Estimating the Lifetime Costs and Benefits of the Incredible Years Teacher Classroom Management Intervention Using Data From 30 Months Follow-Up of the Supporting Teachers and childRen in Schools Trial.

OBJECTIVES: The Incredible Years Teacher® Classroom Management (IY-TCM) intervention is associated with short-term improvements in mental health difficulties in young people. The aim was to estimate the long-term impact and cost-effectiveness of the IY-TCM intervention compared with no intervention. METHODS: An existing health economic model (LifeSim 1.0) was used to translate short-term changes in the Strength and Difficulties Questionnaire (SDQ), based on the Supporting Teachers and childRen in Schools cluster randomized controlled trial of the IY-TCM intervention in schools, into estimated medium- and long-term effects using multiple longitudinal data sets. LifeSim 1.0 was adapted to incorporate teacher-reported SDQ and account for individual heterogeneity. Cost-effectiveness analyses were conducted using the trial-based intervention cost with subgroup analyses on deprivation, conduct scores and parental depression in the simulated baseline population. RESULTS: Regression analyses show significant predictor variables for intervention effectiveness, including deprivation and baseline SDQ. LifeSim results indicate small gains in long-term outcomes, and cost-effective analyses estimated that the IY-TCM intervention could be cost-effective, but there was a large amount of uncertainty (net monetary benefit = £10, Estimated CI = -£134, £156). Benefits and certainty of cost-effectiveness were greater for some subgroups, such as those with high conduct scores at baseline (net monetary benefit = £206, Estimated CI = £26, £318). CONCLUSIONS: IY-TCM could be cost-effective, but there was a large amount of uncertainty around costs and benefits. Greater benefits for pupils with difficulties at baseline suggest that the intervention may be more cost-effective for schools in more deprived areas with high levels of conduct problems.

Examining the Impact of Structural Uncertainty Across 10 Type 2 Diabetes Models: Results From the 2022 Mount Hood Challenge.

OBJECTIVES: The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes. METHODS: Ten independent modeling groups completed a blinded simulation exercise to estimate the cost-effectiveness of 3 interventions in 2 type 2 diabetes populations. Modeling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB) and the drivers of those differences. RESULTS: Overall, modeling groups agreed which interventions had a positive NMB (ie, were cost-effective), Although estimates of NMB varied substantially-by up to £23 696 for 1 intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modeled health states was also a significant predictor of NMB. CONCLUSIONS: This exercise demonstrates that structural uncertainty between different health economic models affects cost-effectiveness estimates. Although it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimizing the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modeling.

A Dutch cost-effectiveness analysis of fremanezumab versus best supportive care in patients with chronic migraine and inadequate response to prior preventive therapy.

BACKGROUND: Chronic migraine (CM) is the most severe and burdensome subtype of migraine. Fremanezumab is a monoclonal antibody that targets the calcitonin gene-related peptide pathway as a migraine preventive therapy. This study aimed to conduct a cost-effectiveness analysis of fremanezumab from a societal perspective in the Netherlands, using a Markov cohort simulation model. METHODS: The base-case cost-effectiveness analysis adhered to the Netherlands Authority guidelines. Fremanezumab was compared with best supportive care (BSC; acute migraine treatment only) in patients with CM and an inadequate response to topiramate or valproate and onabotulinumtoxinA (Dutch patient group [DPG]). A supportive analysis was conducted in the broader group of CM patients with prior inadequate response to 2-4 different classes of migraine preventive treatments. One-way sensitivity, probabilistic sensitivity, and scenario analyses were conducted. RESULTS: Over a lifetime horizon, fremanezumab is cost saving compared with BSC in the DPG (saving of €2514 per patient) and led to an increase of 1.45 quality-adjusted life-years (QALYs). In the broader supportive analysis, fremanezumab was cost effective compared with BSC, with an incremental cost-effectiveness ratio of €2547/QALY gained. Fremanezumab remained cost effective in all sensitivity and scenario analyses. CONCLUSION: In comparison to BSC, fremanezumab is cost saving in the DPG and cost effective in the broader population.

