scholarly journals Patient and family financial burden associated with cancer treatment in Canada: a national study

2021 ◽  
Author(s):  
Christopher J. Longo ◽  
Margaret I. Fitch ◽  
Jonathan M. Loree ◽  
Linda E. Carlson ◽  
Donna Turner ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Financial Burden ◽  
Family Care ◽  
Indirect Costs ◽  
National Study ◽  
Patients With Cancer ◽  
Alternative Medicines ◽  
Patient Reported ◽  
Household Incomes ◽  
Self Administered Questionnaire

Abstract Goal To determine patient-reported financial and family burden associated with treatment of cancer in the previous 28 days across Canada. Methods A self-administered questionnaire (P-SAFE v7.2.4) was completed by 901 patients with cancer from twenty cancer centres nationally (344 breast, 183 colorectal, 158 lung, 216 prostate) measuring direct and indirect costs related to cancer treatment and foregone care. Monthly self-reported out-of-pocket-costs (OOPCs) included drugs, homecare, homemaking, complementary/ alternative medicines, vitamins/supplements, family care, accommodations, devices, and “other” costs. Travel and parking costs were captured separately. Patients indicated if OOPC, travel, parking, and lost income were a financial burden. Results Mean 28-day OOPCs were CA$518 (US Purchase Price Parity [PPP] $416), plus CA$179 (US PPP $144) for travel and CA$84 (US PPP $67) for parking. Patients self-reporting high financial burden had total OOPCs (33%), of CA$961 (US PPP $772), while low-burden participants (66%) had OOPCs of CA$300 (US PPP $241). “Worst burden” respondents spent a mean of 50.7% of their monthly income on OOPCs (median 20.8%). Among the 29.4% who took time off work, patients averaged 18.0 days off. Among the 26.0% of patients whose caregivers took time off work, caregivers averaged 11.5 days off. Lastly, 41% of all patients had to reduce spending. Fifty-two per cent of those who reduced spending were families earning < CA$50,000/year. Conclusions In our Canadian sample, high levels of financial burden exist for 33% of patients, and the severity of burden is higher for those with lower household incomes.

scholarly journals Burden of Treatment Among Elderly Patients with Cancer: A Scoping Review

Healthcare ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 612
Author(s):  
Adem Sav ◽  
Sara S. McMillan ◽  
Adeola Akosile
Keyword(s):  
Elderly Patients ◽  
Cancer Treatment ◽  
Scoping Review ◽  
Financial Burden ◽  
Significant Proportion ◽  
Indirect Costs ◽  
The United States ◽  
Treatment Burden ◽  
Cross Sectional ◽  
Patients With Cancer

Background: The objective of this scoping review is to understand how treatment burden is experienced in elderly patients with cancer and what the most prevalent dimensions of treatment burden are among this population. According to one conceptual model, there are six dimensions of treatment burden, including financial, medication, administrative, time/travel, lifestyle, and healthcare. Methods: A scoping review methodology framework was used to collected data from EMBASE CINAHL (Cumulative Index to Nursing and Allied Health Literature), Medline/PubMed, Scopus, Web of Science, Embase, and Cochrane from 2000 to March 2020. Studies which focused on treatment burden among elderly patients with cancer (+65 years) were selected. Data were extracted using a standardized proforma. Results: The results identified 3319 total papers. Of these, 24 met the inclusion criteria and were included in the scoping review. A significant proportion of these studies was conducted in the United States (n = 10) using self-reported, cross-sectional data. Financial burden was the most prevalent dimension of treatment burden, with 11 studies focusing on the direct and indirect costs associated with cancer treatment. Other but less obvious aspects of treatment burden elderly patients experienced included the length of time taken to access and administer treatment and medication-related burdens. Conclusion: Emerging findings suggest that the financial aspects of cancer treatment are a significant burden for most elderly cancer patients. Personalized healthcare interventions targeting ways to reduce and screen for treatment burden, particularly those related to cost, are urgently needed.

