METHODS: A cross-sectional, facility-based, concurrent mixed-methods study was carried out in seven health facilities in the Kailali, Baglung, and Ilam districts of Nepal. A total of 822 beneficiaries, sampled using probability proportional to size (PPS), attending health care institutions, were interviewed using a structured questionnaire for quantitative data. A total of seven focus group discussions (FGDs) and 12 in-depth interviews (IDIs), taken purposefully, were conducted with beneficiaries and service providers, using guidelines, respectively. Quantitative data were entered into Epi-data and analyzed with SPSS, MS-Excel, and Epitools, an online statistical calculator. Manual thematic analysis with predefined themes was carried out for qualitative data. Percentage, frequency, mean, and median were used to describe the variables, and the Chi-square test and binary logistic regression were used to infer the findings. We then combined the qualitative data from beneficiaries' and providers' perceptions, and experiences to explore different aspects of health insurance programs as well as to justify the quantitative findings.
RESULTS AND PROSPECTS: Of a total of 822 respondents (insured-404, uninsured-418), 370 (45%) were men. Families' median income was USD $65.96 (8.30-290.43). The perception of insurance premiums did not differ between the insured and uninsured groups (p = 0.53). Similarly, service utilization (OR = 220.4; 95% CI, 123.3-393.9) and accessibility (OR = 74.4; 95% CI, 42.5-130.6) were found to have high odds among the insured as compared to the uninsured respondents. Qualitative findings showed that the coverage and service quality were poor. Enrollment was gaining momentum despite nearly a one-tenth (9.1%) dropout rate. Moreover, different aspects, including provider-beneficiary communication, benefit packages, barriers, and ways to go, are discussed. Additionally, we also argue for some alternative health insurance schemes and strategies that may have possible implications in our contexts.
CONCLUSION: Although enrollment is encouraging, adherence is weak, with a considerable dropout rate and poor renewal. Patient management strategies and insurance education are recommended urgently. Furthermore, some alternate schemes and strategies may be considered.
METHODS: A systematic review was conducted across PubMed, Medline, Embase, Cochrane Library and CINAHLComplet@EBSCOhost from inception until 30 September 2022, capturing studies that reported the effect of HI on healthy lifestyle and NCDs. A narrative synthesis of the studies was done. The review concluded both longitudinal and cross-sectional studies. A critical appraisal checklist for survey-based studies and the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies were used for the quality assessment.
RESULT: Twenty-four studies met the inclusion criteria. HI was associated with the propensity to engage in physical activities (6/11 studies), consume healthy diets (4/7 studies), not to smoke (5/11 studies) or take alcohol (5/10 studies). Six (of nine) studies showed that HI coverage was associated with a lowered prevalence of NCDs.
CONCLUSION: This evidence suggests that HI is beneficial. More reports showed that it propitiated a healthy lifestyle and was associated with a reduced prevalence of NCDs.
MATERIALS AND METHODS: This cross-sectional study was conducted in three Malaysian public hospitals using a multilevel sampling technique to recruit 630 respondents. A validated self-developed four-domain questionnaire which includes one domain for health insurance was used to collect the relevant data.
RESULTS: Approximately 31.7% of the respondents owned PHI. The PHI usage was significantly higher among male respondents (p=0.035), those aged 18-40 years old (p<0.001), Indian and Chinese ethnicities (p=0.002), with tertiary education level (p<0.001), employed (p<0.001), working in the private sector (p<0.001), high household income (T20) (p<0.001), home near to the hospital (p=0.001) and medium household size (p<0.001). The significant predictive factors were age 18-40 years aOR 3.01 (95% CI: 1.67-5.41), age 41-60 years aOR 2.22 (95% CI 1.41-3.49), medium (M40) income aOR 2.90 (95% CI: 1.92-4.39) and high (T20) income aOR 3.86 (95% CI: 1.68-18.91), home near to the hospital aOR 1.68 (95% CI: 1.10-2.55), medium household size aOR 2.20 (95% CI: 1.30-3.72) and female head of household aOR 1.79 (95% CI: 1.01-3.16). The type of cancer treatment, the location of treatment, prior treatment in private healthcare facilities and existence of financial coping mechanisms also were significant factors in determining PHI usage among cancer patients in this study.
CONCLUSION: Several factors are significantly associated with PHI usage in cancer patients. The outcome of this study can guide policymakers to identify high-risk groups which need supplementary health insurance to bear the cost for their cancer treatment so that a better pre-payment health financing system such as a national health insurance can be formulated to cater for these groups.