Achieving Decentralized, Electrified, and Decarbonized Ammonia Production.

The rapid reduction in the cost of renewable energy has motivated the transition from carbon-intensive chemical manufacturing to renewable, electrified, and decarbonized technologies. Although electrified chemical manufacturing technologies differ greatly, the feasibility of each electrified approach is largely related to the energy efficiency and capital cost of the system. Here, we examine the feasibility of ammonia production systems driven by wind and photovoltaic energy. We identify the optimal regions where wind and photovoltaic electricity production may be able to meet the local demand for ammonia-based fertilizers and set technology targets for electrified ammonia production. To compete with the methane-fed Haber-Bosch process, electrified ammonia production must reach energy efficiencies of above 20% for high natural gas prices and 70% for low natural gas prices. To account for growing concerns regarding access to water, geospatial optimization considers water stress caused by new ammonia facilities, and recommendations ensure that the identified regions do not experience an increase in water stress. Reducing water stress by 99% increases costs by only 1.4%. Furthermore, a movement toward a more decentralized ammonia supply chain driven by wind and photovoltaic electricity can reduce the transportation distance for ammonia by up to 76% while increasing production costs by 18%.

Disease Progression Modeling for Economic Evaluation in Nonalcoholic Fatty Liver Disease-A Systematic Review.

BACKGROUND & AIMS: Globally, 25% of people have nonalcoholic fatty liver disease (NAFLD), and, currently, there are no approved pharmacologic treatments for NAFLD. With a slow disease progression, long-term impact of pharmacologic treatments can be assessed only by complementing emerging clinical trial evidence with data from other sources in disease progression modeling. Although this modeling is crucial for economic evaluation studies assessing the clinical and economic consequences of new treatments, the approach to modeling the natural history of NAFLD differs in contemporary research. This systematic literature review investigated modeling of the natural history of NAFLD. METHODS: A systematic literature review was conducted searching PubMed, Scopus, Cochrane, and the National Health Service Economic Evaluation Database to identify articles focusing on modeling of the natural history of NAFLD. Model structure and transition probabilities were extracted from included studies. RESULTS: Of the 28 articles identified, differences were seen in model structure and data input. Clear definitions of nonalcoholic steatohepatitis and NAFLD often were lacking; differences in the granularity of modeling fibrosis progression, the approach to disease regression, and modeling of advanced liver disease varied across studies. Observed transition probabilities for F0 to F1, F1 to F2, F2 to F3, and F3 to compensated cirrhosis varied between 0.059 to 0.095, 0.023 to 0.140, 0.018 to 0.070, and 0.040 to 0.118, respectively. CONCLUSIONS: The difference in disease progression modeling for seemingly similar models warrants further inquiry regarding how to model the natural course of NAFLD. Such differences may have a large impact when assessing the value of emerging pharmacologic treatments.

Dealing With Uncertainty in Early Health Technology Assessment: An Exploration of Methods for Decision Making Under Deep Uncertainty.

OBJECTIVES: In early stages, the consequences of innovations are often unknown or deeply uncertain, which complicates early health economic modeling (EHEM). The field of decision making under deep uncertainty uses exploratory modeling (EM) in situations when the system model, input probabilities/distributions, and consequences are unknown or debated. Our aim was to evaluate the use of EM for early evaluation of health technologies. METHODS: We applied EM and EHEM to an early evaluation of minimally invasive endoscopy-guided surgery (MIS) for acute intracerebral hemorrhage and compared these models to derive differences, merits, and drawbacks of EM. RESULTS: EHEM and EM differ fundamentally in how uncertainty is handled. Where in EHEM the focus is on the value of technology, while accounting for the uncertainty, EM focuses on the uncertainty. EM aims to find robust strategies, which give relatively good outcomes over a wide range of plausible futures. This was reflected in our case study. EHEM provided cost-effectiveness thresholds for MIS effectiveness, assuming fixed MIS costs. EM showed that a policy with a population in which most patients had severe intracerebral hemorrhage was most robust, regardless of MIS effectiveness, complications, and costs. CONCLUSIONS: EHEM and EM were found to complement each other. EM seems most suited in the very early phases of innovation to explore existing uncertainty and many potential strategies. EHEM seems most useful to optimize promising strategies, yet EM methods are complex and might only add value when stakeholders are willing to consider multiple solutions to a problem and adopt flexible research and adoption strategies.

Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Cost-effectiveness and budget impact of heat-stable carbetocin compared to oxytocin and misoprostol for the prevention of postpartum hemorrhage (PPH) in women giving birth in India.

INTRODUCTION: Low- and middle-income countries (LMICs) are committed to achieving the Sustainable Development Goal 3.1 to reduce maternal mortality. The Ministry of Health and Family Welfare of India recommends prophylactic uterotonic administration to every woman following delivery to reduce the risk of postpartum hemorrhage (PPH), as PPH is the leading cause of maternal mortality in LMICs, including India. In 2018, the World Health Organization first recognized heat-stable carbetocin for PPH prevention. Governments are now considering its introduction into their public health systems. METHODS: A decision-tree model was developed from the public healthcare system perspective to compare the value of heat-stable carbetocin versus oxytocin and misoprostol among women giving birth in public sector healthcare facilities in India. The model accounted for differences in PPH risk and costs based on mode of delivery and healthcare setting, as well as provider behavior to mitigate quality concerns of oxytocin. Model outcomes for each prophylactic uterotonic included the number of PPH events, DALYs due to PPH, deaths due to PPH, and direct medical care costs. The budget impact was estimated based on projected uterotonic uptake between 2022-2026. RESULTS: Compared to oxytocin, heat-stable carbetocin avoided 5,468 additional PPH events, 5 deaths, and 244 DALYs per 100,000 births. Projected direct medical costs to the public healthcare system were lowered by US $171,700 (₹12.8 million; exchange rate of ₹74.65 = US$1 from 2 Feb 2022) per 100,000 births. Benefits were even greater when compared to misoprostol (7,032 fewer PPH events, 10 fewer deaths, 470 fewer DALYs, and $230,248 saved per 100,000 births). In the budget impact analysis, India's public health system is projected to save US$11.4 million (₹849 million) over the next five years if the market share for heat-stable carbetocin grows to 19% of prophylactic uterotonics administered. CONCLUSIONS: Heat-stable carbetocin is expected to reduce the number of PPH events and deaths, avoid more DALYs, and reduce costs to the public healthcare system of India. Greater adoption of heat-stable carbetocin for the prevention of PPH could advance India's efforts to achieve its maternal health goals and increase efficiency of its public health spending.

Venous thromboembolism prophylaxis in shoulder surgery: a break-even cost-effectiveness study.

BACKGROUND: Venous thromboembolism (VTE) is a serious complication following orthopedic shoulder surgery; however, research is limited involving the break-even cost-effectiveness of VTE prophylaxis. The purpose of this study was to determine whether the cost of aspirin and enoxaparin would break even for VTE prevention in patients following shoulder surgery. METHODS: A drug retail database was used to obtain the lowest price for a course of aspirin (81 mg) and enoxaparin (40 mg) to perform a break-even cost analysis. Our institutional purchasing records were then searched to estimate the cost of treating a symptomatic VTE. The TriNetX national database was queried to establish a rate of VTE after shoulder surgery. A break-even cost analysis was performed by determining the absolute risk reduction (ARR). This value was used to calculate the number of patients who are treated to prevent a single VTE while breaking even on cost. Sensitivity analyses were performed for drugs that did not break even at the database-derived VTE rates. RESULTS: Full medication courses of aspirin and enoxaparin were found to cost $1.18 and $125.37, respectively. The cost of treating a symptomatic VTE was determined to be $9407.00. Data from the TriNetX database showed rates of symptomatic VTE following shoulder arthroplasty, hemiarthroplasty, and arthroscopic rotator cuff repair of 1.60%, 1.50%, and 0.68%, respectively. Aspirin broke even on cost for all procedures if the initial rate decreased by an ARR of 0.01% (number needed to treat, 7972). Similarly, enoxaparin broke even for shoulder arthroplasty and hemiarthroplasty if the initial rate of VTE decreased by an ARR of 1.33% (number needed to treat, 75). Enoxaparin did not break even at the initial VTE rate for arthroscopic rotator cuff repair; however, sensitivity analysis found enoxaparin would break even if the drug could be obtained at a cost of ≤$60.00. Enoxaparin broke even if the cost of treating a symptomatic VTE was ≥$20,000.00. CONCLUSIONS: The cost of a 3-week course of twice-daily aspirin or once-daily enoxaparin breaks even for VTE prophylaxis following shoulder arthroplasty and hemiarthroplasty if these drugs reduce the VTE rate by a calculated ARR. Given the lower rate of VTE observed for patients undergoing arthroscopic rotator cuff repair, only the 3-week course of aspirin broke even under these conditions. Once-daily enoxaparin did not break even at current market rate. Further research is needed to help determine optimal VTE prophylaxis after shoulder surgery.

