METHODS: A Microsoft Excel-based cost calculator was developed for such comparison. The estimated size of eligible population, uptake rates for dapagliflozin, as well as costs related to drugs, clinical events, and adverse events were based on published data, official tariffs, and databases, and expert opinion. Clinical data from the DAPA-HF trial were used to inform efficacy and safety inputs (i.e., hospitalization for heart failure (hHF), cardiovascular death, and adverse events). Results were reported as total annual and cumulative costs (in 2023 Malaysian Ringgits [RM], United States Dollars [USD], and European Union Euros, [EUR]; with exchange rates of 1 USD = RM 4.40 and 1 EUR = RM 4.90]), as well as the number of clinical events. Sensitivity and scenario analyses were also conducted.
FINDINGS: The base-case analysis estimated that over a five-year period, the adoption of dapagliflozin for HFrEF treatment would result in a cumulative cost-saving of RM 2.6 million (USD 0.6 million/EUR 0.5 million), representing a 0.3% reduction in costs, driven primarily by reduced expenditure on hHF. Moreover, dapagliflozin treatment would lead to 731 fewer hHF and 366 fewer cardiovascular deaths. Sensitivity and scenario analyses revealed that the results were most sensitive to assumptions regarding loop diuretic requirements and the cost of dapagliflozin. Although cost savings or a net-zero balance were projected for the first four years, an anticipated 2.5% annual increase in dapagliflozin uptake in the longer term would lead to additional costs for the MOH, starting from the fifth year.
IMPLICATIONS: Incorporating dapagliflozin into the SoC can improve health outcomes for HFrEF patients and may generate cost savings, potentially easing the economic strain of HFrEF management on Malaysia's public healthcare system in the short term. Nonetheless, a modest increase in budget should be anticipated as more patients gain access to the treatment over time.
DESIGN: Budget impact analysis. Assumptions and costs in the opportunistic and novel CRC screening scenarios were derived from a previous evaluation of opportunistic CRC screening in community health clinics across Malaysia and the CRC-SIM research project, respectively.
SETTING: National level (with supplement analysis for district level). The BIA was conducted from the viewpoint of the federal government and estimated the annual financial impact over a period of 5 years.
RESULTS: The total annual cost of the current practice of opportunistic screening was RM1 584 321 (~I$1 099 460) of which 80% (RM1 274 690 or ~I$884 587) was expended on the provision of opportunistic CRC to adults who availed of the service. Regarding the implementation of national CRC screening programme, the net budget impact in the first year was estimated to be RM107 631 959 (~I$74 692 546) and to reach RM148 485 812 (~I$103 043 589) in the fifth year based on an assumed increased uptake of 5% annually. The costs were calculated to be sensitive to the probability of adults who were contactable, eligible and agreeable to participating in the programme.
CONCLUSIONS: Results from the BIA provided direct and explicit estimates of the budget changes to when implementing a population-based national CRC screening programme to aid decision making by health services planners and commissioners in Malaysia about whether such programme is affordable within given their budget constraint. The study also illustrates the use and value of the BIA approach in low-income and middle-income countries and resource-constrained settings.
METHODS: An Excel-based budget impact model was constructed to assess dialysis-associated costs when changing dialysis modalities between PD and ICHD. The model incorporates the current modality distribution and accounts for Malaysian government dialysis payments and erythropoiesis-stimulating agent costs. Epidemiological data including dialysis prevalence, incidence, mortality, and transplant rates from the Malaysian renal registry reports were used to estimate the dialysis patient population for the next 5 years. The baseline scenario assumed a stable distribution of PD (8%) and ICHD (92%) over 5 years. Alternative scenarios included the prevalence of PD increasing by 2.5%, 5.0%, and 7.5% or decreasing 1% yearly over 5 years. All four scenarios were accompanied with commensurate changes in ICHD.
RESULTS: Under the current best available cost information, an increase in the prevalent PD population from 8% in 2014 to 18%, 28%, or 38% in 2018 is predicted to result in 5-year cumulative savings of Ringgit Malaysia (RM) 7.98 million, RM15.96 million, and RM23.93 million, respectively, for the Malaysian government. If the prevalent PD population were to decrease from 8% in 2014 to 4.0% by 2018, the total expenditure for dialysis treatments would increase by RM3.19 million over the next 5 years.
CONCLUSIONS: Under the current cost information associated with PD and HD paid by the Malaysian government, increasing the proportion of patients on PD could potentially reduce dialysis-associated costs in Malaysia.
Methods: We applied a retrospective approach using a top-down costing method to estimate the cost of health care services. Clinical and Administrative departments divided into cost centres, and the unit cost was calculated by dividing the total cost of final care cost centres into the total number of patients discharged in one year. The average cost of inpatient services was calculated based on the average cost of each ward and the number of patients treated.
Results: The average cost per patient stayed in KFCH was SAR 19,034, with the highest cost of SAR 108,561 for patients in the Orthopedic ward. The average cost of the patient in the Surgery ward, Plastic surgery, Neurosurgery, Medical ward, Pediatric ward and Gynecology ward was SAR 33,033, SAR 29,425, SAR 23,444, SAR 20,450, SAR 9579 and SAR 8636 respectively.
Conclusion: This study provides necessary information about the cost of health care services in a tertiary care setting. This information can be used as a primary tool and reference for further studies in other regions of the country. Hence, this data can help to provide a better understanding of tertiary hospital costing in the region to achieve the privatization objective.