Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand.

OBJECTIVES: The purpose of this study is to evaluate the cost-effectiveness of increasing access to colorectal cancer (CRC) diagnosis, considering resource limitations in Thailand. METHODS: We analyzed the cost-effectiveness of increasing access to fecal immunochemical test screening (strategy I), symptom evaluation (strategy II), and their combination through healthcare and societal perspectives using Colo-Sim, a simulation model of CRC care. We extended our analysis by adding a risk-stratification score (RS) to the strategies. We analyzed all strategies under the currently limited annual colonoscopy capacity and sufficient capacity. We estimated quality-adjusted life-years (QALYs) and costs over 2023 to 2047 and performed sensitivity analyses. RESULTS: Annual costs for CRC care will increase over 25 years in Thailand, resulting in a cumulative cost of 323B Thai baht (THB). Each strategy results in higher QALYs gained and additional costs. With the current colonoscopy capacity and willingness-to-pay threshold of 160 000 THB, strategy I with and without RS is not cost-effective. Strategy II + RS is the most cost-effective, resulting in 0.68 million QALYs gained with additional costs of 66B THB. Under sufficient colonoscopy capacity, all strategies are deemed cost-effective, with the combined approach (strategy I + II + RS) being the most favorable, achieving the highest QALYs (1.55 million) at an additional cost of 131 billion THB. This strategy also maintains the highest probability of being cost-effective at any willingness-to-pay threshold above 96 000 THB. CONCLUSIONS: In Thailand, fecal immunochemical test screening, symptom evaluation, and RS use can achieve the highest QALYs; however, boosting colonoscopy capacity is essential for cost-effectiveness.

Experimental and simulation investigation on suppressing thermal runaway in battery pack.

In order to address the issue of suppressing thermal runaway (TR) in power battery, a thermal generation model for power batteries was established and then modified based on experimental data. On the basis of simulation calculations, a scheme was designed to suppress thermal runaway of the battery module and battery pack, and samples were produced for testing. The results of the test and simulation calculations were very consistent, confirming the accuracy of the simulation calculation model. The results of thermal runaway test also demonstrate that the measures designed to suppress thermal runaway are effective and meet the design requirements.

Factors limiting the potential range expansion of lodgepole pine in Interior Alaska.

Understanding the factors influencing species range limits is increasingly crucial in anticipating migrations due to human-caused climate change. In the boreal biome, ongoing climate change and the associated increases in the rate, size, and severity of disturbances may alter the distributions of boreal tree species. Notably, Interior Alaska lacks native pine, a biogeographical anomaly that carries implications for ecosystem structure and function. The current range of lodgepole pine (Pinus contorta var. latifolia) in the adjacent Yukon Territory may expand into Interior Alaska, particularly with human assistance. Evaluating the potential for pine expansion in Alaska requires testing constraints on range limits such as dispersal limitations, environmental tolerance limits, and positive or negative biotic interactions. In this study, we used field experiments with pine seeds and transplanted seedlings, complemented by model simulations, to assess the abiotic and biotic factors influencing lodgepole pine seedling establishment and growth after fire in Interior Alaska. We found that pine could successfully recruit, survive, grow, and reproduce across our broadly distributed network of experimental sites. Our results show that both mammalian herbivory and competition from native tree species are unlikely to constrain pine growth and that environmental conditions commonly found in Interior Alaska fall well within the tolerance limits for pine. If dispersal constraints are released, lodgepole pine could have a geographically expansive range in Alaska, and once established, its growth is sufficient to support pine-dominated stands. Given the impacts of lodgepole pine on ecosystem processes such as increases in timber production, carbon sequestration, landscape flammability, and reduced forage quality, natural or human-assisted migration of this species is likely to substantially alter responses of Alaskan forest ecosystems to climate change.

Design and study of mine silo drainage method based on fuzzy control and Avoiding Peak Filling Valley strategy.

