Methods: This study used five series of National Health and Morbidity Survey data from 1986 to 2015. Healthcare utilisation for inpatient, outpatient and dental care were analysed. SES was grouped based on household expenditure variables accounting for total number of adults and children in the household using consumption per adult equivalents approach. The determination of healthcare utilisation across the SES segments was measured using concentration index.
Results: The overall distribution of inpatient utilisation tended towards the pro-poor, although only data from 1996 (P-value = 0.017) and 2006 (P-value = 0.021) were statistically significant (P < 0.05). Out-patient care showed changing trends from initially being pro-rich in 1986 (P < 0.05), then gradually switching to pro-poor in 2015 (P < 0.05). Dental care utilisation was significantly pro-rich throughout the survey period (P < 0.05). Public providers mostly showed significantly pro-poor trends for both in- and out-patient care (P < 0.05). Private providers, meanwhile, constantly showed a significantly pro-rich (P < 0.05) trend of utilisation.
Conclusion: Total health utilisation was close to being equal across SES throughout the years. However, this overall effect exhibited inequities as the effect of pro-rich utilisation in the private sector negated the pro-poor utilisation in the public sector. Strategies to improve equity should be consistent by increasing accessibility to the private sectors, which has been primarily dominated by the richest population.
Methods: With the SCOPUS database, we selected those documents made in Malaysia whose title included descriptors related to SGAs. We applied bibliometric indicators of production and dispersion, as Price's law and Bradford's law, respectively. We also calculated the participation index of the different countries. The bibliometric data were also been correlated with some social and health data from Malaysia (total per capita expenditure on health and gross domestic expenditure on R&D).
Results: We found 105 original documents published between 2004 and 2016. Our results fulfilled Price's law, with scientific production on SGAs showing exponential growth (r = 0.401, vs. r = 0.260 after linear adjustment). The drugs most studied are olanzapine (9 documents), clozapine (7), and risperidone (7). Division into Bradford zones yields a nucleus occupied by the Medical Journal of Malaysia, Singapore Medical Journal, Australian and New Zealand Journal of Psychiatry, and Pharmacogenomics. Totally, 63 different journals were used, but only one in the top four journals had an impact factor being greater than 3.
Conclusion: The publications on SGAs in Malaysia have undergone exponential growth, without evidence a saturation point.
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.
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$761). Almost 16% (79/503) suffered from catastrophic health spending (out-of-pocket health spending ≥40% of household non-food expenditures), 29.2% (147/503) were unable to pay for medical bills, 25.0% (126/503) withdrew savings to help meet living expenses, 16.5% (83/503) reduced their monthly food consumption, 12.5% (63/503) were unable to pay utility bills and 9.0% (45/503) borrowed money to help meet living expenses.
CONCLUSIONS: Overall, the economic impact of IHD on patients in Malaysia was considerable and the prospect of economic hardship likely to persist over the years due to the long-standing nature of IHD. The findings highlight the need to evaluate the present health financing system in Malaysia and to expand its safety net coverage for vulnerable patients.
METHODS: The National Nephrology Societies of the region responded to a questionnaire on KRT practices. The responses were based on the latest registry data, acceptable community-based studies and societal perceptions. The representative countries were divided into high income and higher-middle income (HI & HMI) and low income and lower-middle income (LI & LMI) groups.
RESULTS: Data provided by 15 countries showed almost similar percentage of GDP as health expenditure (4%-7%). But there was a significant difference in per capita income (HI & HMI -US$ 28 129 vs. LI & LMI - US$ 1710.2) between the groups. Even after having no significant difference in monthly cost of haemodialysis (HD) and PD in LI & LMI countries, they have poorer PD utilization as compared to HI & HMI countries (3.4% vs. 10.1%); the reason being lack of formal training/incentives and time constraints for the nephrologist while lack of reimbursement and poor general awareness of modalities has been a snag for the patients. The region expects ≥10% PD growth in the near future. Hong Kong and Thailand with 'PD first' policy have the highest PD utilization.
CONCLUSION: Important deterrents to PD underutilization were lack of PD centric policies, lackadaisical patient/physician's attitude, lack of structured patient awareness programs, formal training programs and affordability.
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.