METHODS: The authors obtained data on volumes and reimbursement rates for the most common 25 tests at the five hospitals with which they are affiliated and organized them to be as comparable as possible. Simple descriptive statistics were used to make cross-country comparisons.
RESULTS: There are strong similarities across all five hospitals in the top five tests by both volume and revenue. However, the top five by volume differ from the top five by revenue. Reimbursement rates also follow common patterns, being lowest for the most common biochemical test; intermediate for the most common hematology and microbiology tests, respectively; and highest for the most common pathology test.
CONCLUSIONS: Most of the most common tests also appear in the new Essential Diagnostics List. This may inform plans for universal health coverage.
METHODS: This study employs a quantitative method by way of a cross-sectional approach. The 2018 JKN claims data, drawn from a 1% sample that JKN annually produces, were analyzed. Nine hundred forty-five HIV patients out of 1,971,744 members were identified in the data sample and their claims record data at primary care and hospital levels were analyzed. Using ICD (International Statistical Classification of Diseases and Related Health Problems), 10 codes (i.e., B20, B21, B22, B23, and B24) that fall within the categories of HIV-related disease. For each level, patterns of service utilization by patient-health status, discharge status, severity level, and total cost per claim were analyzed.
RESULTS: Most HIV patients (81%) who first seek care at the primary-care level are referred to hospitals. 72.5% of the HIV patients receive antiretroviral treatment (ART) through JKN; 22% at the primary care level; and 78% at hospitals. The referral rate from public primary-care facilities was almost double (45%) that of private providers (24%). The most common referral destination was higher-level hospitals: Class B 48%, and Class C 25%, followed by the lowest Class A at 3%. Because JKN pays hospitals for each inpatient admission, it was possible to estimate the cost of hospital care. Extrapolating the sample of hospital cases to the national level using the available weight score, it was estimated that JKN paid IDR 444 billion a year for HIV hospital services and a portion of capitation payment.
CONCLUSION: There was an underrepresentation of PLHIV (People Living with HIV) who had been covered by JKN as 25% of the total PLHIV on ART were able to attain access through other schemes. This study finding is principally aligned with other local research findings regarding a portion of PLHIV access and the preferred delivery channel. Moreover, the issue behind the underutilization of National Health Insurance services in Indonesia among PLHIV is similar to what was experienced in Vietnam in 2015. The 2015 Vietnam study showed that negative perception, the experience of using social health insurance as well as inaccurate information, may lead to the underutilization problem (Vietnam-Administration-HIV/AIDSControl, Social health insurance and people living with HIV in Vietnam: an assessment of enrollment in and use of social health insurance for the care and treatment of people living with HIV, 2015). Furthermore, the current research finding shows that 99% of the total estimated HIV expenditure occurred at the hospital. This indicates a potential inefficiency in the service delivery scheme that needs to be decentralized to a primary-care facility.
METHODS: Medical claims records from February 2019 to February 2020 were extracted from a health insurance claims database. Data cleaning and data analysis were performed using Python 3.7 with the Pandas, NumPy and Matplotlib libraries. The top five most common diagnoses were identified, and for each diagnosis, the most common medication classes and medications prescribed were quantified. Potentially inappropriate prescribing practices were identified by comparing the medications prescribed with relevant clinical guidelines.
KEY FINDINGS: The five most common diagnoses were upper respiratory tract infection (41.5%), diarrhoea (7.7%), musculoskeletal pain (7.6%), headache (6.7%) and gastritis (4.0%). Medications prescribed by general practitioners were largely as expected for symptomatic management of the respective conditions. One area of potentially inappropriate prescribing identified was inappropriate antibiotic choice. Same-class polypharmacy that may lead to an increased risk of adverse events were also identified, primarily involving multiple paracetamol-containing products, non-steroidal anti-inflammatory drugs (NSAIDs), and antihistamines. Other areas of non-adherence to guidelines identified included the potential overuse of oral corticosteroids and oral salbutamol, and inappropriate gastroprotection for patients receiving NSAIDs.
CONCLUSIONS: While prescribing practices are generally appropriate within the private primary care sector, there remain several areas where some potentially inappropriate prescribing occurs. The areas identified should be the focus in continuing efforts to improve prescribing practices to obtain the optimal clinical outcomes while reducing unnecessary risks and healthcare costs.
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.