METHODS AND FINDINGS: Key electronic databases including Medline, Embase, Scopus, Global Health, CinAHL, EconLit and Business Source Premier were searched. We also searched the grey literature, specifically websites of leading organizations supporting health care in LMICs. Only studies using benefit incidence analysis (BIA) and/or financing incidence analysis (FIA) as explicit methodology were included. A total of 512 records were obtained from the various sources. The full texts of 87 references were assessed against the selection criteria and 24 were judged appropriate for inclusion. Twelve of the 24 studies originated from sub-Saharan Africa, nine from the Asia-Pacific region, two from Latin America and one from the Middle East. The evidence points to a pro-rich distribution of total health care benefits and progressive financing in both sub-Saharan Africa and Asia-Pacific. In the majority of cases, the distribution of benefits at the primary health care level favoured the poor while hospital level services benefit the better-off. A few Asian countries, namely Thailand, Malaysia and Sri Lanka, maintained a pro-poor distribution of health care benefits and progressive financing.
CONCLUSION: Studies evaluated in this systematic review indicate that health care financing in LMICs benefits the rich more than the poor but the burden of financing also falls more on the rich. There is some evidence that primary health care is pro-poor suggesting a greater investment in such services and removal of barriers to care can enhance equity. The results overall suggest that there are impediments to making health care more accessible to the poor and this must be addressed if universal health coverage is to be a reality.
METHODS: Data on patient costs were collected prospectively in the first year following diagnosis by using a self-administered questionnaire and telephone interviews at three time points for all four stages of colorectal cancer. The patient cost data consisted of direct out-of-pocket payments for medical-related expenses such as hospital stays, tests and treatment and for non-medical items such as travel and food associated with hospital visits. In addition, indirect cost data related to the loss of productivity of the patient and caregiver(s) was assessed. The patient's perceived level of financial difficulty and types of coping strategy were also explored.
RESULT: The total 1-year patient cost (both direct and indirect) increased with the stage of colorectal cancer: RM 6544.5 (USD 2045.1) for stage I, RM 7790.1 (USD 2434.4) for stage II, RM 8799.1 (USD 2749.7) for stage III and RM 8638.2 (USD 2699.4) for stage IV. The majority of patients perceived paying for their healthcare as somewhat difficult. The most frequently used financial coping strategy was a combination of current income and savings.
CONCLUSION: Despite the high subsidisation in public hospitals, the management of colorectal cancer imposes a substantial financial burden on patients and their families. Moreover, the majority of patients and their families perceive healthcare payments as difficult. Therefore, it is recommended that policy- and decision-makers should further consider some financial protection strategies and support for cancer treatment because cancer is a very costly and chronic disease.
METHODS: This study was designed in the form of cross-sectional analysis, in which, cancer survivors were recruited from the Sarawak General Hospital, the largest tertiary and referral public hospital in Sarawak. To capture the financial toxicity of the cancer survivors, the Comprehensive Score for Financial Toxicity (COST) instrument in its validated form was adopted. Multivariable logistic regression analysis was applied to determine the relationship between financial toxicity (FT) and its predictors.
RESULTS: The median age of the 461 cancer survivors was 56 while the median score of COST was 22.0. Besides, finding from multivariable logistic regression revealed that low income households (OR: 6.893, 95% CI, 3.109-15.281) were susceptible to higher risk of financial toxicity, while elderly survivors above 50 years old reported a lower risk in financial toxicity. Also, survivors with secondary schooling (OR:0.240; 95%CI, 0.110-0.519) and above [College or university (OR: 0.242; 95% CI, 0.090-0.646)] suffer a lower risk of FT.
CONCLUSION: Financial toxicity was found to be associated with survivors age, household income and educational level. In the context of cancer treatment within public health facility, younger survivors, households from B40 group and individual with educational attainment below the first level schooling in the Malaysian system of education are prone to greater financial toxicity. Therefore, it is crucial for healthcare policymakers and clinicians to deliberate the plausible risk of financial toxicity borne by the patient amidst the treatment process.
METHODS: A cross-sectional study was conducted at the National Heart Institute of Malaysia involving 503 patients who were hospitalized during the year prior to the survey.
RESULTS: The mean annual out-of-pocket health spending for IHD was MYR3045 (at the time US$761). Almost 16% (79/503) suffered from catastrophic health spending (out-of-pocket health spending ≥40% of household non-food expenditures), 29.2% (147/503) were unable to pay for medical bills, 25.0% (126/503) withdrew savings to help meet living expenses, 16.5% (83/503) reduced their monthly food consumption, 12.5% (63/503) were unable to pay utility bills and 9.0% (45/503) borrowed money to help meet living expenses.
CONCLUSIONS: Overall, the economic impact of IHD on patients in Malaysia was considerable and the prospect of economic hardship likely to persist over the years due to the long-standing nature of IHD. The findings highlight the need to evaluate the present health financing system in Malaysia and to expand its safety net coverage for vulnerable patients.
METHODS: A total of 429 respondents diagnosed with urologic cancers (prostate cancer, bladder and renal cancer) from Sarawak General Hospital and Subang Jaya Medical Centre in Malaysia were interviewed using a structured questionnaire. Objective and subjective FT were measured by catastrophic health expenditure (healthcare-cost-to-income ratio greater than 40%) and the Personal Financial Well-being Scale, respectively. HRQoL was measured with the Functional Assessment of Cancer Therapy - General 7 Items scale.