Coal is a non-renewable fossil energy source on which humanity relies heavily, and producing one ton of raw coal requires the discharge of 2-7 tons of mine water from the ground. The huge drainage task increases the cost of coal mining in coal mines significantly, so saving the drainage cost while guaranteeing the safe production of coal mines is a problem that needs to be solved urgently. Most of the fuzzy controllers used in the traditional dynamic planning methods applied to mine drainage are two-dimensional fuzzy controllers with limited control effect, so the traditional two-dimensional fuzzy controllers are improved by introducing the rate of change of gushing water to form a three-dimensional fuzzy controller with three-dimensional control of instantaneous section-water level-rate of change of gushing water, and at the same time, the optimized dynamic planning method is designed by combining the Avoiding Peak Filling Valley strategy and the optimal dy-namic planning method is used in conjunction with the un-optimized dynamic planning method. The optimized dynamic planning method is applied to the same coal mine water silo gushing water experiments; experimental comparison found that the pumping station system before the optimi-zation of the electricity consumed is 52,586 yuan/day, while after the optimization of the electricity consumed is reduced to 41,692 yuan/day, the cost per day consumed compared with the previous reduction of 20.69%, a year can be saved 3,969,730 yuan. Therefore, the mine water bin drainage method based on fuzzy control and Avoiding Peak Filling Valley strategy proposed in this paper can be used as an improvement method of the existing mine drainage method, which can further ex-pand the economic benefits of coal mines and realize safe production while realizing cost savings.

Inclusion of marginalized populations in HPV vaccine modeling: A systematic review.

OBJECTIVE: Models simulating the potential impacts of Human Papillomavirus (HPV) vaccine have been used globally to guide vaccination policies and programs. We sought to understand how and why marginalized populations have been incorporated into HPV vaccine simulation models. METHODS: We conducted a systematic search of PubMed, CINAHL, Scopus, and Embase to identify studies using simulation models of HPV vaccination incorporating one or more marginalized population through stratification or subgroup analysis. We extracted data on study characteristics and described these overall and by included marginalized groups. RESULTS: We identified 36 studies that met inclusion criteria, which modeled vaccination in 21 countries. Models included men who have sex with men (MSM; k = 16), stratification by HIV status (k = 9), race/ethnicity (k = 6), poverty (k = 5), rurality (k = 4), and female sex workers (k = 1). When evaluating for a marginalized group (k = 10), HPV vaccination was generally found to be cost-effective, including for MSM, individuals living with HIV, and rural populations. In studies evaluating equity in cancer prevention (k = 9), HPV vaccination generally advanced equity, but this was sensitive to differences in HPV vaccine uptake and use of absolute or relative measures of inequities. Only one study assessed the impact of an intervention promoting HPV vaccine uptake. DISCUSSION: Incorporating marginalized populations into decision models can provide valuable insights to guide decision making and improve equity in cancer prevention. More research is needed to understand the equity impact of HPV vaccination on cancer outcomes among marginalized groups. Research should emphasize implementation - including identifying and evaluating specific interventions to increase HPV vaccine uptake.

Assessing the properties of patient-specific treatment effect estimates from causal forest algorithms under essential heterogeneity.

BACKGROUND: Treatment variation from observational data has been used to estimate patient-specific treatment effects. Causal Forest Algorithms (CFAs) developed for this task have unknown properties when treatment effect heterogeneity from unmeasured patient factors influences treatment choice - essential heterogeneity. METHODS: We simulated eleven populations with identical treatment effect distributions based on patient factors. The populations varied in the extent that treatment effect heterogeneity influenced treatment choice. We used the generalized random forest application (CFA-GRF) to estimate patient-specific treatment effects for each population. Average differences between true and estimated effects for patient subsets were evaluated. RESULTS: CFA-GRF performed well across the population when treatment effect heterogeneity did not influence treatment choice. Under essential heterogeneity, however, CFA-GRF yielded treatment effect estimates that reflected true treatment effects only for treated patients and were on average greater than true treatment effects for untreated patients. CONCLUSIONS: Patient-specific estimates produced by CFAs are sensitive to why patients in real-world practice make different treatment choices. Researchers using CFAs should develop conceptual frameworks of treatment choice prior to estimation to guide estimate interpretation ex post.

