Impact Of Parameter Uncertainty Research Articles

Consistent asset modelling with random coefficients and switches between regimes

We explore a stochastic model that enables capturing external influences in two specific ways. The model allows for the expression of uncertainty in the parametrisation of the stochastic dynamics and incorporates patterns to account for different behaviours across various times or regimes. To establish our framework, we initially construct a model with random parameters, where the switching between regimes can be dictated either by random variables or deterministically. Such a model is highly interpretable. We further ensure mathematical consistency by demonstrating that the framework can be elegantly expressed through local volatility models taking the form of standard jump diffusions. Additionally, we consider a Markov-modulated approach for the switching between regimes characterised by random parameters. For all considered models, we derive characteristic functions, providing a versatile tool with wide-ranging applications. In a numerical experiment, we apply the framework to the financial problem of option pricing. The impact of parameter uncertainty is analysed in a two-regime model, where the asset process switches between periods of high and low volatility imbued with high and low uncertainty, respectively.

An Economic Analysis of SC24 in Canada: A Randomized Study of SBRT Compared With Conventional Palliative RT for Spinal Metastases

Purposexx.xx was a multicenter randomized controlled phase 2/3 trial conducted in Canada and Australia. Patients with painful spinal metastases were randomized to either 24 Gy/2 stereotactic body radiotherapy (SBRT) or 20 Gy/5 conventional external beam radiotherapy (CRT). The study met its primary endpoint demonstrating superior complete pain response rates (CRR) at 3 months following SBRT (35%) vs CRT (14%). SBRT planning and delivery is resource intensive. Given its benefits in xx.xx, we performed an economic analysis to determine the incremental cost-effectiveness of SBRT compared to CRT. MethodsThe trial recruited 229 patients. Cost-effectiveness was assessed using a Markov model taking into account observed survival, treatments costs, including retreatment, and quality of life (QoL) over the lifetime of the patient. The EORTC-QLU-C10D was used to determine QoL values. Transition probabilities for outcomes were from available patient data. Health system costs were from the Canadian health care perspective and based on 2021 Canadian dollars (CDN). The incremental cost-effectiveness ratio (ICER) was expressed as the ratio of incremental cost to quality-adjusted life years (QALY). Impact of parameter uncertainty was investigated using deterministic and probabilistic sensitivity analyses. RESULTSThe base case for SBRT compared to CRT had an ICER of $9,040CDN per QALY gained. Sensitivity analyses demonstrated that the ICER was most sensitive to variations in the utility assigned to the “No local failure” ($5,457CDN to $241,051CDN per QALY), adopting low and high estimates of utility) and the cost of the SBRT (ICERs ranging from $7,345 to $123,361CDN per QALY). It was more robust to variations in assumptions around survival and the response rate. ConclusionsSBRT is associated with higher upfront costs compared to CRT. The ICER shows that, within the Canadian health care system, SBRT with 2 fractions is likely to be cost-effective relative to CRT.

Cost-Effectiveness Analysis of Light Adjustable Lens Compared to Monofocal Intraocular Lens in Cataract Surgery.

To analyze the cost-effectiveness of the Light Adjustable Lens (LAL; RxSight) in comparison to a monofocal intraocular lens (IOL) for individuals undergoing cataract surgery in both eyes. A cost-effectiveness analysis was performed using a Markov model that simulated the patient outcomes and costs associated with undergoing cataract surgery with the LAL or monofocal IOL. Cost-effectiveness was determined using the incremental cost-effectiveness ratio (ICER), a measure that quantifies the incremental cost in dollars per quality-adjusted life year (QALY) gained. Treatments with the ICER below the willingness-to-pay threshold (WTP) of $50,000/QALY were considered cost-effective. The model was also evaluated for the impact of uncertainties in parameters using one-way sensitivity and probabilistic sensitivity analyses. The cost-effectiveness analysis showed that the LAL is cost-effective compared to monofocal IOLs in patients undergoing cataract surgery, with ICERs of $9,792/QALY (health care perspective) and $10,072/QALY (societal perspective) both significantly below the WTP. The model was most sensitive to patient age, market cost of the LAL, and proportion of patients with residual astigmatism following cataract surgery. The probabilistic sensitivity analysis showed that cataract surgeries in patients starting at age 65 years were cost-effective in 94% of the simulations at a WTP of $50,000/QALY. From both health care and societal perspectives, the study shows cataract surgeries performed with the LAL are cost-effective when compared to those performed with a monofocal IOL. More studies are needed to compare the LAL to other premium lenses that also provide patients with excellent visual outcomes at a higher cost. [J Refract Surg. 2023;39(11):777-782.].

Pricing quanto options with market liquidity risk.

This paper investigates the pricing problem of quanto options with market liquidity risk using the Bayesian method. The increasing volatility of global financial markets has made liquidity risk a significant factor that should be taken into consideration while evaluating option prices. To address this issue, we first derive the pricing formula for quanto options with liquidity risk. Next, we construct a likelihood function to conduct posterior inference on model parameters. We then propose a numerical algorithm to conduct statistical inferences on the option prices based on the posterior distribution. This proposed method considers the impact of parameter uncertainty on option prices. Finally, we conduct a comparison between the Bayesian method and traditional estimation methods to examine their validity. Empirical results show that our proposed method is feasible for pricing and predicting quanto options with liquidity risk, particularly for parameter estimations with a small sample size.