Identifying robust adaptive irrigation operating policies to balance deeply uncertain economic food production and groundwater sustainability trade-offs.

Increasing irrigation demand has heavily relied on groundwater use, especially in places with highly variable water supplies that are vulnerable to drought. Groundwater management in agriculture is becoming increasingly challenging given the growing effects from overdraft and groundwater depletion worldwide. However, multiple challenges emerge when seeking to develop sustainable groundwater management in irrigated systems, such as trade-offs between the economic revenues from food production and groundwater resources, as well as the broad array of uncertainties in food-water systems. In this study we explore the applicability of Evolutionary Multi-Objective Direct Policy Search (EMODPS) to identify adaptive irrigation policies that water agencies and farmers can implement including operational decisions related to land use and groundwater use controls as well as groundwater pumping fees. The EMODPS framework yields state-aware, adaptive policies that respond dynamically as system state conditions change, for example with variable surface water (e.g., shifting management strategies across wet versus dry years). For this study, we focus on the Semitropic Water Storage district located in the San Joaquin Valley, California to provide broader insights relevant to ongoing efforts to improve groundwater sustainability in the state. Our findings demonstrate that adaptive irrigation policies can achieve sufficiently flexible groundwater management to acceptably balance revenue and sustainability goals across a wide range of uncertain future scenarios. Among the evaluated policy decisions, pumping restrictions and reductions in inflexible irrigation demands from tree crops are actions that can support dry-year pumping while maximizing groundwater storage recovery during wet years. Policies suggest that an adaptive pumping fee is the most flexible decision to control groundwater pumping and land use.

Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations.

Although social distancing can effectively contain the spread of infectious diseases by reducing social interactions, it may have economic effects. Crises such as the COVID-19 pandemic create dilemmas for policymakers because the long-term implementation of restrictive social distancing policies may cause massive economic damage and ultimately harm healthcare systems. This paper proposes an epidemic control framework that policymakers can use as a data-driven decision support tool for setting efficient social distancing targets. The framework addresses three aspects of the COVID-19 pandemic that are related to social distancing or community mobility data: modeling, financial implications, and policy-making. Thus, we explore the COVID-19 pandemic and concurrent economic situation as functions of historical pandemic data and mobility control. This approach allows us to formulate an efficient social distancing policy as a stochastic feedback control problem that minimizes the aggregated risks of disease transmission and economic volatility. We further demonstrate the use of a deep learning algorithm to solve this control problem. Finally, by applying our framework to U.S. data, we empirically examine the efficiency of the U.S. social distancing policy.

Insights from Adding Transportation Sector Detail into an Economy-Wide Model: The Case of the ADAGE CGE Model.