Predictors of high financial distress in a national, multiethnic sample of patients with cancer.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 149-149
Author(s):  
Meera Vimala Ragavan ◽  
Rosie Cunningham ◽  
Andrea Incudine ◽  
Hala Borno ◽  
Thomas Stivers
Keyword(s):  
Cancer Treatment ◽  
Financial Distress ◽  
Financial Support ◽  
Financial Stress ◽  
The United States ◽  
Financial Assistance ◽  
Financial Toxicity ◽  
Targeted Interventions ◽  
Patients With Cancer ◽  
Patient Reported

149 Background: Financial toxicity is characterized by financial burden that patients face. Patients and providers are seldom aware of available resource to help mitigate this growing problem. To date, our understanding of the myriad of financial repercussions of cancer treatment remains limited. Prior published research has largely been single center, thereby limiting generalizability across the United States. This study leveraged a national, multi-ethnic sample of patients who receive financial support services including comprehensive financial assistance, navigation, planning, and a guidebook with relevant resources from a non-profit entity (Family Reach) to evaluate financial stress in during cancer treatment. Methods: Patients were identified for study participation if they received at least one financial support resource from Family Reach between 1/1/2020-6/30/2020. An 11-item survey was sent electronically to all eligible participants who were given a one-month time frame to complete. A multivariate model was employed to identify sociodemographic predictors of high financial distress. Results: A total of 832 patients were contacted, of whom 330 (40%) completed the survey. Demographic information is included in table. Patient reported financial distress in the prior week was high, with 46% of patients reporting a distress level of seven or higher on a ten-point scale. In a multivariate regression, Hispanic/Latinx ethnicity was associated with a higher distress rating and higher patient reported financial stress. Lower annual household income was associated with lower reports of feeling in financial control, lower reports of meeting monthly expenses, and higher reports of financial stress. Conclusions: Patient-reported financial distress was high in a national sample of patients with cancer who had utilized at least one financial resource provided by Family Reach. Hispanic ethnicity and Lower Annual Income were predictors of higher patient-reported financial distress. Larger samples are needed to confirm these patterns. Delivery systems should develop targeted interventions, including referrals to organizations providing financial assistance, for patient populations at high risk for financial toxicity. [Table: see text]

Financial Toxicity in Cancer Treatment

2021 ◽  
pp. 616-620
Author(s):  
Victoria Blinder ◽  
Francesca M. Gany
Keyword(s):  
Cancer Treatment ◽  
Emotional Distress ◽  
Low Income ◽  
Financial Distress ◽  
Financial Burden ◽  
Symptom Burden ◽  
Indirect Costs ◽  
Young Female ◽  
Vulnerable Groups ◽  
Financial Toxicity

Financial toxicity is a preventable cancer treatment side effect, encompassing the subjective financial distress and objective financial burden that result from increased spending and decreased earning after diagnosis. The prevalence of financial toxicity has increased with new expensive cancer treatments and insurers gradually shifting costs to patients. Patients with financial toxicity experience increased symptom burden, treatment nonadherence, and cancer-related death. The patients at highest risk are young, female, and nonwhite. For low-income patients, the indirect costs of cancer care can be especially burdensome and include child/elder care, transportation, unpaid work absences or job loss, cancer-related comorbidity treatment costs, and fulfilling dietary requirements. Psychosocial impacts include depression, emotional distress, and reduced quality of life. Patients in palliative care have rated financial distress as more severe than physical, familial, and emotional distress. Interventions and policy changes are needed to ameliorate the effects of financial toxicity, especially for the most vulnerable groups.

scholarly journals Catastrophic Healthcare Expenditure and Coping Strategies among Patients Attending Cancer Treatment Services in Addis Ababa, Ethiopia

2019 ◽  
Author(s):  
Gebremicheal Gebreslassie Kasahun ◽  
Gebremedhin Beedemariam Gebretekle ◽  
Yohannes Hailemichael Gecho ◽  
Aynalem Abraha Woldemariam ◽  
Teferi Gedif Fenta
Keyword(s):  
Cancer Treatment ◽  
Coping Strategies ◽  
Addis Ababa ◽  
Financial Burden ◽  
Public Hospitals ◽  
Medical Expenditure ◽  
Patients With Cancer ◽  
Treatment Services ◽  
Number Of Patients ◽  
And Coping

