scholarly journals Relation Between Narrow Networks and Providers of Cancer Care

2017 ◽  
Vol 35 (27) ◽  
pp. 3131-3135 ◽  
Author(s):  
Laura Yasaitis ◽  
Justin E. Bekelman ◽  
Daniel Polsky
Keyword(s):  
Cancer Care ◽  
Cancer Centers ◽  
Patients With Cancer ◽  
Provider Networks ◽  
Narrow Networks ◽  
Cancer Network ◽  
The Relationship ◽  
Insurance Exchanges ◽  
Limit Access ◽  
Health Insurers

Purpose Health insurers offer plans covering a narrow subset of providers in an attempt to lower premiums and compete for consumers. However, narrow networks may limit access to high-quality providers, particularly those caring for patients with cancer. Methods We examined provider networks offered on the 2014 individual health insurance exchanges, assessing oncologist supply and network participation in areas that do and do not contain one of 69 National Cancer Institute (NCI)–Designated Cancer Centers. We characterized a network’s inclusion of oncologists affiliated with NCI-Designated Cancer Centers relative to oncologists excluded from the network within the same region and assessed the relationship between this relative inclusion and each network’s breadth. We repeated these analyses among networks offered in the same regions as the subset of 27 NCI-Designated Cancer Centers identified as National Comprehensive Cancer Network (NCCN) Cancer Centers. Results In regions containing NCI-Designated Cancer Centers, there were 13.7 oncologists per 100,000 residents and 4.9 (standard deviation [SD], 2.8) networks covering a mean of 39.4% (SD, 26.2%) of those oncologists, compared with 8.8 oncologists per 100,000 residents and 3.2 (SD, 2.1) networks covering on average 49.9% (SD, 26.8%) of the area’s oncologists ( P < .001 for all comparisons). There was a strongly significant correlation ( r = 0.4; P < .001) between a network’s breadth and its relative inclusion of oncologists associated with NCI-Designated Cancer Centers; this relationship held when considering only affiliation with NCCN Cancer Centers. Conclusion Narrower provider networks are more likely to exclude oncologists affiliated with NCI-Designated or NCCN Cancer Centers. Health insurers, state regulators, and federal lawmakers should offer ways for consumers to learn whether providers of cancer care with particular affiliations are in or out of narrow provider networks.

Availability of Outpatient Clinical Nutrition Services for Patients With Cancer Undergoing Treatment at Comprehensive Cancer Centers

2015 ◽  
Vol 11 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Mary E. Platek ◽  
Jordan Johnson ◽  
Kathleen Woolf ◽  
Nour Makarem ◽  
Danielle C. Ompad
Keyword(s):  
Cancer Care ◽  
Multidisciplinary Care ◽  
Clinical Nutrition ◽  
Cancer Centers ◽  
Patients With Cancer ◽  
Nutrition Services ◽  
Comprehensive Cancer Centers

Comprehensive cancer centers rely on referral-based clinical nutrition services, which are not always a part of multidisciplinary care. An in-depth comparison of clinical nutrition services among other approaches to cancer care is needed.

scholarly journals Access to Accredited Cancer Hospitals Within Federal Exchange Plans Under the Affordable Care Act

2017 ◽  
Vol 35 (6) ◽  
pp. 645-651 ◽  
Author(s):  
Kenneth L. Kehl ◽  
Kai-Ping Liao ◽  
Trudy M. Krause ◽  
Sharon H. Giordano
Keyword(s):  
Affordable Care Act ◽  
Cancer Care ◽  
The United States ◽  
Metal Level ◽  
Network Data ◽  
Exchange Networks ◽  
Health Maintenance ◽  
Cancer Centers ◽  
Provider Networks ◽  
The Affordable Care Act