Computable general equilibrium (CGE) models provide valuable insights into economy-wide impacts of anticipated future structural changes in the transportation sector, yet few CGE models offer detailed transportation representations. We use an enhanced Applied Dynamic Analysis of the Global Economy (ADAGE) CGE model to incorporate disaggregated transportation modes and technologies in on-road passenger and freight transportation. We assess the impacts of these inclusions on U.S. transportation patterns, energy consumption and greenhouse gas emissions. Simulating illustrative global oil price cases with and without transportation detail, we find subsector mode disaggregation and technology additions in a CGE model significantly alter the impacts of oil prices on global trade and freight patterns, energy consumption, and greenhouse gas (GHG) emissions. We find that: (1) alternative technologies are essential for capturing transportation sector impacts, (2) electrification may reduce emissions with electricity decarbonization, and (3) higher oil prices may hasten electrification.

Economic feasibility of a novel tool to assist extubation decision-making: an early health economic modeling.

OBJECTIVES: To estimate the minimum percent change in failed extubation to make a tool designed to reduce extubation failure (Extubation Advisor [EA]) economically viable. METHODS: We conducted an early return on investment (ROI) analysis using data from intubated intensive care unit (ICU) patients at a large Canadian tertiary care hospital. We obtained input parameters from the hospital database and published literature. We ran generalized linear models to estimate the attributable length of stay, total hospital cost, and time to subsequent extubation attempt following failure. We developed a Markov model to estimate the expected ROI and performed probabilistic sensitivity analyses to assess the robustness of findings. Costs were presented in 2020 Canadian dollars (C$). RESULTS: The model estimated a 1 percent reduction in failed extubation could save the hospital C$289 per intubated patient (95 percent CI: 197, 459). A large center seeing 2,500 intubated ICU patients per year could save C$723,124/year/percent reduction in failed extubation. At the current annual price of C$164,221, the EA tool must reduce extubation failure by at least 0.24 percent (95 percent CI: .14, .41) to make the tool cost-effective at our site. CONCLUSIONS: Clinical decision-support tools like the EA may play an important role in reducing healthcare costs by reducing the rate of extubation failure, a costly event in the ICU.

Burden and Cost of Hospitalization for Respiratory Syncytial Virus in Young Children, Singapore.

Respiratory syncytial virus (RSV) is the most common cause of pediatric acute lower respiratory tract infection worldwide. Detailed data on the health and economic burden of RSV disease are lacking from tropical settings with year-round RSV transmission. We developed a statistical and economic model to estimate the annual incidence and healthcare cost of medically attended RSV disease among young children in Singapore, using Monte Carlo simulation to account for uncertainty in model parameters. RSV accounted for 708 hospitalizations in children <6 months of age (33.5/1,000 child-years) and 1,096 in children 6-29 months of age (13.2/1,000 child-years). The cost of hospitalization was SGD 5.7 million (US $4.3 million) at 2014 prices; patients bore 60% of the cost. RSV-associated disease burden in tropical settings in Asia is high and comparable to other settings. Further work incorporating efficacy data from ongoing vaccine trials will help to determine the potential cost-effectiveness of different vaccination strategies.

Improved feeding and forages at a crossroads: Farming systems approaches for sustainable livestock development in East Africa.

Dairy development provides substantial potential economic opportunities for smallholder farmers in East Africa, but productivity is constrained by the scarcity of quantity and quality feed. Ruminant livestock production is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, land-use change, and loss of biodiversity. Improved livestock feeding and forages have been highlighted as key entry point to sustainable intensification, increasing food security, and decreasing environmental trade-offs including GHG emission intensities. In this perspective article, we argue that farming systems approaches are essential to understand the multiple roles and impacts of forages in smallholder livelihoods. First, we outline the unique position of forages in crop-livestock systems and systemic obstacles to adoption that call for multidisciplinary thinking. Second, we discuss the importance of matching forage technologies with agroecological and socioeconomic contexts and niches, and systems agronomy that is required. Third, we demonstrate the usefulness of farming systems modeling to estimate multidimensional impacts of forages and for reducing agro-environmental trade-offs. We conclude that improved forages in East Africa are at a crossroads: if adopted by farmers at scale, they can be a cornerstone of pathways toward sustainable livestock systems in East Africa.

