Discounting money and health effects from communicable and noncommunicable diseases in Thailand.

The purpose of this study was to determine the discount rates for money and health outcomes in the Thai context, including the discount rates for communicable and non-communicable diseases. Moreover, this study aimed to explore the socio-demographic characteristics that influence discounting. The computer-based experimental design was used to obtain time preferences for money and health in a total of 1202 Chiang Mai province population, aged 25-50, individually interviewed by trained interviewers. Money-related questions were carried out in all subjects. For health-related questions, all subjects were randomly assigned in a 1:1 ratio for response to questions about Coronavirus Disease 2019 (COVID-19) (N = 602) and air pollution (N = 600). A choice-based elicitation procedure was performed in the experiment to obtain the indifference values from subjects' time preferences. The cumulative weighting functions were generated using the indifference values to indicate the degree of discounting. The discount factors were computed from the cumulative weighting functions. The discount rates were estimated using a continuous approximation based on the relationship between the discount factors and the parameters governing the discounting model. The Tobit model was applied to investigate the relationships between discounting and socio-demographic characteristics. Discounting for money was greater than discounting for health. Money and health had annual discount rates of 6.2% and 1.3%, respectively. Furthermore, in the COVID -19 situation, the annual discount rate for health was higher than that in the air pollution situation (2.4% vs. 0.7%). Generation X subjects (aged 42 years and above), children under the age of 15 in the household, and underlying diseases were positively related to discounting, while household income was negatively related to discounting. Health should be discounted at a lower rate than money. Moreover, different discount rates should be considered for different types of diseases.

Cost-Utility Analysis of Sacubitril-Valsartan Compared with Enalapril Treatment in Patients with Acute Decompensated Heart Failure in Thailand.

BACKGROUND: Sacubitril-valsartan is effective in reducing the N-terminal pro-B-type natriuretic peptide level of hospitalized patients with acute decompensated heart failure, with a high acquisition cost compared with enalapril treatment. OBJECTIVE: This study aimed to determine the cost utility of sacubitril-valsartan compared with enalapril for acute decompensated heart failure treatment. METHODS: A Markov model was constructed to project the total costs, life-years, quality-adjusted life-years (QALYs) of early initiation, and a 2-month delay of sacubitril-valsartan treatment and enalapril treatment in hospitalized patients with acute decompensated heart failure over a lifetime horizon from a Thai healthcare system perspective. Clinical inputs were mainly derived from the PIONEER-HF and PARADIGM-HF trials, together with Thai epidemiological data. Cost data were based on the Thai population. All costs and outcomes were discounted at 3% annually. A series of sensitivity analyses were performed. RESULTS: Compared with enalapril, sacubitril-valsartan incurred a higher total cost per year (THB 42,994 [US$1367.48] vs THB 19,787 [US$629.37]), and it gained more QALYs (4.969 vs 4.755). The incremental cost-effectiveness ratio was THB 108,508/QALY (US$3451.26/QALY). Early initiation of sacubitril-valsartan treatment was more cost effective than delayed treatment. Sensitivity analyses revealed that at a level of willingness to pay of THB 160,000/QALY (US$5089/QALY), sacubitril-valsartan was a cost-effective strategy of about 60%. CONCLUSIONS: Sacubitril-valsartan is cost effective in patients with acute decompensated heart failure. However, the results are highly dependent on the long-term cardiovascular mortality, and they are applicable only to Thailand or countries with a similarly structured healthcare system. Long-term registries should be pursued to decrease the uncertainty around long-term mortality.