Purpose The Affordable Care Act expanded access to health insurance in the United States, but concerns have arisen about access to specialized cancer care within narrow provider networks. To characterize the scope and potential impact of this problem, we assessed rates of inclusion of Commission on Cancer (CoC) –accredited hospitals and National Cancer Institute (NCI) –designated cancer centers within federal exchange networks. Methods We downloaded publicly available machine-readable network data and public use files for individual federal exchange plans from the Centers for Medicare and Medicaid Services for the 2016 enrollment year. We linked this information to National Provider Identifier data, identified a set of distinct provider networks, and assessed the rates of inclusion of CoC-accredited hospitals and NCI-designated centers. We measured variation in these rates according to geography, plan type, and metal level. Results Of 4,058 unique individual plans, network data were available for 3,637 (90%); hospital information was available for 3,531 (87%). Provider lists for these plans reduced into 295 unique networks for analysis. Ninety-five percent of networks included at least one CoC-accredited hospital, but just 41% of networks included NCI-designated centers. States and counties each varied substantially in the proportion of networks listed that included NCI-designated centers (range, 0% to 100%). The proportion of networks that included NCI-designated centers also varied by plan type (range, 31% for health maintenance organizations to 49% for preferred provider organizations; P = .04) but not by metal level. Conclusion A large majority of federal exchange networks contain CoC-accredited hospitals, but most do not contain NCI-designated cancer centers. These results will inform policy regarding access to cancer care, and they reinforce the importance of promoting access to clinical trials and specialized care through community sites.

scholarly journals ReCAP: Impact of Multidisciplinary Care on Processes of Cancer Care: A Multi-Institutional Study

2016 ◽  
Vol 12 (2) ◽  
pp. 155-156 ◽  
Author(s):  
Eberechukwu Onukwugha ◽  
Nicholas J. Petrelli ◽  
Kathleen M. Castro ◽  
James F. Gardner ◽  
Jinani Jayasekera ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Care ◽  
Multidisciplinary Care ◽  
Time To Treatment ◽  
Cancer Centers ◽  
Institutional Level ◽  
Care Processes ◽  
Study Results ◽  
Physician Engagement ◽  
The Relationship

QUESTION ASKED: What is the relationship between the level of implementation of multidisciplinary care (MDC) and various processes of cancer care (eg, time to treatment receipt, evaluation for enrollment onto a clinical trial) among community cancer centers serving patients diagnosed with colon, rectal, or lung cancer? There is limited generalizable evidence on this topic. It is important to answer this question using data that can generalize across cancer patients, the majority of whom receive treatment in a community cancer center. SUMMARY ANSWER: Focusing on the time to receipt of cancer-directed treatment as one key process of cancer care in this patient population, we found that the answer to our question depended on the MDC assessment area and tumor site ( Table 1 ). Among patients with colon cancer, higher MDC levels of physician engagement (ie, a higher level of physician engagement at the institutional level) were associated with a shorter time to treatment receipt, whereas higher MDC levels of case planning were associated with a longer time to treatment receipt. Among patients with rectal cancer, higher MDC levels of physician engagement were associated with a shorter time to cancer-directed treatment receipt, whereas higher MDC levels of evaluation for enrollment onto clinical trials were associated with a longer time to treatment receipt. Among patients with lung cancer, there was no association between the MDC areas of assessment and the time to cancer-directed treatment receipt. [Table: see text] METHODS: We collected data for patients receiving care at 14 National Cancer Institute (NCI) community cancer centers. We characterized the NCI community cancer centers according to their level of MDC implementation across seven MDC assessment areas and over time. Using statistical regression models, we investigated the relationship between the level of MDC implementation and various process measures, including time to treatment receipt, clinical trial evaluation, receipt of multimodality treatment, and adherence to treatment guidelines published by the National Comprehensive Cancer Network. BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: In the absence of a validated MDC assessment tool, the NCI community cancer centers used a nonvalidated tool. Additional institutional-level data would have been useful for characterizing norms and practices that may have differed across cancer centers and potentially explained variation in care processes. Although we controlled for patient demographic characteristics, baseline data were not available to document patient comorbidity or performance status level. To the extent that cancer centers at higher levels of MDC implementation may have been more likely to treat clinically complex patients, the inability to control for potential confounding bias caused by patient case mix may have influenced the study results. REAL-LIFE IMPLICATIONS: MDC models are important decision-making forums in current oncology practice. They involve oncologists in generating a comprehensive and coordinated plan of care for patients. Although MDC is purported to offer benefits to patients, there is limited generalizable evidence regarding the benefit to individuals receiving care at community cancer centers in the United States. Across various care processes that are important for characterizing cancer care, this study’s results indicate that changes in the level of MDC implementation could differentially affect the process of care, depending on the MDC area of assessment and the cancer site. In addition, the study results can be used to generate hypotheses for future studies among individuals diagnosed with colon, rectal, or lung cancer.