Density-Dependent Selection during Range Expansion Affects Expansion Load in Life History Traits.

AbstractModels of range expansion have independently explored fitness consequences of life history trait evolution and increased rates of genetic drift-or "allele surfing"-during spatial spread, but no previous model has examined the interactions between these two processes. Here, using spatially explicit simulations, we explore an ecologically complex range expansion scenario that combines density-dependent selection with allele surfing to asses the genetic and fitness consequences of density-dependent selection on the evolution of life history traits. We demonstrate that density-dependent selection on the range edge acts differently depending on the life history trait and can either diminish or enhance allele surfing. Specifically, we show that selection at the range edge is always weaker at sites affecting competitive ability (K-selected traits) than at sites affecting birth rate (r-selected traits). We then link differences in the frequency of deleterious mutations to differences in the efficacy of selection and rate of mutation accumulation across distinct life history traits. Finally, we demonstrate that the observed fitness consequences of allele surfing depend on the population density in which expansion load is measured. Our work highlights the complex relationship between ecology and expressed genetic load, which will be important to consider when interpreting both experimental and field studies of range expansion.

Possible mechanisms and simulation modeling of FLASH radiotherapy.

FLASH radiotherapy (FLASH-RT) has great potential to improve patient outcomes. It delivers radiation doses at an ultra-high dose rate (UHDR: ≥ 40 Gy/s) in a single instant or a few pulses. Much higher irradiation doses can be administered to tumors with FLASH-RT than with conventional dose rate (0.01-0.40 Gy/s) radiotherapy. UHDR irradiation can suppress toxicity in normal tissues while sustaining antitumor efficiency, which is referred to as the FLASH effect. However, the mechanisms underlying the effects of the FLASH remain unclear. To clarify these mechanisms, the development of simulation models that can contribute to treatment planning for FLASH-RT is still underway. Previous studies indicated that transient oxygen depletion or augmented reactions between secondary reactive species produced by irradiation may be involved in this process. To discuss the possible mechanisms of the FLASH effect and its clinical potential, we summarized the physicochemical, chemical, and biological perspectives as well as the development of simulation modeling for FLASH-RT.

Measure Twice, Change Once: Using Simulation to Support Change Management in Rural Healthcare Delivery.

Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

Personalizing age of gastric cancer screening based on comorbidity in China: Model estimates of benefits, affordability and cost-effectiveness optimization.

The benefits of gastric cancer screening are related to age and comorbidity status, but reliable estimates are lacking in China. This study aimed to estimate the benefits and affordability of the gastric cancer screening strategy by level of comorbidity to inform decisions to screening age. We assessed six current gastric cancer screening strategies in China using a microsimulation model with different starting and stopping ages and comorbidity profiles, for a total of 378 strategies. 1,000,000 individuals were simulated in the model and followed the alternative strategies. Primary outcomes included gastric cancer incidence, the number of endoscopy and complications, life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Future costs and QALYs are discounted by 5% per year. Sensitivity analyses were used to evaluate model uncertainty. Strategies with longer screening durations were associated with higher benefits of life-year gained and gastric cancer deaths averted, but were also accompanied by a large number of endoscopy screening, and complication events. Using the threshold of US$18,575 per QALY gained, at the no, moderate, and severe comorbidity level, the leading cost-effectiveness strategies were the new gastric cancer screening scoring system strategy (NGCS) screening from age 40 years to 60 years (40-60), 40-55-NGCS, and 40-55-NGCS strategy, respectively. The results are robust in sensitivity analyses. Our study illustrates the importance of considering comorbidity conditions and age when determining the starting and stopping screening age for gastric cancer and informs the discussion on personalizing decisions. The trade-off between benefits and harms can also be referenced when necessary.

Modeling Thyroid Cancer Epidemiology in the United States Using Papillary Thyroid Carcinoma Microsimulation Model.

