Cost-effectiveness analysis of a digital Diabetes Prevention Program (dDPP) in prediabetic patients.

OBJECTIVES: To assess the cost-effectiveness of a digital Diabetes Prevention Program (dDPP) in preventing type 2 diabetes mellitus among prediabetic patients from a health system perspective over a 10-year time horizon. METHODS: A Markov cohort model was constructed to assess the cost-effectiveness of dDPP compared to a small group education (SGE) intervention. Transition probabilities for the first year of the model were derived from two clinical trials on dDPP. Transition probabilities for longer-term effects were derived from meta-analyses on lifestyle and Diabetes Prevention Program interventions. Cost and health utilities were derived from published literature. Partial completion of interventions was incorporated to provide a robust prediction of a real-world deployment. Parameter uncertainties were assessed using univariate and probabilistic sensitivity analyses. Cost-effectiveness was measured by an incremental cost-effectiveness ratio (ICER) between dDPP and SGE from a health system perspective over a 10-year time horizon. RESULTS: The dDPP dominated the SGE at the $50,000, $100,000, and $150,000 willingness-to-pay thresholds per quality-adjusted life years (QALYs). The base case analysis at the $100,000 willingness-to-pay threshold (WTP) revealed a dominated ICER, with the SGE costing $1332 more and accruing an average of 0.04 fewer QALYs. Probabilistic sensitivity analysis showed that the dDPP was preferred in 64.4% of simulations across the $100,000 WTP thresholds. CONCLUSIONS: The findings comparing a dDPP to an SGE suggest that a dDPP can be cost-effective for patients with a high risk of developing type 2 diabetes.

Telemedicine Use by Age in Louisiana Medicaid During COVID-19: Claims-Based Longitudinal Analysis.

BACKGROUND: Limited availability of in-person health care services and fear of contracting COVID-19 during the pandemic promoted an increased reliance on telemedicine. However, long-standing inequities in telemedicine due to unequal levels of digital literacy and internet connectivity among different age groups raise concerns about whether the uptake of telemedicine has exacerbated or alleviated those inequities. OBJECTIVE: The aim of this study is to examine changes in telemedicine and in-person health service use during the COVID-19 pandemic across age groups for Medicaid beneficiaries in the state of Louisiana. METHODS: Interrupted time series models were used on Louisiana Medicaid claims data to estimate trends in total, in-person, and telemedicine monthly office visit claims per 1000 Medicaid beneficiaries between January 2018 and December 2020. Changes in care pattern trends and levels were estimated around the infection peaks (April 2020 and July 2020) and for an end-of-year infection leveling off period (December 2020). Four mutually exclusive age categories (0 to 17, 18 to 34, 35 to 49, and 50 to 64 years) were used to compare the differences. RESULTS: Prior to the COVID-19 pandemic, telemedicine services accounted for less than 1% of total office visit claim volume across the age groups. Each age group followed similar patterns of sharp increases in April 2020, downward trends until sharp increases again in July 2020, followed by flat trends thereafter until December 2020. These sharp increases were most pronounced for older patients, with those aged 50 to 64 years seeing increases of 184.09 telemedicine claims per 1000 Medicaid beneficiaries in April 2020 (95% CI 172.19 to 195.99) and 120.81 in July 2020 (95% CI 101.32 to 140.31) compared with those aged 18 to 34 years, seeing increases of 84.47 (95% CI 78.64 to 90.31) and 57.00 (95% CI 48.21 to 65.79), respectively. This resulted in overall changes from baseline to December 2020 levels of 123.65 (95% CI 112.79 to 134.51) for those aged 50 to 64 years compared with 59.07 (95% CI 53.89 to 64.24) for those aged 18 to 34 years. CONCLUSIONS: Older Medicaid beneficiaries in Louisiana had higher rates of telemedicine claim volume during the COVID-19 pandemic compared with younger beneficiaries.

Medical service utilization and out-of-pocket spending among near-poor National Health Insurance members in South Korea.

BACKGROUND: The public health care system in South Korea is a two-tiered system. The lowest-income population is covered by the Medical Aid program, and the remaining population is covered by the National Health Insurance. The near poor, a relatively low-income population which is excluded from South Korea's Medical Aid program due to exceeding the income threshold, experiences insufficient use of medical services and incurs high out-of-pocket expenses due to a lack of coverage under the country's National Health Insurance (NHI) program. This study aims to examine medical utilization, out-of-pocket spending, and the occurrence of catastrophic health expenditures among the near-poor group compared to both Medical Aid beneficiaries and other (higher income) NHI members. METHODS: A cross-sectional study was conducted drawing upon a nationally representative dataset derived from the 2018 Korea Welfare Panel Study. The study classified people into three groups: Medical Aid beneficiaries; the near-poor population below 50 % of the median income threshold but still not qualifying for Medical Aid and thus enrolled in NHI; and NHI members above the threshold of 50 % of the median income. Using a generalized boosted model to estimate the propensity score weights between study groups, this study examined medical utilization, out-of-pocket spending, and the occurrence of catastrophic health expenditure among the study groups. RESULTS: The findings suggest that the utilization of medical services was not significantly different among the study groups. However, out-of-pocket spending and the occurrence of catastrophic health expenditure were significantly higher in the near-poor group compared to the other two groups. CONCLUSIONS: The study found that the near-poor group was the most vulnerable among the Korean population because of their higher chance of incurring greater out-of-pocket spending and catastrophic health expenditures than is the case among the Medical Aid beneficiary and above-poverty line groups. Health policy needs to take the vulnerability of this near-poor population into account.