Abstract Background: With the rapid increase in magnitude and mortality of cancer, which is costly disease to manage, several patients particularly in developing countries are facing a huge financial burden. Objective: The purpose of the study was to examine the level of catastrophic health expenditure (CHE), identify associated factors and coping strategies among patients attending cancer treatment services in Addis Ababa, Ethiopia. Methods: A hospital based cross-sectional survey of patients with cancer was conducted in public and private hospitals between January and March 2018. Data was collected using a structured questionnaire. All direct medical and nonmedical expenditures were measured and reported as expenditure (US$) per patient (1US$ equivalent to 23.41 Ethiopian Birr). The CHE was estimated using a threshold of 10% of annual household income. Results: A total of 352 (response rate of 87.1%) participants were interviewed. Majority (73.3%) of the respondents were females; most (94%) from public hospitals and their mean (±SD) age was 48±13.2years. Breast (37%) and Cervical (16.5%) cancers accounted the largest proportion. Vast majority (74.4%) of patients experienced CHE with mean overall expenditure of $2366 per patient (median: $1708). Medical expenditure shared the highest overall expenditure (83.6%) with mean medical and nonmedical costs of $1978 (median: $1394) and $388 (median: $222), respectively. Patients who took greater than six cycles of chemotherapy (AOR: 3.64; 95%CI: 1.11-11.92), and age (AOR: 1.03; 95%CI: 1.01-1.06) were significantly associated with CHE. Household saving (85.5%) followed by financial support (43.0%) were the main coping strategies. Conclusion: A substantial number of patients with cancer are exposed to CHE with considerable medical expenditure. Hence, mobilizing the health insurance scheme is urgently needed to ensure financial risk protection and realize universal health coverage for patients with cancer.

scholarly journals Development of Machine Learning Algorithms for the Prediction of Financial Toxicity in Localized Breast Cancer Following Surgical Treatment

2021 ◽  
pp. 338-347
Author(s):  
Chris Sidey-Gibbons ◽  
André Pfob ◽  
Malke Asaad ◽  
Stefanos Boukovalas ◽  
Yu-Li Lin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Treatment ◽  
Linear Model ◽  
Financial Burden ◽  
Breast Cancer Treatment ◽  
Support Vector ◽  
Financial Toxicity ◽  
Operating Characteristics ◽  
Patient Reported

PURPOSE Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but identification of need is difficult. We sought to develop and test a tool to accurately predict an individual's risk of financial toxicity based on clinical, demographic, and patient-reported data prior to initiation of breast cancer treatment. PATIENTS AND METHODS We surveyed 611 patients undergoing breast cancer therapy at MD Anderson Cancer Center. We collected data using the validated COmprehensive Score for financial Toxicity (COST) patient-reported outcome measure alongside other financial indicators (credit score, income, and insurance status). We also collected clinical and perioperative data. We trained and tested an ensemble of machine learning (ML) algorithms (neural network, regularized linear model, support vector machines, and a classification tree) to predict financial toxicity. Data were randomly partitioned into training and test samples (2:1 ratio). Predictive performance was assessed using area-under-the-receiver-operating-characteristics-curve (AUROC), accuracy, sensitivity, and specificity. RESULTS In our test sample (N = 203), 48 of 203 women (23.6%) reported significant financial burden. The algorithm ensemble performed well to predict financial burden with an AUROC of 0.85, accuracy of 0.82, sensitivity of 0.85, and specificity of 0.81. Key clinical predictors of financial burden from the linear model were neoadjuvant therapy (βregularized, .11) and autologous, rather than implant-based, reconstruction (βregularized, .06). Notably, radiation and clinical tumor stage had no effect on financial burden. CONCLUSION ML models accurately predicted financial toxicity related to breast cancer treatment. These predictions may inform decision making and care planning to avoid financial distress during cancer treatment or enable targeted financial support. Further research is warranted to validate this tool and assess applicability for other types of cancer.

scholarly journals Correction to: Patient and family financial burden associated with cancer treatment in Canada: a national study

2021 ◽  
Author(s):  
Christopher J. Longo ◽  
Margaret I. Fitch ◽  
Jonathan M. Loree ◽  
Linda E. Carlson ◽  
Donna Turner ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Financial Burden ◽  
National Study

scholarly journals Financial Burdens of Cancer Treatment: A Systematic Review of Risk Factors and Outcomes

2019 ◽  
Vol 17 (10) ◽  
pp. 1184-1192 ◽  
Author(s):  
Grace L. Smith ◽  
Maria A. Lopez-Olivo ◽  
Pragati G. Advani ◽  
Matthew S. Ning ◽  
Yimin Geng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Insurance ◽  
Cancer Treatment ◽  
Financial Burden ◽  
Cochrane Library ◽  
Random Effects Models ◽  
Patients With Cancer ◽  
Related Quality ◽  
Financial Burdens ◽  
Cancer Experience