OBJECTIVES: Thyroid cancer incidence increased over 200% from 1992 to 2018, whereas mortality rates had not increased proportionately. The increased incidence has been attributed primarily to the detection of subclinical disease, raising important questions related to thyroid cancer control. We developed the Papillary Thyroid Carcinoma Microsimulation model (PATCAM) to answer them, including the impact of overdiagnosis on thyroid cancer incidence. METHODS: PATCAM simulates individuals from age 15 until death in birth cohorts starting from 1975 using 4 inter-related components, including natural history, detection, post-diagnosis, and other-cause mortality. PATCAM was built using high-quality data and calibrated against observed age-, sex-, and stage-specific incidence in the United States as reported by the Surveillance, Epidemiology, and End Results database. PATCAM was validated against US thyroid cancer mortality and 3 active surveillance studies, including the largest and longest running thyroid cancer active surveillance cohort in the world (from Japan) and 2 from the United States. RESULTS: PATCAM successfully replicated age- and stage-specific papillary thyroid cancers (PTC) incidence and mean tumor size at diagnosis and PTC mortality in the United States between 1975 and 2015. PATCAM accurately predicted the proportion of tumors that grew more than 3 mm and 5 mm in 5 years and 10 years, aligning with the 95% confidence intervals of the reported rates from active surveillance studies in most cases. CONCLUSIONS: PATCAM successfully reproduced observed US thyroid cancer incidence and mortality over time and was externally validated. PATCAM can be used to identify factors that influence the detection of subclinical PTCs.

Using neural networks to calibrate agent based models enables improved regional evidence for vaccine strategy and policy.

Distribution and administration strategy are critical to successful population immunization efforts. Agent-based modeling (ABM) can reflect the complexity of real-world populations and can experimentally evaluate vaccine strategy and policy. However, ABMs historically have been limited in their time-to-development, long runtime, and difficulty calibrating. Our team had several technical advances in the development of our GradABMs: a novel class of scalable, fast and differentiable simulations. GradABMs can simulate million-size populations in a few seconds on commodity hardware, integrate with deep neural networks and ingest heterogeneous sources. This allows for rapid and real-world sensitivity analyses. Our first epidemiological GradABM (EpiABMv1) enabled simulation interventions over real million-scale populations and was used in vaccine strategy and policy during the COVID-19 pandemic. Literature suggests decisions aided by evidence from these models saved thousands of lives. Our most recent model (EpiABMv2) extends EpiABMv1 to allow improved regional calibration using deep neural networks to incorporate local population data, and in some cases different policy recommendations versus our prior models. This is an important advance for our model to be more effective at vaccine strategy and policy decisions at the local public health level.

Dynamics of colorectal cancer screening in low and middle-income countries: A modeling analysis from Thailand.

BACKGROUND: Low and middle-income countries face constraints for early colorectal cancer (CRC) detection, including restricted access to care and low colonoscopy capacity. Considering these constraints, we studied strategies for increasing access to early CRC detection and reducing CRC progression and mortality rates in Thailand. METHODS: We developed a system dynamics model to simulate CRC death and progression trends. We analyzed the impacts of increased access to screening via fecal immunochemical test and colonoscopy, improving access to CRC diagnosis among symptomatic individuals, and their combination. RESULTS: Projecting the status quo (2023-2032), deaths per 100K people increase from 87.5 to 115.4, and CRC progressions per 100K people rise from 131.8 to 159.8. In 2032, improved screening access prevents 2.5 CRC deaths and 2.5 progressions per 100K people, with cumulative prevented 7K deaths and 9K progressions, respectively. Improved symptom evaluation access prevents 7.5 CRC deaths per 100K with no effect on progression, totaling 35K saved lives. A combined approach prevents 9.3 deaths and 1.8 progressions per 100K, or 41K and 7K cumulatively. The combined strategy prevents most deaths; however, there is a tradeoff: It prevents fewer CRC progressions than screening access improvement. Increasing the current annual colonoscopy capacity (200K) to sufficient capacity (681K), the combined strategy achieves the best results, preventing 15.0 CRC deaths and 10.3 CRC progressions per 100K people, or 54K and 30K cumulatively. CONCLUSION: Until colonoscopy capacity increases, enhanced screening and symptom evaluation are needed simultaneously to curb CRC deaths, albeit not the best strategy for CRC progression prevention.