scholarly journals Correction to: The relationship between comorbidity medication adherence and health related quality of life among patients with cancer

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Dana Drzayich Antol ◽  
Adrianne Waldman Casebeer ◽  
Raya Khoury ◽  
Todd Michael ◽  
Andrew Renda ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Medication Adherence ◽  
Health Related Quality ◽  
Patients With Cancer ◽  
Related Quality ◽  
Health Related ◽  
The Relationship

An amendment to this paper has been published and can be accessed via the original article.

Psychology Staffing at Cancer Centers: Data From National Comprehensive Cancer Network Member Institutions

2020 ◽  
Vol 16 (11) ◽  
pp. e1343-e1354
Author(s):  
Laura Melton ◽  
Diana Krause ◽  
Jessica Sugalski
Keyword(s):  
National Comprehensive Cancer Network ◽  
Patient Care ◽  
Clinical Care ◽  
The United States ◽  
Direct Patient Care ◽  
Cancer Center ◽  
Network Member ◽  
Full Time ◽  
Cancer Centers ◽  
Cancer Network

PURPOSE: The field of psycho-oncology is relatively undeveloped, with little information existing regarding the use of psychologists at cancer centers. Comprising 30 leading cancer centers across the United States, the National Comprehensive Cancer Network (NCCN) set out to understand the trends in its Member Institutions. METHODS: The NCCN Best Practices Committee surveyed NCCN Member Institutions regarding their use of psychologists. The survey was administered electronically in the spring/summer of 2017. RESULTS: The survey was completed by 18 cancer centers. Across institutions, 94% have psychologists appointed to provide direct care to their cancer center patients. The number of licensed psychologist full-time equivalents (FTEs) on staff who provide direct patient care ranged from < 1.0 FTE (17%) to 17.0-17.9 FTEs (6%). Regarding psychologist appointments, 41% have both faculty and staff appointments, 41% have all faculty appointments, and 18% have all staff appointments. Forty-three percent of institutions indicated that some licensed psychologists at their centers (ranging from 1%-65%) do not provide any direct clinical care, and 57% indicated that all licensed psychologist on staff devote some amount of time to direct clinical care. The percent of clinical care time that is spent on direct clinical care ranged from 15%-90%. CONCLUSION: There is great variability in psychology staffing, academic appointments, and the amount of direct patient care provided by on-staff psychologists at cancer centers.

557 THE RELATIONSHIP OF PAIN AND HOPELESSNESS IN PATIENTS WITH CANCER

2006 ◽  
Vol 10 (S1) ◽  
pp. S147-S147
Author(s):  
Y. Kuzeyli Yildirim ◽  
O.O. Sertoz ◽  
M. Uyar ◽  
C. Fadiloglu
Keyword(s):  
Patients With Cancer ◽  
Relationship Of ◽  
The Relationship

scholarly journals Incarceration and Cancer-Related Outcomes (ICRO) study protocol: using a mixed-methods approach to investigate the role of incarceration on cancer incidence, mortality and quality of care

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e048863
Author(s):  
Lisa Puglisi ◽  
Alexandra A Halberstam ◽  
Jenerius Aminawung ◽  
Colleen Gallagher ◽  
Lou Gonsalves ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Quality Of Care ◽  
Mixed Methods ◽  
Cancer Incidence ◽  
Cancer Care ◽  
Survival Models ◽  
Structural Racism ◽  
Interaction Terms ◽  
The Relationship

