claims and apportioned them into surgery and adjuvant therapy cohorts based on treatment history. We defined an outreach visit as the provision of care by a traveling oncologist at a clinic outside of their primary hospital service area. We used hierarchical logistic regression to examine the associations between patient receipt of preoperative care at an outreach visit (preoperative outreach) and > 60-day surgical delay, and patient receipt of postoperative care at an outreach visit (postoperative outreach) and > 60-day adjuvant delay.

RESULTS

We identified 30,337 rural-residing patients who received breast cancer surgery, of whom 4071 (13.4%) experienced surgical delay. Among surgical patients, 14,501 received adjuvant therapy, of whom 2943 (20.3%) experienced adjuvant delay. In adjusted analysis, we found that patient receipt of preoperative outreach was associated with reduced odds of surgical delay (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.61-0.91); however, we found no association between patient receipt of postoperative outreach and adjuvant delay (OR 1.04, 95% CI 0.85-1.25).

CONCLUSIONS

Our findings indicate that preoperative outreach is protective against surgical delay. The traveling oncologists who enable such outreach may play an integral role in catalyzing the coordination and timeliness of patient-centered care.

Characterizing the Traveling Oncology Workforce and Its Influence on Patient Travel Burden: A Claims-Based Approach

PURPOSE

Oncology outreach is a common strategy for extending cancer care to rural patients. However, a nationwide characterization of the traveling workforce that enables this outreach is lacking, and the extent to which outreach reduces travel burden for rural patients is unknown.

METHODS

This cross-sectional study analyzed a rural (nonurban) subset of a 100% fee-for-service sample of 355,139 Medicare beneficiaries with incident breast, colorectal, and lung cancers. Surgical, medical, and radiation oncologists were linked to patients using Part B claims, and traveling oncologists were identified by observing hospital service area (HSA) transition patterns. We defined oncology outreach as the provision of cancer care by a traveling oncologist outside of their primary HSA. We used hierarchical gamma regression models to examine the separate associations between patient receipt of oncology outreach and one-way patient travel times to chemotherapy, radiotherapy, and surgery.

RESULTS

On average, 9,935 of 39,960 oncologists conducted annual outreach, where 57.8% traveled with low frequency (0-1 outreach visits/mo), 21.1% with medium frequency (1-3 outreach visits/mo), and 21.1% with high frequency (>3 outreach visits/mo). Oncologists provided surgery, radiotherapy, and chemotherapy to 51,715, 27,120, and 5,874 rural beneficiaries, respectively, of whom 2.5%, 6.9%, and 3.6% received oncology outreach. Rural patients who received oncology outreach traveled 16% (95% CI, 11 to 21) and 11% (95% CI, 9 to 13) less minutes to chemotherapy and radiotherapy than those who did not receive oncology outreach, corresponding to expected one-way savings of 15.9 (95% CI, 15.5 to 16.4) and 11.9 (95% CI, 11.7 to 12.2) minutes, respectively.

CONCLUSION

Our study introduces a novel claims-based approach for tracking the nationwide traveling oncology workforce and supports oncology outreach as an effective means for improving rural access to cancer care.

Geographic differences in community oncology provider and practice location characteristics in the central United States

PURPOSE

How care delivery influences urban-rural disparities in cancer outcomes is unclear. We sought to understand community oncologists' practice settings to inform cancer care delivery interventions.

METHODS

We conducted secondary analysis of a national dataset of providers billing Medicare from June 1, 2019 to May 31, 2020 in 13 states in the central United States. We used Kruskal-Wallis rank and Fisher's exact tests to compare physician characteristics and practice settings among rural and urban community oncologists.

FINDINGS

We identified 1,963 oncologists practicing in 1,492 community locations; 67.5% practiced in exclusively urban locations, 11.3% in exclusively rural locations, and 21.1% in both rural and urban locations. Rural-only, urban-only, and urban-rural spanning oncologists practice in an average of 1.6, 2.4, and 5.1 different locations, respectively. A higher proportion of rural community sites were solo practices (11.7% vs 4.0%, P<.001) or single specialty practices (16.4% vs 9.4%, P<.001); and had less diversity in training environments (86.5% vs 67.8% with <2 medical schools represented, P<.001) than urban community sites. Rural multispecialty group sites were less likely to include other cancer specialists.