Mortality, incarceration and cost implications of fentanyl felonization laws: A modeling study.

BACKGROUND: Opioid overdose continues to be a major cause of death in the United States. One effort to control opioid use has been to implement policies that enhance criminalization of opioid possession. Laws to further criminalize possession of fentanyl have been enacted or are under consideration across the country, including at the national level. OBJECTIVE: Estimate the long-term effects on opioid death and incarceration resulting from increasingly strict fentanyl possession laws . DESIGN: We built a Markov simulation model to explore the potential outcomes of a 2022 Colorado law which made possession of >1 g of drug with any amount of fentanyl a Level 4 drug felony (and escalation of the previous law, where >4 g of any drug with any amount of fentanyl in possession was considered a felony). The model simulates a cohort of people with fentanyl possession moving through the criminal justice system, exploring the probability of overdose and incarceration under different scenarios, including various fentanyl possession policies and potential interventions. SETTING: Colorado PARTICIPANTS: A simulated cohort of people in possession of fentanyl. MEASUREMENTS: Number of opioid overdose deaths, people incarcerated, and associated costs over 5 years. RESULTS: When >4 g of a drug containing any amount of fentanyl is considered a felony in Colorado, the model predicts 5460 overdose deaths (95% CrI 410-9260) and 2,740 incarcerations for fentanyl possession (95% CrI: 230-10,500) over 5 years. When the policy changes so that >1 g possession of drug with fentanyl is considered a felony, opioid overdose deaths increase by 19% (95% CRI: 16-38%) and incarcerations for possession increase by 98% (CrI: 85-98%). Diversion programs and MOUD in prison help alleviate some of the increases in death and incarceration, but do not completely offset them. LIMITATIONS: The mathematical model is meant to offer broad assessment of the impact of these policies, not forecast specific and exact numerical outcomes. CONCLUSIONS: Our model shows that lowering thresholds for felony possession of fentanyl containing drugs can lead to more opioid overdose deaths and incarceration.

Time Series Electrical Motor Drives Forecasting Based on Simulation Modeling and Bidirectional Long-Short Term Memory.

Accurately forecasting electrical signals from three-phase Direct Torque Control (DTC) induction motors is crucial for achieving optimal motor performance and effective condition monitoring. However, the intricate nature of multiple DTC induction motors and the variability in operational conditions present significant challenges for conventional prediction methodologies. To address these obstacles, we propose an innovative solution that leverages the Fast Fourier Transform (FFT) to preprocess simulation data from electrical motors. A Bidirectional Long Short-Term Memory (Bi-LSTM) network then uses this altered data to forecast processed motor signals. Our proposed approach is thoroughly examined using a comparative examination of cutting-edge forecasting models such as the Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). This rigorous comparison underscores the remarkable efficacy of our approach in elevating the precision and reliability of forecasts for induction motor signals. The results unequivocally establish the superiority of our method across stator and rotor current testing data, as evidenced by Mean Absolute Error (MAE) average results of 92.6864 and 93.8802 for stator and rotor current data, respectively. Additionally, compared to alternative forecasting models, the Root Mean Square Error (RMSE) average results of 105.0636 and 85.7820 underscore reduced prediction loss.

The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review.

The effectiveness and cost of a public health intervention is dependent on complex human behaviors, yet health economic models typically make simplified assumptions about behavior, based on little theory or evidence. This paper reviews existing methods across disciplines for incorporating behavior within simulation models, to explore what methods could be used within health economic models and to highlight areas for further research. This may lead to better-informed model predictions. The most promising methods identified which could be used to improve modeling of the causal pathways of behavior-change interventions include econometric analyses, structural equation models, data mining and agent-based modeling; the latter of which has the advantage of being able to incorporate the non-linear, dynamic influences on behavior, including social and spatial networks. Twenty-two studies were identified which quantify behavioral theories within simulation models. These studies highlight the importance of combining individual decision making and interactions with the environment and demonstrate the importance of social norms in determining behavior. However, there are many theoretical and practical limitations of quantifying behavioral theory. Further research is needed about the use of agent-based models for health economic modeling, and the potential use of behavior maintenance theories and data mining.