The Economic Case for the Prevention of Mental Illness.

Poor mental health has profound economic consequences. Given the burden of poor mental health, the economic case for preventing mental illness and promoting better mental health may be very strong, but too often prevention attracts little attention and few resources. This article describes the potential role that can be played by economic evidence alongside experimental trials and observational studies, or through modeling, to substantiate the need for increased investment in prevention. It illustrates areas of action across the life course where there is already a good economic case. It also suggests some further areas of substantive public health concern, with promising effectiveness evidence, that may benefit from economic analysis. Financial and economic barriers to implementation are then presented, and strategies to address the barriers and increase investment in the prevention of mental illness are suggested.

Challenges with Forecasting Budget Impact: A Case Study of Six ICER Reports.

BACKGROUND: Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact. OBJECTIVE: We examined how different modeling assumptions influenced the results of 6 BIMs from the Institute for Clinical and Economic Review (ICER). STUDY DESIGN: Retrospective analysis of pharmaceutical sales data. METHODS: From ICER reports issued before 2016, we collected estimates of 3 BIM outputs: aggregate therapy cost (ie, cost to treat the patient population with a particular therapy), therapy uptake, and price. We compared these against real-world estimates that we generated using drug sales data. We considered 2 classes of BIM estimates: those forecasting future uptake of new agents, which assumed "unmanaged uptake," and those describing the contemporaneous market state (ie, estimates of current, managed uptake and budget impact for compounds already on the market). RESULTS: Differences between ICER's estimates and our own were largest for forecasted studies. Here, ICER's uptake estimates exceeded real-world estimates by factors ranging from 7.4 (sacubitril/valsartan) to 54 (hepatitis C treatments). The "unmanaged uptake" assumption (removed from ICER's approach in 2017) yields large deviations between BIM estimates and real-world consumption. Nevertheless, in some cases, ICER's BIMs that relied on current market estimates also deviated substantially from real-world sales data. CONCLUSIONS: This study highlights challenges with forecasting budget impact. In particular, assumptions about uptake and data source selection can greatly influence the accuracy of results.

A novel hybrid modeling approach for the evaluation of integrated care and economic outcome in heart failure treatment.

BACKGROUND: Demographic changes, increased life expectancy and the associated rise in chronic diseases pose challenges to public health care systems. Optimized treatment methods and integrated concepts of care are potential solutions to overcome increasing financial burdens and improve quality of care. In this context modeling is a powerful tool to evaluate potential benefits of different treatment procedures on health outcomes as well as health care budgets. This work presents a novel modeling approach for simulating different treatment procedures of heart failure patients based on extensive data sets from outpatient and inpatient care. METHODS: Our hybrid heart failure model is based on discrete event and agent based methodologies and facilitates the incorporation of different therapeutic procedures for outpatient and inpatient care on patient individual level. The state of health is modeled with the functional classification of the New York Heart Association (NYHA), strongly affecting discrete state transition probabilities alongside age and gender. Cooperation with Austrian health care and health insurance providers allowed the realization of a detailed model structure based on clinical data of more than 25,000 patients. RESULTS: Simulation results of conventional care and a telemonitoring program underline the unfavorable prognosis for heart failure and reveal the correlation of NYHA classes with health and economic outcomes. Average expenses for the treatment of NYHA class IV patients of €10,077 ± €165 were more than doubled compared to other classes. The selected use case of a telemonitoring program demonstrated potential cost savings within two years of application. NYHA classes II and III revealed most potential for additional treatment measures. CONCLUSION: The presented model allows performing extensive simulations of established treatment procedures for heart failure patients and evaluating new holistic methods of care and innovative study designs. This approach offers health care providers a unique, adaptable and comprehensive tool for decision making in the complex and socioeconomically challenging field of cardiovascular diseases.

Impact of differences in adenoma and proximal serrated polyp detection rate on the long-term effectiveness of FIT-based colorectal cancer screening.