RESULTS: Objective and subjective FT were experienced by 16.1 and 47.3% of the respondents, respectively. Respondents who sought treatment at a private hospital and had out-of-pocket health expenditures were more likely to experience objective FT, after adjustment for covariates. Respondents who were female and had a monthly household income less than MYR 5000 were more likely to experience average to high subjective FT. Greater objective FT (OR = 2.75, 95% CI 1.09-6.95) and subjective FT (OR = 4.68, 95% CI 2.63-8.30) were associated with poor HRQoL.
CONCLUSIONS: The significant association between both objective and subjective FT and HRQoL highlights the importance of reducing FT among urologic cancer patients. Subjective FT was found to have a greater negative impact on HRQoL.
METHODS: A cost and outcome study was conducted using a retrospective cohort database from four tertiary hospitals. All patients with high-risk surgeries visiting the hospitals from 2011 to 2017 were included. Outcomes included major postsurgical complications, length of stay (LOS), in-hospital death, and total healthcare costs. Multivariate regression analyses were performed to identify risk factors of postsurgical outcomes.
RESULTS: A total of 14,930 patients were identified with an average age of 57.7 ± 17.0 years and 34.9% being male. Gastrointestinal (GI) procedures were the most common high-risk procedures, accounting for 54.9% of the patients, followed by cardiovascular (CV) procedures (25.2%). Approximately 27.2% of the patients experienced major postsurgical complications. The top three complications were respiratory failure (14.0%), renal failure (3.5%), and myocardial infarction (3.4%). In-hospital death was 10.0%. The median LOS was 9 days. The median total costs of all included patients were 2,592 US$(IQR: 1,399-6,168 US$). The patients, who received high-risk GI surgeries and experienced major complications, had significantly increased risk of in-hospital death (OR: 4.53; 95%CI: 3.81-5.38), longer LOS (6.53 days; 95%CI: 2.60-10.46 days) and higher median total costs (2,465 US$; 95%CI: 1,945-2,984 US$), compared to those without major complications. Besides, the patients, who underwent high-risk CV surgeries and developed major complications, resulted in significantly elevated risk of in-hospital death (OR: 2.22; 95%CI: 1.74-2.84) and increased median total costs (2,719 US$; 95%CI: 2,129-3,310 US$), compared to those without major complications.
CONCLUSIONS: Postsurgical complications are a serious problem in Thailand, as they are associated with worsening mortality risk, LOS, and healthcare costs. Clinicians should develop interventions to prevent or effectively treat postsurgical complications to mitigate such burdens.
OBJECTIVES: To evaluate the economic burden of treating cancer patients.
METHOD: Descriptive cross-sectional cost of illness study in the leading teaching and referral hospital in Kenya, with data collected from the hospital files of sampled adult patients for treatment during 2016.
RESULTS: In total, 412 patient files were reviewed, of which 63.4% (n = 261) were female and 36.6% (n = 151) male. The cost of cancer care is highly dependent on the modality. Most reviewed patients had surgery, chemotherapy and palliative care. The cost of cancer therapy varied with the type of cancer. Patients on chemotherapy alone cost an average of KES 138,207 (USD 1364.3); while those treated with surgery cost an average of KES 128,207 (1265.6), and those on radiotherapy KES 119,036 (1175.1). Some patients had a combination of all three, costing, on average, KES 333,462 (3291.8) per patient during the year.
CONCLUSION: The cost of cancer treatment in Kenya depends on the type of cancer, the modality, cost of medicines and the type of inpatient admission. The greatest contributors are currently the cost of medicines and inpatient admissions. This pilot study can inform future initiatives among the government as well as private and public insurance companies to increase available resources, and better allocate available resources, to more effectively treat patients with cancer in Kenya. The authors will be monitoring developments and conducting further research.
METHODS: Through the Association of Southeast Asian Nations Costs in Oncology study, 1,294 newly diagnosed patients with cancer (Ministry of Health [MOH] hospitals [n = 577], a public university hospital [n = 642], private hospitals [n = 75]) were observed in Malaysia. Cost diaries and questionnaires were used to measure incidence of financial toxicity, encompassing financial catastrophe (FC; out-of-pocket costs ≥ 30% of annual household income), medical impoverishment (decrease in household income from above the national poverty line to below that line after subtraction of cancer-related costs), and economic hardship (inability to make necessary household payments). Predictors of financial toxicity were determined using multivariable analyses.
RESULTS: One fifth of patients had private health insurance. Incidence of FC at 1 year was 51% (MOH hospitals, 33%; public university hospital, 65%; private hospitals, 72%). Thirty-three percent of households were impoverished at 1 year. Economic hardship was reported by 47% of families. Risk of FC attributed to conventional medical care alone was 18% (MOH hospitals, 5%; public university hospital, 24%; private hospitals, 67%). Inclusion of expenditures on nonmedical goods and services inflated the risk of financial toxicity in public hospitals. Low-income status, type of hospital, and lack of health insurance were strong predictors of FC.
CONCLUSION: Patients with cancer may not be fully protected against financial hardships, even in settings with universal health coverage. Nonmedical costs also contribute as important drivers of financial toxicity in these settings.