Projected Benefits of Long-Acting Antiretroviral Therapy in Nonsuppressed People With Human Immunodeficiency Virus Experiencing Adherence Barriers.

Background: In a demonstration project, long-acting, injectable cabotegravir-rilpivirine (CAB-RPV) achieved viral suppression in a high proportion of people with HIV (PWH) who were virologically nonsuppressed with adherence barriers. We projected the long-term impact of CAB-RPV for nonsuppressed PWH experiencing adherence barriers. Methods: Using the Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model, we compared 3 strategies: (1) standard of care oral integrase inhibitor-based ART (INSTI); (2) INSTI-based ART with supportive social services ("wraparound services" [WS]) (INSTI/WS); and (3) CAB-RPV with WS (CAB-RPV/WS). Model outcomes included viral suppression (%) and engagement in care (%) at 3 years, and life expectancy (life-years [LYs]). Base case cohort characteristics included mean age of 47y (standard deviation [SD], 10y), 90% male at birth, and baseline mean CD4 count 150/µL (SD, 75/µL). Viral suppression at 3 months was 13% (INSTI), 28% (INSTI/WS), and 60% (CAB-RPV/WS). Mean loss to follow-up was 28/100 person-years (PY) (SD, 2/100 PY) without WS and 16/100 PY (SD, 1/100 PY) with WS. Results: Projected viral suppression at 3 years would vary widely: 16% (INSTI), 38% (INSTI/WS), and 44% (CAB-RPV/WS). Life expectancy would be 7.4 LY (INSTI), 9.0 LY (INSTI/WS), and 9.4 LY (CAB-RPV/WS). Projected benefits over oral ART would be greater for PWH initiating CAB-RPV/WS at lower CD4 counts. Across plausible key parameter ranges, CAB-RPV/WS would improve viral suppression and life expectancy compared with oral INSTI strategies. Conclusions: These model-based results support that long-acting injectable CAB-RPV with extensive support services for nonsuppressed PWH experiencing adherence barriers is likely to increase viral suppression and improve survival. A prospective study to provide further evidence is needed.

Modeling the influence of safety aid market penetration on traffic safety: Case of collision warning system for powered two-wheelers.

Every year, several thousand powered two-wheeler (PTW) i.e., motorcycle, moped and scooter drivers and passengers die in traffic accidents in the EU. Despite the much higher risk of death and injuries for PTW vs. car users, there is a three-fold lack regarding collision warning technologies for PTWs: lack of research, lack of regulation and lack of availability in the market. Many injuries occur in rear-end collisions, when PTW is struck from the rear by another vehicle. In this paper we present a hybrid, multi-method simulation model that allows simulation of various situations in which a vehicle may collide with the rear end of a PTW. We have used this model to estimate the potential impact of market penetration of a novel PTW ESS + RECAS system, named MEBWS (Motorcycle Emergency Braking Warning System), within the EU on the number of traffic accidents and their consequences, which would contribute to the EU "Vision Zero" goal: "reduce road deaths to almost zero by 2050". MEBWS has been developed at the Faculty of Information Studies in Novo mesto and patented. Simulation results using EU traffic accident data show that with 100% market penetration of the MEBWS system in the EU, the total number of PTW rear-end collisions would decrease by 29.50%. This reduction would result in fewer injuries and a decrease in economic crash costs by €43,145,172, according to the standard EU methodology. With the MEBWS system enabled, the number of traffic accidents in the standard rear-end collision emergency braking scenarios Moto, normal drive, Moto, emergency stop and Moto, not moving decreased by 33.15%, 27.76% and 28.76%, respectively. In cases where the collision could not be prevented due to slow response of the following driver or very high relative speed of the vehicles, MEBWS reduced the relative speed at impact, resulting in a reduction of injury severity by up to 11.198%, as estimated by the amount of kinetic energy released at collision.

