Out-of-pocket payment and financial risk protection for breast cancer treatment: a prospective study from India

Background

Available data on cost of cancer treatment, out-of-pocket payment and reimbursement are limited in India. We estimated the treatment costs, out-of-pocket payment, and reimbursement in a cohort of breast cancer patients who sought treatment at a publicly funded tertiary cancer care hospital in India.

Methods

A prospective longitudinal study was conducted from June 2019 to March 2022 at Tata Memorial Centre (TMC), Mumbai. Data on expenditure during each visit of treatment was collected by a team of trained medical social workers. The primary outcome variables were total cost (TC) of treatment, out-of-pocket payment (OOP), and reimbursement. TC included cost incurred by breast cancer patients during treatment at TMC. OOP was defined as the total cost incurred at TMC less of reimbursement. Reimbursement was any form of financial assistance (cashless or repayment), including social health insurance, private health insurance, employee health schemes, and assistance from charitable trusts, received by the patients for breast cancer treatment.

Findings

Of the 500 patients included in the study, 45 discontinued treatment (due to financial or other reasons) and 26 died during treatment. The mean TC of breast cancer treatment was ₹258,095/US$3531 (95% CI: 238,225, 277,934). Direct medical cost (MC) accounted for 56.3% of the TC. Systemic therapy costs (₹50,869/US$696) were higher than radiotherapy (₹33,483/US$458) and surgery costs (₹25,075/US$343). About 74.4% patients availed some form of financial assistance at TMC; 8% patients received full reimbursement. The mean OOP for breast cancer treatment was ₹186,461/US$2551 (95% CI: 167,666, 205,257), accounting for 72.2% of the TC. Social health insurance (SHI) had a reasonable coverage (33.1%), followed by charitable trusts (29.6%), employee health insurance (5.1%), private health insurance (4.4%) and 25.6% had no reimbursement. But SHI covered only 40.1% of the TC of treatment compared to private health insurance that covered as much as 57.1% of it. Both TC and OOP were higher for patients who were younger, belonged to rural areas, had a comorbidity, were diagnosed at an advanced stage, and were from outside Maharashtra.

Interpretation

In India, the cost and OOP for breast cancer treatment are high and reimbursement for the treatment flows from multiple sources. Though many of the patients receive some form of reimbursement, it is insufficient to prevent high OOP. Hence both wider insurance coverage as well as higher cap of the insurance packages in the health insurance schemes is suggested. Allowing for the automatic inclusion of cancer treatment in SHI can mitigate the financial burden of cancer patients in India.

Funding

This work was funded by an extramural grant from the Women's Cancer Initiative and the Nag Foundation and an intramural grant from the International Institute of Population Sciences, Mumbai.

Health care costs for adolescents and young adults with cancer: a Wisconsin community-based hospital study between 2005 and 2020

INTRODUCTION

Adolescents and young adults (AYA) with cancer are at risk of high cumulative healthcare system costs potentially associated with poor health and financial outcomes. Although this has been studied at academic centers, little data on AYA costs at community-based practices exist. The goals of this study were to understand direct health care costs for AYA patients, identify factors for high costs, and assess how total health care costs may relate to survival.

METHODS

AYA patients (15-39 years) treated at a community hospital in Wisconsin (USA) between 2005 and 2020 were identified. Patient demographics, cancer characteristics, therapies, support services, and all direct health care charges (including up to 1 year prior to diagnosis to capture any diagnostic workup) were collected. Logistic and Cox proportional hazard regression models identified factors associated with high costs and survival, respectively.

RESULTS

The 388 AYA patients had a median follow-up of 9 years (97% survival). Most were 30-39 years (62%), female (61%), white (95%), diagnosed early-stage (85%), and underwent surgery (83%). Complete health care costs were available for 233 patients (60%). Median total costs per patient were $123 K (range, $73-$215 K). On adjusted analysis, higher direct health care costs (> $125 K) were associated with greater odds of hospital admissions (odds ratio [OR] = 1.7, 95% CI = 1.35-2.27), chemotherapy (OR = 4.1, 95% CI = 1.44-12.70), and breast cancer diagnosis (OR = 3.8, 95% CI = 1.07-14.70). Living farther from the hospital (OR = 0.1, 95% CI = 0.02-0.50), later year of diagnosis (OR = 0.7, 95% CI = 0.55-0.77), and uninsured/unknown insurance status (OR = 0.1, 95% CI = 0.01-0.57) were associated with decreased odds of having higher health care costs. On adjusted analysis, death was associated with greater odds of higher direct health care costs per $125 K (hazards ratio [HR] = 7.9, 95% CI = 2.22-27.80) and radiation (HR = 31.8, 95% CI = 3.15-321) but lower odds of hormone therapy (HR = 0.1, 95% CI = 0.01-0.72) and later year of diagnosis (HR = 0.3, 95% CI = 0.12-0.60).

CONCLUSION

High direct health care costs among AYA patients are associated with hospital admissions, chemotherapy, breast cancer diagnosis, hospital proximity, and earlier year of diagnosis. Death was associated with high direct health care costs, earlier years of diagnosis, and radiation therapy. Total health care costs in community-based hospitals should be considered in the context of AYA patients with cancer.

Men receive more end-of-life cancer hospital treatment than women: fact or fiction?

BACKGROUND

An important goal of health care systems is equitable access to health care. Previous research, however, indicates that men receive more cancer care and health care resources than women. The aim of this study was to investigate whether there is a gender difference in terms of end-of-life cancer treatment in hospitals in Norway.