IntroductionIncarceration is associated with decreased cancer screening rates and a higher risk for hospitalisation and death from cancer after release from prison. However, there is a paucity of data on the relationship between incarceration and cancer outcomes and quality of care. In the Incarceration and Cancer-Related Outcomes Study, we aim to develop a nuanced understanding of how incarceration affects cancer incidence, mortality and treatment, and moderates the relationship between socioeconomic status, structural racism and cancer disparities.Methods and analysisWe will use a sequential explanatory mixed-methods study design. We will create the first comprehensive linkage of data from the Connecticut Department of Correction and the statewide Connecticut Tumour Registry. Using the linked dataset, we will examine differences in cancer incidence and stage at diagnosis between individuals currently incarcerated, formerly incarcerated and never incarcerated in Connecticut from 2005 to 2016. Among individuals with invasive cancer, we will assess relationships among incarceration, quality of cancer care and mortality, and will assess the degree to which incarceration status moderates relationships among race, socioeconomic status, quality of cancer care and cancer mortality. We will use multivariable logistic regression and Cox survival models with interaction terms as appropriate. These results will inform our conduct of in-depth interviews with individuals diagnosed with cancer during or shortly after incarceration regarding their experiences with cancer care in the correctional system and the immediate postrelease period. The results of this qualitative work will help contextualise the results of the data linkage.Ethics and disseminationThe Yale University Institutional Review Board (#2000022899) and the Connecticut Department of Public Health Human Investigations Committee approved this study. We will disseminate study findings through peer-reviewed publications and academic and community presentations. Access to the deidentified quantitative and qualitative datasets will be made available on review of the request.

Evolving oncology provider perspectives on care delivery during the COVID-19 pandemic.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18609-e18609
Author(s):  
Divya Ahuja Parikh ◽  
Meera Vimala Ragavan ◽  
Sandy Srinivas ◽  
Sarah Garrigues ◽  
Eben Lloyd Rosenthal ◽  
...  
Keyword(s):  
Cancer Care ◽  
Care Delivery ◽  
The United States ◽  
Advanced Practice ◽  
Curative Surgery ◽  
Time Points ◽  
Patients With Cancer ◽  
Provider Perspectives ◽  
Significant Difference ◽  
The Impact

e18609 Background: The COVID-19 pandemic prompted rapid changes in cancer care delivery. We sought to examine oncology provider perspectives on clinical decisions and care delivery during the pandemic and to compare provider views early versus late in the pandemic. Methods: We invited oncology providers, including attendings, trainees and advanced practice providers, to complete a cross-sectional online survey using a variety of outreach methods including social media (Twitter), email contacts, word of mouth and provider list-serves. We surveyed providers at two time points during the pandemic when the number of COVID-19 cases was rising in the United States, early (March 2020) and late (January 2021). The survey responses were analyzed using descriptive statistics and Chi-squared tests to evaluate differences in early versus late provider responses. Results: A total of 132 providers completed the survey and most were white (n = 73/132, 55%) and younger than 49 years (n = 88/132, 67%). Respondents were attendings in medical, surgical or radiation oncology (n = 61/132, 46%), advanced practice providers (n = 48/132, 36%) and oncology fellows (n = 16/132, 12%) who predominantly practiced in an academic medical center (n = 120/132, 91%). The majority of providers agreed patients with cancer are at higher risk than other patients to be affected by COVID-19 (n = 121/132, 92%). However, there was a significant difference in the proportion of early versus late providers who thought delays in cancer care were needed. Early in the pandemic, providers were more likely to recommend delays in curative surgery or radiation for early-stage cancer (p < 0.001), delays in adjuvant chemotherapy after curative surgery (p = 0.002), or delays in surveillance imaging for metastatic cancer (p < 0.001). The majority of providers early in the pandemic responded that “reducing risk of a complication from a COVID-19 infection to patients with cancer” was the primary reason for recommending delays in care (n = 52/76, 68%). Late in the pandemic, however, providers were more likely to agree that “any practice change would have a negative impact on patient outcomes” (p = 0.003). At both time points, the majority of providers agreed with the need for other care delivery changes, including screening patients for infectious symptoms (n = 128/132, 98%) and the use of telemedicine (n = 114/132, 86%) during the pandemic. Conclusions: We found significant differences in provider perspectives of delays in cancer care early versus late in the pandemic which reflects the swiftly evolving oncology practice during the COVID-19 pandemic. Future studies are needed to determine the impact of changes in treatment and care delivery on outcomes for patients with cancer.

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