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Objective: Autoimmune encephalitis (AE) is a highly treatable neurologic condition that can cause psychosis. Screening for AE is not currently recommended in routine workup for first-episode psychosis (FEP), owing partly to the high cost of testing for AE-associated neuronal autoantibodies., Methods: This study used a decision-analytic model to estimate the cost-effectiveness of routine serum screening for AE compared with clinically targeted screening in patients with FEP. Model parameters drawn from prior published literature included the prevalence of neuronal autoantibodies in FEP (4.5%), serum autoantibody panel cost (US $291), remission probability with antipsychotics (0.58), and remission probability with immunotherapy for patients diagnosed with AE (0.85). Outcomes included quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs), assessed over a 5-year horizon from the US health care sector and societal perspectives. ICER thresholds of $50,000/QALY to $150,000/QALY were used to define cost-effectiveness. The analysis was conducted between June 2018 and January 2020., Results: Routine screening led to mean QALY gains of 0.008 among all patients and 0.174 among the subgroup of patients with neuronal autoantibodies. Mean costs increased by $780 from a societal perspective and $1,150 from a health care sector perspective, resulting in ICERs of $99,330/QALY and $147,460/QALY, respectively. Incorporating joint input data uncertainty, the likelihood routine screening has an ICER ≤ $150,000/QALY was 55% from a societal perspective and 37% from a health care sector perspective. The model parameter with the greatest contribution to overall uncertainty was the effectiveness of immunotherapy relative to antipsychotics., Conclusions: Routine screening for AE in patients with FEP may be cost-effective in the United States. As further immunotherapy effectiveness data become available, a more definitive recommendation to perform routine screening could be warranted., (© Copyright 2020 Physicians Postgraduate Press, Inc.)

Objective: This study aimed to estimate the cost-effectiveness of esketamine, a novel intranasally dosed antidepressant, for patients in the United States with treatment-resistant depression., Methods: A decision-analytic model parameterized with efficacy data from phase 3 randomized trials of esketamine was used to simulate the effects of treatment with esketamine versus oral antidepressants over a 5-year horizon, from both societal and health care sector perspectives. Outcomes included remission and response of depression, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs) for esketamine. Value-based prices were calculated, defined as the per-dose price at which esketamine would become cost-effective given cost-effectiveness thresholds of $50,000/QALY, $100,000/QALY, and $150,000/QALY. Uncertainty in these outcomes was assessed with probabilistic sensitivity analyses. Key model parameters included the efficacy of esketamine versus oral antidepressants (relative risk of 1.39 for remission; 1.32 for response) and the monthly cost of esketamine ($5,572 for month 1; $1,699-$2,244 thereafter)., Results: Over 5 years, esketamine was projected to increase time in remission from 25.3% to 31.1% of life-years, resulting in a gain of 0.07 QALYs. Esketamine increased societal costs by $16,617 and health care sector costs by $16,995. Base case ICERs were $237,111/QALY (societal) and $242,496/QALY (health care sector). Probabilistic sensitivity analysis showed a greater than 95% likelihood that esketamine's ICER would be above $150,000/QALY. At a cost-effectiveness threshold of $150,000/QALY, esketamine's value-based price was approximately $140/dose (versus a current price of $240/dose)., Conclusions: Esketamine is unlikely to be cost-effective for management of treatment-resistant depression in the United States unless its price falls by more than 40%.

Background: Healthcare payers in the United States are increasingly tying provider payments to quality and value using pay-for-performance policies. Cost-effectiveness analysis quantifies value in healthcare but is not currently used to design or prioritize pay-for-performance strategies or metrics. Acute ischemic stroke care provides a useful application to demonstrate how simulation modeling can be used to determine cost-effective levels of financial incentives used in pay-for-performance policies and associated challenges with this approach., Methods and Results: Our framework requires a simulation model that can estimate quality-adjusted life years and costs resulting from improvements in a quality metric. A monetary level of incentives can then be back-calculated using the lifetime discounted quality-adjusted life year (which includes effectiveness of quality improvement) and cost (which includes incentive payments and cost offsets from quality improvements) outputs from the model. We applied this framework to an acute ischemic stroke microsimulation model to calculate the difference in population-level net monetary benefit (willingness-to-pay of $50 000 to $150 000/quality-adjusted life year) accrued under current Medicare policy (stroke payment not adjusted for performance) compared with various hypothetical pay-for-performance policies. Performance measurement was based on time-to-thrombolytic treatment with tPA (tissue-type plasminogen activator). Compared with current payment, equivalent population-level net monetary benefit was achieved in pay-for-performance policies with 10-minute door-to-needle time reductions (5057 more acute ischemic stroke cases/y in the 0-3-hour window) incentivized by increasing tPA payment by as much as 18% to 44% depending on willingness-to-pay for health., Conclusions: Cost-effectiveness modeling can be used to determine the upper bound of financial incentives used in pay-for-performance policies, although currently, this approach is limited due to data requirements and modeling assumptions. For tPA payments in acute ischemic stroke, our model-based results suggest financial incentives leading to a 10-minute decrease in door-to-needle time should be implemented but not exceed 18% to 44% of current tPA payment. In general, the optimal level of financial incentives will depend on willingness-to-pay for health and other modeling assumptions around parameter uncertainty and the relationship between quality improvements and long-run quality-adjusted life expectancy and costs.

Background: Targeting low-dose computed tomography (LDCT) for lung cancer screening to persons at highest risk for lung cancer mortality has been suggested to improve screening efficiency., Objective: To quantify the value of risk-targeted selection for lung cancer screening compared with National Lung Screening Trial (NLST) eligibility criteria., Design: Cost-effectiveness analysis using a multistate prediction model., Data Sources: NLST., Target Population: Current and former smokers eligible for lung cancer screening., Time Horizon: Lifetime., Perspective: Health care sector., Intervention: Risk-targeted versus NLST-based screening., Outcome Measures: Incremental 7-year mortality, life expectancy, quality-adjusted life-years (QALYs), costs, and cost-effectiveness of screening with LDCT versus chest radiography at each decile of lung cancer mortality risk., Results of Base-Case Analysis: Participants at greater risk for lung cancer mortality were older and had more comorbid conditions and higher screening-related costs. The incremental lung cancer mortality benefits during the first 7 years ranged from 1.2 to 9.5 lung cancer deaths prevented per 10 000 person-years for the lowest to highest risk deciles, respectively (extreme decile ratio, 7.9). The gradient of benefits across risk groups, however, was attenuated in terms of life-years (extreme decile ratio, 3.6) and QALYs (extreme decile ratio, 2.4). The incremental cost-effectiveness ratios (ICERs) were similar across risk deciles ($75 000 per QALY in the lowest risk decile to $53 000 per QALY in the highest risk decile). Payers willing to pay $100 000 per QALY would pay for LDCT screening for all decile groups., Results of Sensitivity Analysis: Alternative assumptions did not substantially alter our findings., Limitation: Our model did not account for all correlated differences between lung cancer mortality risk and quality of life., Conclusions: Although risk targeting may improve screening efficiency in terms of early lung cancer mortality per person screened, the gains in efficiency are attenuated and modest in terms of life-years, QALYs, and cost-effectiveness., Primary Funding Source: National Institutes of Health (U01NS086294).