An Insurance Value Modeling Approach That Captures the Wider Value of a Novel Antimicrobial to Health Systems, Patients, and the Population.

Background: Traditional health economic evaluations of antimicrobials currently underestimate their value to wider society. They can be supplemented by additional value elements including insurance value, which captures the value of an antimicrobial in preventing or mitigating impacts of adverse risk events. Despite being commonplace in other sectors, constituents of the impacts and approaches for estimating insurance value have not been investigated. Objectives: This study assessed the insurance value of a novel gram-negative antimicrobial from operational healthcare, wider population health, productivity, and informal care perspectives. Methods: A novel mixed-methods approach was used to model insurance value in the United Kingdom: (1) literature review and multidisciplinary expert workshops to identify risk events for 4 relevant scenarios: ward closures, unavoidable shortage of conventional antimicrobials, viral respiratory pandemics, and catastrophic antimicrobial resistance (AMR); (2) parameterizing mitigable costs and frequencies of risk events across perspectives and scenarios; (3) estimating insurance value through a Monte Carlo simulation model for extreme events and a dynamic disease transmission model. Results: The mean insurance value across all scenarios and perspectives over 10 years in the UK was £718 million, should AMR remain unchanged, where only £134 million related to operational healthcare costs. It would be 50%-70% higher if AMR steadily increased or if a more risk-averse view (1-in-10 year downside) of future events is taken. Discussion: The overall insurance value if AMR remains at current levels (a conservative projection), is over 5 times greater than insurance value from just the operational healthcare costs perspective, traditionally the sole perspective used in health budgeting. Insurance value was generally larger for nationwide or universal (catastrophic AMR, pandemic, and conventional antimicrobial shortages) rather than localized (ward closure) scenarios, across perspectives. Components of this insurance value match previously published estimates of operational costs and mortality impacts. Conclusions: Insurance value of novel antimicrobials can be systematically modeled and substantially augments their traditional health economic value in normal circumstances. These approaches are generalizable to similar health interventions and form a framework for health systems and governments to capture broader value in health technology assessments, improve healthcare access, and increase resilience by planning for adverse scenarios.

'Drive the doctor' for endovascular thrombectomy in a rural area: a simulation study.

BACKGROUND: Patients who present in a primary stroke center (PSC) with ischemic stroke are usually transferred to a comprehensive stroke center (CSC) in case of a large vessel occlusion (LVO) for endovascular thrombectomy (EVT) treatment, the so-called 'drip-and-ship' (DS) model. The 'drive-the-doctor' (DD) model modifies the DS model by allowing mobile interventionalists (MIs) to transfer to an upgraded PSC acting as a thrombectomy capable stroke center (TSC), instead of transferring patients to a CSC. Using simulation we estimated time savings and impact on clinical outcome of DD in a rural region. METHODS: Data from EVT patients in northern Netherlands was prospectively collected in the MR CLEAN Registry between July 2014 - November 2017. A Monte Carlo simulation model of DS patients served as baseline model. Scenarios included regional spread of TSCs, pre-hospital patient routing to 'the nearest PSC' or 'nearest TSC', MI's notification after LVO confirmation or earlier prehospital, and MI's transport modalities. Primary outcomes are onset to groin puncture (OTG) and predicted probability of favorable outcome (PPFO) (mRS 0-2). RESULTS: Combining all scenarios OTG would be reduced by 28-58 min and PPFO would be increased by 3.4-7.1%. Best performing and acceptable scenario was a combination of 3 TSCs, prehospital patient routing based on the RACE scale, MI notification after LVO confirmation and MI's transfer by ambulance. OTG would reduce by 48 min and PPFO would increase by 5.9%. CONCLUSIONS: A DD model is a feasible scenario to optimize acute stroke services for EVT eligible patients in rural regions. Key design decisions in implementing the DD model for a specific region are regional spread of TSCs, patient routing strategy, and MI's notification moment and transport modality.