CONCLUSIONS

We identified 2 potentially distinct styles of care delivery in rural communities, which may require distinct interventions: (1) innovation-isolated rural oncologists, who are more likely to be solo providers, provide care at few locations, and practice with doctors with similar training experiences; and (2) urban-rural spanning oncologists who provide care at a high number of locations and have potential to spread innovation, but may face high complexity and limited opportunity for care standardization.

A look at the gynecologic oncologist workforce - Are we meeting patient demand?

OBJECTIVE

to examine the geographic distribution of gynecologic oncologists (GO) and assess if the GO workforce is meeting the demand for oncology services for patients with gynecologic cancers.

METHODS

We identified GO by National Provider Identifiers (NPI) and calculated county-level density of GO. County-level gynecologic cancer rates were derived from the U.S. Cancer Statistics to represent demand for GO services. A spatial data plot compared GO workforce to gynecologic cancer service demand. U.S. census county-level demographic information was collected and compared.

RESULTS

In 2019, 1527 GO had a registered NPI. Of 3142 counties in the US, 2864 (91.2%) counties had no GO in their local county and 1943 (61.8%) counties had no GO in local or adjacent (neighboring) counties. As the gynecologic cancer rate increases (described in quintiles) in counties, there are fewer counties without a GO or adjacent GO. However, county-level GO density (number of GO per 100,000 women) did not significantly increase as the county-level incidence of gynecologic cancer increased (r = -0.12, p = 0.06)… Women living in counties with the highest gynecologic cancer rates and without access to a GO were more likely to reside in a rural area where residents had a lower median income and were predominately of White race..

CONCLUSION

There are a significant number of counties in the U.S. without a GO. As county-level gynecologic cancer incidence increased, the proportion of counties without a GO decreased; GO density did not increase with increasing cancer rates. Rural counties with high gynecologic incidence rates are underserved by GO. This information can inform initiatives to improve outreach and collaboration to better meet the needs of patients in different geographic areas.

Temporal Changes in Esophageal Cancer Mortality by Geographic Region: A Population-based Analysis

Purpose

To analyze differences in esophageal cancer survival by geographic region of the U.S. from the 1970s to the 2000s, and attribute the causes of these discrepancies.

Methods

Raw data were obtained from the Surveillance Epidemiology and End Results (SEER) program of the National Cancer Institute. Patients were stratified by decade of diagnosis and by geographic region (East, Hawaii/Alaska, Midwest, Southwest, and West), containing SEER registries. The Kaplan-Meier method with the log-rank test was used to compare the overall survival (OS) among these geographic groups. A multivariate Cox Proportional Hazard analysis was conducted to evaluate the impact of the following factors on differences in survival: patient age, gender, race, tumor stage, site, histology, treatment method, and metropolitan size.

Results

A total of 87,834 patients were identified. OS has increased significantly since 1973, with five-year OS improving from 4.9% (the 1970s) to 15.3% (2000s) (P<0.001). Residence in the East was prognostic for higher OS compared to all the other regions, with a median OS of six months in the 1970s and 12 months in the 2000s (P<0.001). The multivariate analysis revealed increased age, African American race, distant disease, non-distal tumor location, squamous cell histology, and no radiation therapy were associated with worse OS. The West and East had the highest amount of cancer centers (12 and seven, respectively). And the East had the highest number of cancer centers per person (5.7E-07) while the South had the lowest (1.6E-07).

Conclusions

There are disparities in esophageal cancer survival and quality of care through different geographic regions of the U.S., which may be attributed to a combination of the unbalanced distribution of medical resources, the regional differences in cancer biology, and other lifestyle and socioeconomic factors. More research should be conducted to further characterize regional differences and guide the implementation of improvements in survival.

Intraoperative Radiotherapy for Breast Cancer Treatment in a Rural Community

BACKGROUND

Access to health care poses particular challenges for patients living in rural communities. Intraoperative radiotherapy (IORT) offers a treatment alternative to traditional whole-breast radiation therapy (WBRT) for select patients. This study aimed to analyze the use of IORT for patients undergoing breast-conserving surgery at an academic institution located in a rural state.

METHODS

A retrospective review analyzed all patients at a single institution with a diagnosis of ductal carcinoma in situ (DCIS) or invasive breast cancer from April 2012 to January 2017 who were undergoing breast-conserving surgery with either IORT or WBRT. Student's t test or Fisher's exact test was used to make statistical comparisons.

