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In this new study, investigators sought to measure and attribute out-of-pocket costs to cancer stage and by diagnosis.
Although much is known of cancer diagnoses and the related financial implications among an older patient population, especially those with Medicare coverage, far less is known of how the finances of younger patients (< 65 years) with private insurance are affected following a new cancer diagnosis—especially their out-of-pocket (OOP) costs.
Data published online today in JAMA Network Open show that patients with an incident diagnosis of breast, colorectal, or lung cancer are responsible for having to pay more than $3500 OOP in the first 6 months following diagnosis, and this total only rises with an advanced-stage diagnosis.1 The study authors attribute this to higher-stage diseases requiring more therapies. Using US administrative claims data from the Surveillance, Epidemiology, and End Results cancer registry, they measured these costs among a cohort of 46,158 patients, of whom 19,656 had cancer and 26,502 made up the control group. Of the patients with cancer, the most common was breast cancer (n = 14,581), followed by colorectal cancer (n = 2842) and lung cancer (n = 2233) cancer. Their mean (SD) overall age was 46 (12) years, 66.6% were female patients, 67.4% were non-Hispanic White race/ethnicity, 31.8% were enrolled in a high-deductible health plan, and the most common annual household incomes were $75,000 to $124,999 (23.9%); $40,000 to $74,999 (18.0%); and less than $40,000 (10.5%).
“Several obstacles have made estimating OOP [costs] associated with specific cancer diagnoses difficult in the privately insured US adult population,” the study authors wrote, pointing to inadequate survey-based datasets, claims databases, and inconsistent staging information. “A link between claims and clinical data is necessary to identify patient populations most at risk for high OOP [costs]. While the linkage between Medicare claims records and [Surveillance, Epidemiology, and End Results] data has been explored, such linkages have remained elusive for the privately insured population.”
According to the National Cancer Institute, female breast cancer, colorectal cancer, and lung cancer incur the highest national medical costs, and female breast cancer and lung cancer have the highest oral prescription drug costs.2 In 2020 alone for breast cancer, projected total annual medical costs topped $29.8 billion.3
Overall, the patients with cancer were older, at ages 52 to 57 years vs 42 years for the control cohort, and they had more comorbidities. Per the Elixhauser Comorbidity Index, patients with breast cancer had at least 1 comorbidity (P < .001), patients with lung cancer had at least 2 (P < .001), and patients with colorectal cancer, 1 (P = .002).
For this analysis, stage at diagnosis ranged from 0 to IV for breast cancer and I to IV for lung and colorectal cancers. Significant differences were not seen in monthly OOP costs before diagnosis, but the authors saw a spike for all 3 cancers in the month of diagnosis and noted OOP costs remained higher for the patients with cancer vs the patients not diagnosed for at least 6 months after diagnosis.
In the first 6 months after diagnosis, patients with cancer paid higher monthly OOP amounts vs patients who did not have cancer, and these ranged from $462.01 with stage 0 disease to $719.97 with stage IV disease. | Image Credit: Maggie-sort.chatgpt.com
Drilling down to each cancer type, these were the mean OOP costs:
By stage, per estimated difference-in-differences (DID) OOP changes in the first 6 months after diagnosis, patients with cancer paid the following higher monthly OOP amounts vs patients who did not have cancer:
The authors note that these differences “underscore the financial burden of cancer care on patients with insurance who are not yet eligible for Medicare.” They also underscore the pervasiveness of financial toxicity—which currently affects even cancer survivors—and its negative impact on quality of life and health care access after diagnosis.4 TT
“Our understanding of this phenomenon among individuals enrolled in Medicare is relatively thorough. However, our understanding of financial toxicity outside of the Medicare population is relatively poor,” they conclude. “Along with data sparsity, there is vast variation in health insurance plans available to individuals and households, contributing to substantial heterogeneity what costs a patient may have after diagnosis.”
They suggest there is a great need for better patient-focused policies that consider both insurance continuity and financial assistance. However, their findings are limited by their DID approach, potential for differential attrition (loss of insurance coverage), and lack of data on reasons for dropping insurance and all-payer claims. They also did not include indirect costs, such as travel and lost wages, which they noted fall outside of the accepted definition of OOP costs.
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