Background: Patients with cancer experience financial toxicity from the costs of treatment, as well as material and psychologic stress related to this burden. A synthesized understanding of predictors and outcomes of the financial burdens associated with cancer care is needed to underpin strategic responses in oncology care. This study systematically reviewed risk factors and outcomes associated with financial burdens related to cancer treatment. Methods: MEDLINE, Embase, PubMed, PsychINFO, and the Cochrane Library were searched from study inception through June 2018, and reference lists were scanned from studies of patient-level predictors and outcomes of financial burdens in US patients with cancer (aged ≥18 years). Two reviewers conducted screening, abstraction, and quality assessment. Variables associated with financial burdens were synthesized. When possible, pooled estimates of associations were calculated using random-effects models. Results: A total of 74 observational studies of financial burdens in 598,751 patients with cancer were identified, among which 49% of patients reported material or psychologic financial burdens (95% CI, 41%–56%). Socioeconomic predictors of worse financial burdens with treatment were lack of health insurance, lower income, unemployment, and younger age at cancer diagnosis. Compared with patients with health insurance, those who were uninsured demonstrated twice the odds of financial burdens (pooled odds ratio [OR], 2.09; 95% CI, 1.33–3.30). Financial burdens were most severe early in cancer treatment, did not differ by disease site, and were associated with worse health-related quality of life (HRQoL) and nearly twice the odds of cancer medication nonadherence (pooled OR, 1.70; 95% CI, 1.13–2.56). Only a single study demonstrated an association with increased mortality. Studies assessing the comparative effectiveness of interventions to mitigate financial burdens in patients with cancer were lacking. Conclusions: Evidence showed that financial burdens are common, disproportionately impacting younger and socioeconomically disadvantaged patients with cancer, across disease sites, and are associated with worse treatment adherence and HRQoL. Available evidence helped identify vulnerable patients needing oncology provider engagement and response, but evidence is critically needed on the effectiveness of interventions designed to mitigate financial burden and impact.

scholarly journals Household Financial Burden and Poverty Impacts of Cancer Treatment in Vietnam

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Van Minh Hoang ◽  
Cam Phuong Pham ◽  
Quynh Mai Vu ◽  
Thuy Trang Ngo ◽  
Dinh Ha Tran ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Older Patients ◽  
Financial Burden ◽  
National Income ◽  
Indirect Costs ◽  
Vulnerable Groups ◽  
Catastrophic Expenditure ◽  
Direct And Indirect Costs ◽  
Individual Interviews ◽  
Multiple Treatments

Purpose. This paper aims to analyze the household financial burden and poverty impacts of cancer treatment in Vietnam. Methods. Under the “ASEAN CosTs in ONcology” study design, three major specialized cancer hospitals were employed to assemble the Vietnamese data. Factors of socioeconomic, direct, and indirect costs of healthcare were collected prospectively through both individual interviews and hospital financial records. Results. The rates of catastrophic expenditure based on the cut-off points of 20%, 30%, 40%, and 50% of household’s income were 82.6%, 73.7%, 64.7%, and 56.9%, respectively. 37.4% of the households with patient were impoverished by the treatment costs for cancer. The statistically significant correlates of the impoverishment problem were higher among older patients (40–60 years: 1.77, 95% CI 1.14–2.73; above 60 years: 1.75, 95% CI 1.03–2.98); poorer patients (less than 100% national income: 29, 95% CI 18.6–45.24; less than 200% national income: 2.89, 95% CI 1.69–4.93); patients who underwent surgery alone (receiving nonsurgery treatment: 2.46, 95% CI 1.32–4.59; receiving multiple treatments: 2.4, 95% CI 1.38–4.17). Conclusions. Lots of households were pushed into poverty due to their expenditure on cancer care; more actions are urgently needed to improve financial protection to the vulnerable groups.