RESULTS

Patients undergoing IORT (n = 117) were significantly older than patients treated with WBRT (n = 191) (65.6 vs 58.6 years; p < 0.001) and had smaller tumors on both preoperative imaging (1.04 vs 1.66 cm; p < 0.05) and final pathology (0.99 vs 1.48 cm; p < 0.05). Patients receiving IORT lived farther from the treating facility than patients treated with WBRT (67.2 vs 30.8 miles; p < 0.05). To account for biases created in the IORT selection criteria, subgroup analysis was performed for women receiving WBRT who fulfilled IORT selection criteria, and distance traveled remained significant (67.2 vs 31.4 miles; p < 0.05). Neither recurrence nor survival differed between the IORT and WBRT groups. Medicare reimbursement for IORT was approximately 50% more than for WBRT.

CONCLUSIONS

For women from rural communities, IORT appears to be an attractive option because these women tend to be older and to live farther from the treatment facility.

Variation in geographic access to chemotherapy by definitions of providers and service locations: a population-based observational study

Background

An aging population, with its associated rise in cancer incidence and strain on the oncology workforce, will continue to motivate patients, healthcare providers and policy makers to better understand the existing and growing challenges of access to chemotherapy. Administrative data, and SEER-Medicare data in particular, have been used to assess patterns of healthcare utilization because of its rich information regarding patients, their treatments, and their providers. To create measures of geographic access to chemotherapy, patients and oncologists must first be identified. Others have noted that identifying chemotherapy providers from Medicare claims is not always straightforward, as providers may report multiple or incorrect specialties and/or practice in multiple locations. Although previous studies have found that specialty codes alone fail to identify all oncologists, none have assessed whether various methods of identifying chemotherapy providers and their locations affect estimates of geographic access to care.

Methods

SEER-Medicare data was used to identify patients, physicians, and chemotherapy use in this population-based observational study. We compared two measures of geographic access to chemotherapy, local area density and distance to nearest provider, across two definitions of chemotherapy provider (identified by specialty codes or billing codes) and two definitions of chemotherapy service location (where chemotherapy services were proven to be or possibly available) using descriptive statistics. Access measures were mapped for three representative registries.

Results

In our sample, 57.2 % of physicians who submitted chemotherapy claims reported a specialty of hematology/oncology or medical oncology. These physicians were associated with 91.0 % of the chemotherapy claims. When providers were identified through billing codes instead of specialty codes, an additional 50.0 % of beneficiaries (from 23.8 % to 35.7 %) resided in the same ZIP code as a chemotherapy provider. Beneficiaries were also 1.3 times closer to a provider, in terms of driving time. Our access measures did not differ significantly across definitions of service location.

Conclusions

Measures of geographic access to care were sensitive to definitions of chemotherapy providers; far more providers were identified through billing codes than specialty codes. They were not sensitive to definitions of service locations, as providers, regardless of how they are identified, generally provided chemotherapy at each of their practice locations.

Access to chemotherapy services by availability of local and visiting oncologists

PURPOSE

Geographic disparities have raised important questions about factors related to treatment choice and travel time, which can affect access to cancer care.

PATIENTS AND METHODS

Iowa residents who received chemotherapy regardless of where they were diagnosed or treated were identified through the Iowa Cancer Registry (ICR), a member of the SEER program. Oncologists and their practice locations, including visiting consulting clinics (VCCs), were tracked through the Iowa Physician Information System. Oncologists, VCCs, and patients were mapped to hospital service areas (HSAs).

RESULTS

Between 2004 and 2010, 113,885 newly diagnosed invasive cancers were entered into ICR; among patients in whom these cancers were diagnosed, 31.6% received chemotherapy as a first course of treatment. During this period, 106 Iowa oncologists practiced in 14 cities, and 82 engaged in outreach to 85 VCCs in 77 rural communities. Of patients receiving chemotherapy, 63.0% resided in an HSA that had a local oncologist and traveled 21 minutes for treatment on average. In contrast, 29.3% of patients receiving chemotherapy resided in an HSA with a VCC, and 7.7% resided in an HSA with no oncology provider. These latter two groups of patients traveled 58 minutes on average to receive chemotherapy. Availability of oncologists and VCCs affected where patients received chemotherapy. The establishment of VCCs increased access to oncologists in rural communities and increased the rate that chemotherapy was administered in rural communities from 10% to 24%, a notable increase in local access.

CONCLUSION

Access to cancer care is dependent on the absolute number of providers, but it is also dependent on their geographic distribution.