BACKGROUND: Both the adenoma detection rate (ADR) and proximal serrated polyp detection rate (PSPDR) vary among endoscopists. It is unclear how these variations influence colorectal cancer (CRC) screening effectiveness. We evaluated the effect of variation in these detection rates on the long-term impact of fecal immunochemical test (FIT) based screening. METHODS: The Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) model was set up to simulate the Dutch national biennial FIT-based CRC screening program between 2014 and 2044. Adherence to FIT and colonoscopy was 73 and 92%. Besides a 'no screening scenario', several screening scenarios varying in ADR and PSPDR were evaluated. Using the available literature on colonoscopy miss rates led to a base-case ADR of 59% and PSPDR of 11%, which were varied with intervals of 3 and 2%. RESULTS: Compared to no screening, FIT-screening in the base-case scenario reduced long-term mortality with 51.8%. At a fixed PSPDR of 11%, an increase in ADR from 44 to 62% would result in a 10.7% difference in mortality reduction. Using a fixed ADR of 59%, changing the PSPDR from 3 to 15% did not substantially influence long-term mortality (51.0 to 52.3%). CONCLUSIONS: An increase in ADR gradually reduces CRC burden in a FIT-based screening program, whereas an increase in PSPDR only minimally influences long-term outcomes at a population-level. The limited effect of the PSPDR can be explained by the limited sensitivity of FIT for serrated polyps (SPs). Other triage modalities aiming to detect relevant SPs should be explored.

"Pay for Success" Financing and Home-Based Multicomponent Childhood Asthma Interventions: Modeling Results From the Detroit Medicaid Population.

Policy Points: The Pay for Success (PFS) financing approach has potential for scaling the implementation of evidence-based prevention interventions in Medicaid populations, including a range of multicomponent interventions for childhood asthma that combine home environment risk mitigation with medical case management. Even though this type of intervention is efficacious and cost-saving among high-risk children with asthma, the main challenges for implementation in a PFS context include legal and regulatory barriers to capturing federal Medicaid savings and using them as a source of private investor repayment. Federal-level policy change and guidance are needed to support PFS financing of evidence-based interventions that would reduce expensive acute care among Medicaid enrollees. CONTEXT: Pay for Success has emerged as a potential financing mechanism for innovative and cost-effective prevention programs. In the PFS model, interventions that provide value to the public sector are implemented with financing from private investors who receive a payout from the government only if the metrics identified in a performance-based contract are met. In this nascent field, little has been written about the potential for and challenges of PFS initiatives that produce savings and/or value for Medicaid. METHODS: In order to elucidate the basic economics of a PFS intervention in a Medicaid population, we modeled the potential impact of an evidence-based multicomponent childhood asthma intervention among low-income children enrolled in Medicaid in Detroit. We modeled outcomes and a comparative benefit-cost analysis in 3 risk-based target groups: (1) all children with an asthma diagnosis; (2) children with an asthma-related emergency department visit in the past year; and (3) children with an asthma-related hospitalization in the past year. Modeling scenarios for each group produced estimates of potential state and federal Medicaid savings for different types or levels of investment, the time frames for savings, and some overarching challenges. FINDINGS: The PFS economics of a home-based asthma intervention are most viable if it targets children who have already experienced an expensive episode of asthma-related care. In a 7-year demonstration, the overall (undiscounted) modeled potential savings for Group 2 were $1.4 million for the federal Medicaid and $634,000 for the state Medicaid programs, respectively. Targeting children with at least 1 hospitalization in the past year (Group 3) produced estimated potential savings of $2.8 million to federal Medicaid and $1.3 million to state Medicaid. However, current Medicaid rules and regulations pose significant challenges for capturing federal Medicaid savings for PFS payouts. CONCLUSIONS: A multicomponent intervention that provides home remediation and medical case management to high-risk children with asthma has significant potential for PFS financing in urban Medicaid populations. However, there are significant administrative and payment challenges, including the limited ability to capture federal Medicaid savings and to use them as a source of investor repayment. Without some policy reform and clear guidance from the federal government, the financing burden of PFS outcome payments will be on the state Medicaid program or some other state-level funding source.