Machine learning algorithms to predict financial toxicity associated with breast cancer treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 2047-2047 ◽  
Author(s):  
Chris Sidey-Gibbons ◽  
Malke Asaad ◽  
André Pfob ◽  
Stefanos Boukovalas ◽  
Yu-Li Lin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Decision Making ◽  
Cancer Treatment ◽  
Financial Burden ◽  
Breast Cancer Treatment ◽  
Support Vector ◽  
Financial Toxicity ◽  
Operating Characteristics ◽  
Patient Reported

2047 Background: Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but objective identification of individuals in need is difficult. Accurate predictions of an individual’s risk of financial toxicity prior to initiation of breast cancer treatment may facilitate informed clinical decision making, reduce financial burden, and improve patient outcomes. Methods: We retrospectively surveyed 611 patients who had undergone breast cancer therapy at MD Anderson Cancer Center to assess the financial impact of their care. All patients were over 18 and received either a lumpectomy or a mastectomy. We collected data using the FACT-COST patient-reported outcome measures alongside other financial indicators including income and insurance status. We extracted clinical and perioperative data from the electronic health record. Missing data were imputed using multiple imputation. We used this data to train and validate a neural network, LASSO-regularized linear model, and support vector machines. Data were randomly partitioned into training and validation samples (3:1 ratio). Analyses were informed by international PROBAST recommendations for developing multivariate predictors. We combined algorithms into a voting ensemble and assessed predictive performance using area under the receiver operating characteristics curve (AUROC), accuracy, sensitivity, and specificity. Results: In our validation sample, 48 of 203 (23.6%) women reported FACT-COST scores commensurate with significant financial burden. The algorithm predicted significant financial burden relating to cancer treatment with high accuracy (Accuracy = .83, AUROC = .82, sensitivity = .81, specificity = .82). Key clinical predictors of financial burden from linear models were neo-adjuvant therapy (βregularized 0.12) and autologous, rather than implant-based, reconstruction (βregularized 0.10). Conclusions: Machine learning models were able to accurately predict the occurrence of financial toxicity related to breast cancer treatment. These predictions may be used to inform decision making and care planning to avoid financial distress during cancer treatment or to enable targeted financial support for individuals. Further research is warranted to further improve this tool and assess applicability for other types of cancer.

Patient-reported benefit from proposed interventions to reduce financial hardship during cancer treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 7080-7080
Author(s):  
Emeline Aviki ◽  
Fumiko Chino ◽  
Julia Ramirez ◽  
Victoria Susana Blinder ◽  
Jennifer Jean Mueller ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Cancer Patients ◽  
Financial Burden ◽  
Gynecologic Cancer ◽  
Financial Hardship ◽  
Care Providers ◽  
Financial Toxicity ◽  
The Past ◽  
Patient Reported ◽  
The Impact

7080 Background: Awareness of cancer patients’ financial toxicity (FT) has increased substantially over the past decade; however, interventions to minimize financial burden remain underdeveloped and understudied. This survey-based study explores patient beliefs on which potential mitigating strategies could improve their financial hardship during cancer treatment. Methods: Interviewer-administered surveys were conducted with consecutive patients in an outpatient, urban, private academic Gynecologic Cancer clinic waiting room for 2 weeks in August 2019. The survey items included patient demographics, disease characteristics, the Comprehensive Score for Financial Toxicity (COST) tool (validated measure of FT with score 0-44; lower scores indicate worse FT), assessment of cost-coping strategies, and patient-reported anticipated benefit from described potential interventions (items that were feasible and relevant to implement in clinic). Results: Of 101 patients who initiated the survey, 87 (86%) completed it and were included in this analysis. The median age was 66 (range, 32-87). Thirty-eight patients (44%) had ovarian, 29 (33%) uterine, 5 (6%) cervical, and 15 (17%) an “other” gynecologic cancer. The median COST score was 32 (range, 6-44). Twenty-nine patients (33%) had COST scores ≤25 and 16 (18%) had COST scores ≤18. The most frequent cost-coping strategy reported was reducing leisure activities (n = 36, 41%) and using savings to pay for medical bills (n = 34, 39%). Six patients (7%) reported not taking a prescribed medication in the past 12 months due to the inability to pay and 0 reported skipping a recommended imaging study. When it came to interventions patients anticipated would improve their current financial hardships, 34 (39%) indicated access to transportation assistance to and from appointments, 31 (36%) said “knowing up front how much I’m going to have to pay for my healthcare”, 29 (33%) indicated “minimizing wait time associated with appointments, which keeps me away from work”, and 22 (25%) indicated “access to free food during/around appointments and treatments”. Only 26 (30%) noted they were not experiencing financial hardship. Conclusions: For an outpatient population of gynecologic cancer patients, several focused, feasible interventions could be implemented to potentially decrease patient FT. Our study can help health care providers in the design of interventions to create meaningful improvements in patient financial burden. Next steps should assess the impact of targeted interventions on patient outcomes.

Sign in / Sign up

Export Citation Format

Share Document