Methods: Fifteen countries of SA and SEA categorized as HE and LE, represented by the representatives of the national nephrology societies, participated in this questionnaire and interview-based assessment of the impact of economic status on renal care.
Results: Average incidence and prevalence of end-stage kidney disease (ESKD) per million population (pmp) are 1.8 times and 3.3 times higher in HE. Hemodialysis is the main renal replacement therapy (RRT) (HE-68%, LE-63%). Funding of dialysis in HE is mainly by state (65%) or insurance bodies (30%); out of pocket expenses (OOPE) are high in LE (41%). Highest cost for hemodialysis is in Brunei and Singapore, and lowest in Myanmar and Nepal. Median number of dialysis machines/1000 ESKD population is 110 in HE and 53 in LE. Average number of machines/dialysis units in HE is 2.7 times higher than LE. The HE countries have 9 times more dialysis centers pmp (median HE-17, LE-02) and 16 times more nephrologist density (median HE-14.8 ppm, LE-0.94 ppm). Dialysis sessions >2/week is frequently followed in HE (84%) and <2/week in LE (64%). "On-demand" hemodialysis (<2 sessions/week) is prevalent in LE. Hemodialysis dropout rates at one year are lower in HE (12.3%; LE 53.4%), death being the major cause (HE-93.6%; LE-43.8%); renal transplants constitute 4% (Brunei) to 39% (Hong Kong) of the RRT in HE. ESKD burden is expected to increase >10% in all the HE countries except Taiwan, 10%-20% in the majority of LE countries.
Conclusion: Economic disparity in SA and SEA is reflected by poor dialysis infrastructure and penetration, inadequate manpower, higher OOPE, higher dialysis dropout rates, and lesser renal transplantations in LE countries. Utility of RRT can be improved by state funding and better insurance coverage.
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.
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: We identified articles published Jan 1, 2005, to March 7, 2019, describing financial burden/toxicity experienced by cancer patients and/or informal caregivers using OVID Medline Embase and PsychInfo, CINAHL, Business Source Complete, and EconLit databases. Only English language peer-reviewed full papers describing studies conducted in very high development index countries with predominantly publicly funded healthcare were eligible (excluded the USA). All stages of the review were evaluated in teams of two researchers excepting the final data extraction (CJL only).
RESULTS: The searches identified 7117 unique articles, 32 of which were eligible. Studies were undertaken in Canada, Australia, Ireland, UK, Germany, Denmark, Malaysia, Finland, France, South Korea, and the Netherlands. Eighteen studies reported patient/caregiver out-of-pocket costs (range US$17-US$506/month), 18 studies reported patient/caregiver lost income (range 17.6-67.3%), 14 studies reported patient/caregiver travel and accommodation costs (range US$8-US$393/month), and 6 studies reported financial stress (range 41-48%), strain (range 7-39%), or financial burden/distress/toxicity among patients/caregivers (range 22-27%). The majority of studies focused on patients, with some including caregivers. Financial toxicity was greater in those with early disease and/or more severe cancers.
CONCLUSIONS: Despite government-funded universal public healthcare, financial toxicity is an issue for cancer patients and their families. Although levels of toxicity vary between countries, the findings suggest financial protection appears to be inadequate in many countries.
METHODS: A cross-sectional survey was conducted from 3 to 12 April 2020. The health belief model (HBM) was used to assess predictors of the intent to receive the vaccine and the WTP.
RESULTS: A total of 1,159 complete responses was received. The majority reported a definite intent to receive the vaccine (48.2%), followed by a probable intent (29.8%) and a possible intent (16.3%). Both items under the perceived benefits construct in the HBM, namely believe the vaccination decreases the chance of infection (OR = 2.51, 95% CI 1.19-5.26) and the vaccination makes them feel less worry (OR = 2.19, 95% CI 1.03-4.65), were found to have the highest significant odds of a definite intention to take the vaccine. The mean ± standard deviation (SD) for the amount that participants were willing to pay for a dose of COVID-19 vaccine was MYR$134.0 (SD±79.2) [US$30.66 ± 18.12]. Most of the participants were willing to pay an amount of MYR$100 [US$23] (28.9%) and MYR$50 [US$11.5] (27.2%) for the vaccine. The higher marginal WTP for the vaccine was influenced by no affordability barriers as well as by socio-economic factors, such as higher education levels, professional and managerial occupations and higher incomes.
CONCLUSIONS: The findings demonstrate the utility of HBM constructs in understanding COVID-19 vaccination intention and WTP.
MATERIALS AND METHODS: Twelve focus group discussions (n = 64) were conducted with women with breast cancer from two public and three private hospitals. This study specifically focused on (a) health costs, (b) nonhealth costs, (c) employment and earnings, and (d) financial assistance. Thematic analysis was used.
RESULTS: Financial needs related to cancer treatment and health care varied according to the participant's socioeconomic background and type of medical insurance. Although having medical insurance alleviated cancer treatment-related financial difficulties, limited policy coverage for cancer care and suboptimal reimbursement policies were common complaints. Nonhealth expenditures were also cited as an important source of financial distress; patients from low-income households reported transport and parking costs as troublesome, with some struggling to afford basic necessities, whereas participants from higher-income households mentioned hired help, special food and/or supplements and appliances as expensive needs following cancer. Needy patients had a hard time navigating through the complex system to obtain financial support. Irrespective of socioeconomic status, reductions in household income due to loss of employment and/or earnings were a major source of economic hardship.
CONCLUSION: There are many unmet financial needs following a diagnosis of (breast) cancer even in settings with universal health coverage. Health care professionals may only be able to fulfill these unmet needs through multisectoral collaborations, catalyzed by strong political will.
IMPLICATIONS FOR PRACTICE: As unmet financial needs exist among patients with cancer across all socioeconomic groups, including for patients with medical insurance, financial navigation should be prioritized as an important component of cancer survivorship services, including in the low- and middle-income settings. Apart from assisting survivors to understand the costs of cancer care, navigate the complex system to obtain financial assistance, or file health insurance claims, any planned patient navigation program should also provide support to deal with employment-related challenges and navigate return to work. It is also echoed that costs for essential personal items (e.g., breast prostheses) should be covered by health insurance or subsidized by the government.
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 prospective 1-year study was conducted in rheumatology clinics of tertiary care hospitals of Karachi, Pakistan. Cost-of-illness methodology was used and all patient data related to costs of rheumatologist visits, physical therapy sessions, medications, assistive devices and laboratory investigations were obtained directly in printed hardcopies from patient electronic databases using their medical record numbers. Transportation cost was calculated from patient-reported log books. Data were analyzed through IBM SPSS version 23. Patients were asked to sign a written consent and the study was ethically approved.
RESULTS: The mean age of patients (N = 358) was 48 years. Most patients (73.7%) were female, married (86%) and had basic education (71.8%). Average cost of rheumatologist visits was PKR 11 510.61 (USD: 72.05) while it was PKR 66 947.37 (USD: 419.07) for physical therapy sessions. On average, medicines and medical devices costs were estimated at PKR 10 104.23 (USD: 63.25) and PKR 7848.48 (USD: 49.13) respectively. Cost attributed to diagnostic and laboratory charges was PKR 1962.12 (USD: 12.28) and travel expense was PKR 6541 (USD: 40.95). The direct expenditure associated with managing RA was PKR 37 558 (USD: 235.1). All costs were reported per annum.
CONCLUSION: Patient with RA in Pakistan pay a considerable amount of their income for managing their condition. Most patients have no provision for insurance which is a need considering the nature of the disease and associated productivity loss that would significantly lower income as the disease progresses.