MATERIAL AND METHODS

We used nationwide patient-level data from the Norwegian Patient Registry (2013-2017, n = 64,694), and aggregated data from the Norwegian Cause of Death Registry (2013-2018, n = 66,534). We described direct medical costs and utilization of cancer treatment in hospitals (in-patient stays and out-patient clinics) and specialized palliative home care teams by the means of the following variables: gender, type of cancer, age, region of residence, place of death, and use of pharmaceutical anti-cancer treatment last month before death. Generalized linear models with a gamma distribution and log-link function were fitted to identify determinants of direct medical costs in hospital's last year of life.

RESULTS

Women aged 0-69 years had an average direct medical cost in hospitals of €26,117 during the last year of life, compared to €29,540 for men, while they were respectively €19,889 and €22,405 for those aged 70 years or older. These gender differences were confirmed in regression models with gender as the only covariate. Adjusted additionally for the type of cancer, the difference was 11%, while including age as a covariate reduced the difference to 6%. When the place of death was also included, the difference was down to 4%.

DISCUSSION

The gender difference in hospital costs last year of life can largely be explained by age at death and the proportion dying in hospitals. When adjusting for confounding factors, the differences in end-of-life costs in hospitals are minimal.

A population-level comparison of cancer-related and non-cancer-related health care costs using publicly available provincial administrative data

Introduction

Costs associated with cancer care are increasing. Cancer costs in the context of other common non-cancer diagnoses have not been extensively studied at the population level. Knowledge from such analyses can inform health care resource allocation and highlight strategies to reduce overall costs.

Methods

Using cross-sectional data from publicly available population-level administrative data sources (health insurance claims, physician billing, and hospital discharge abstracts), we calculated incidence-adjusted health care costs (in 2014 Canadian dollars) for cancers and common non-cancer diagnoses in the adult population in a large Canadian province. Subgroup analyses were also performed for various provincial health administrative regions.

Results

Total costs related to cancer care amounted to $495 million for the province, of which at least $67 million (14%) was attributable to radiation and chemotherapy. Of the various cancer subtypes, hematologic malignancies were most costly at $70 million, accounting for 14% of the total cancer budget. Colon cancer followed at $51 million (10%), and lung cancer, at $44 million (9%). Cancer costs (with and without costs for radiation and chemotherapy) exceeded those for cardiovascular disease, diabetes mellitus, mental health, and trauma (p < 0.001). In addition, the costs of specific cancer subtypes varied by region, but hematologic and lung cancers were typically the most costly no matter the health region.

Conclusions

Using provincial administrative data to establish cost trends can help to inform health care allocation and budget decisions, and can facilitate comparisons between provinces.

Expanding the Scope of Evidence-Based Cancer Care

This article explores how oncology research can be expanded to ensure that research spending results in maximum benefit. The focus has shifted to the value and quality of care, which view cancer care with the perspective of the patient at the center and cover the spectrum of care. Because there is no agreed-upon definition for value in cancer care, we overview various contributions to defining value and quality in oncology. We outline how cancer care costs are measured in the United States and explore outcome measures that have been proposed and implemented to enable us to assess value in oncology.

Can Centralization of Cancer Surgery Improve Social Welfare?

The empirical association between high hospital procedure volume and lower mortality rates has led to recommendations for the centralization of complex surgical procedures. Yet redirecting patients to a select number of high-volume hospitals creates potential negative consequences for market competition. We use patient-level data to estimate the association between hospital procedure volume and patient mortality and costs. We also estimate the association between hospital market concentration and mortality, cost, and prices. We use our estimates to simulate the change in social welfare resulting from redirecting patients at low-volume hospitals to high-volume facilities. We find that a higher procedure volume leads to significant reductions in mortality for patients undergoing surgery for pancreatic cancer, but not colon cancer. Procedure volume also influences costs for both surgeries, but in a nonlinear fashion. Increased market concentration is associated with higher costs and prices for colon cancer, but not pancreatic cancer patients. Simulations indicated that centralizing pancreatic cancer surgery is unambiguously welfare enhancing. In contrast, there is less evidence to suggest that centralizing colon cancer surgery would be welfare improving.

Cost disparities in lung cancer treatment by disability status, sex, and race

BACKGROUND

The recent literature contains numerous reports of disparities in the diagnosis, treatment, and outcomes of lung cancer across a growing list of population subgroups, including disability status. A common assumption is that disparities stem mainly from variations in the level and type of treatment resources available to specific subgroups. Few studies, however, have directly measured resource differentials. Since policy makers identify reducing health disparities as a critical priority, this study examined whether cumulative Medicare costs (resource consumption) for lung cancer treatment differ across eight patient subgroups defined by disability status, sex, and race.

HYPOTHESIS

Treatment disparities across the eight subgroups will be reflected in variations in the cumulative cost profiles of those subgroups, controlling for other plausible cost drivers. Failure to detect statistically significant differentials in these cost profiles implies that treatment disparities stem from factors other than access to, and utilization of, health care services.

METHODS

Linked SEER-Medicare data were used to construct cost profiles by service type and treatment phase for roughly 80,000 incident lung cancer cases in patients aged 45 to 85 years at diagnosis. Multiple regression models then tested for cost differentials across the eight subgroups, controlling for various patient and disease characteristics.

RESULTS

Significant cost differentials were detected, some unanticipated. Women tended to have higher treatment costs than men; they also had more favorable survivals. Nonwhites also tended to have higher treatment costs than whites, although they had significantly shorter survivals. On average, men with disabilities consumed the fewest treatment resources and had the shortest survivals. Mixed results were obtained for women with disabilities.

CONCLUSIONS

Among others, the findings suggest that reducing disparities will take more than just improving access to health care. Special attention must be paid to lung cancer patients with disabilities by both policy makers and clinicians.