Control of the lifecycle of a technological complex for the rectification of multicomponent mixtures under conditions of parameter uncertainty

Input parameter uncertainty is paid more attention among such parameters as parameter uncertainty, model uncertainty, choice uncertainty under variability, spatial variability uncertainty, temporal variability uncertainty, inter-site variability uncertainty. When the technological component changes, the control starts working again based on a new paradigm of internal and external circuits. The possibility of using the Monte Carlo method for the analysis and estimation of the uncertainty of input parameters is presented. In the analysis of the uncertainties of the input parameters, the simplification of the selection process and the probability density functions were used. Deviations from the normal distribution were represented by a matrix transformation. The technological function of the rectification complex is presented in an expanded form, the uncertainty of parameters and control actions are highlighted separately. The influence of the uncertainty of actions and the uncertainty of input parameters on the functions performed by the technological complex, the functions of planning and coordination is analyzed. It is argued that the impact of parameter uncertainty on these functions has a direct impact on the state of the complex in its lifecycle.

Robustness of Proactive Intensive Care Unit Transfer Policies

Patients whose transfer to the intensive care unit (ICU) is unplanned are prone to higher mortality rates. In “Robustness of Proactive Intensive Care Unit Transfer Policies,” the authors study the problem of finding robust patient transfer policies to the ICU, which account for uncertainty in statistical estimates because of data limitations when optimizing to improve overall patient care. Under general assumptions, it is shown that an optimal transfer policy has a threshold structure. A robust policy also has a threshold structure, and it is more aggressive in transferring patients than the optimal nominal policy, which does not consider parameter uncertainty. The sensitivity of various hospital metrics to small changes in the parameters is highlighted using a data set of close to 300,000 hospitalizations at 21 Kaiser Permanente Northern California hospitals. This work provides useful insights into the impact of parameter uncertainty on deriving simple policies for proactive ICU transfer that have strong empirical performance and theoretical guarantees.

Nonlinear Reactor Design Optimization With Embedded Microkinetic Model Information

Despite the success of multiscale modeling in science and engineering, embedding molecular-level information into nonlinear reactor design and control optimization problems remains challenging. In this work, we propose a computationally tractable scale-bridging approach that incorporates information from multi-product microkinetic (MK) models with thousands of rates and chemical species into nonlinear reactor design optimization problems. We demonstrate reduced-order kinetic (ROK) modeling approaches for catalytic oligomerization in shale gas processing. We assemble a library of six candidate ROK models based on literature and MK model structure. We find that three metrics—quality of fit (e.g., mean squared logarithmic error), thermodynamic consistency (e.g., low conversion of exothermic reactions at high temperatures), and model identifiability—are all necessary to train and select ROK models. The ROK models that closely mimic the structure of the MK model offer the best compromise to emulate the product distribution. Using the four best ROK models, we optimize the temperature profiles in staged reactors to maximize conversions to heavier oligomerization products. The optimal temperature starts at 630–900K and monotonically decreases to approximately 560 K in the final stage, depending on the choice of ROK model. For all models, staging increases heavier olefin production by 2.5% and there is minimal benefit to more than four stages. The choice of ROK model, i.e., model-form uncertainty, results in a 22% difference in the objective function, which is twice the impact of parametric uncertainty; we demonstrate sequential eigendecomposition of the Fisher information matrix to identify and fix sloppy model parameters, which allows for more reliable estimation of the covariance of the identifiable calibrated model parameters. First-order uncertainty propagation determines this parametric uncertainty induces less than a 10% variability in the reactor optimization objective function. This result highlights the importance of quantifying model-form uncertainty, in addition to parametric uncertainty, in multi-scale reactor and process design and optimization. Moreover, the fast dynamic optimization solution times suggest the ROK strategy is suitable for incorporating molecular information in sequential modular or equation-oriented process simulation and optimization frameworks.

Based on a Markov model, cost-effectiveness analysis of influenza vaccination among people aged 60 years and older in Shenzhen

Objective: To assess the cost-effectiveness of influenza vaccination among people aged 60 years and older in Shenzhen. Methods: A Markov state transition model was constructed to evaluate the cost-effectiveness of annual influenza vaccination for preventing influenza infection compared with no vaccination among the elderly from the social perspective. Allowing seasonal variation of influenza activity, the model followed a five-year cohort using weekly cycles. We employed once the Chinese gross domestic product (GDP) per capita in 2019 (70 892 yuan) as the willingness-to-pay (WTP) threshold and calculated the net monetary benefit (NMB) with costs and quality-adjusted life-years (QALYs) discounted at 5% annually. The impact of parameter uncertainty on the results was examined using one-way and probabilistic sensitivity analyses (PSA). Results: The base case amounted to approximately 35 yuan of cost-saving and a net gain of 0.007 QALYs. Correspondingly, the NMB was 529 yuan per vaccinated person. One-way sensitivity analyses showed that the NMB was relatively sensitive to changes in the attack rate of influenza and vaccine effectiveness. Based on the results of PSA with 1 000 Monte Carlo simulations, influenza vaccination had a probability of being cost-effective in 100% of the repetitions. Conclusions: The present study provides evidence that influenza vaccination is a cost-saving disease prevention strategy for people aged 60 years and older in Shenzhen.

Abstract TP72: Cost Effectiveness Of Smoking-Cessation Interventions Following Ischemic Stroke And Transient Ischemic Attack

Introduction: The cost effectiveness of smoking-cessation interventions after ischemic stroke and TIA has not been evaluated. We performed a cost-effectiveness analysis of smoking-cessation interventions in this population. Methods: We constructed a decision tree model to compare brief counseling alone to 3 interventions: varenicline, any pharmacotherapy with intensive counseling, and monetary incentives. Direct health care costs of interventions and outcomes were modeled. The outcomes were recurrent stroke, myocardial infarction, and death using a 5-year horizon. Estimates and variance for the base case (42% cessation), costs and effectiveness of interventions, and outcome rates were imputed from the stroke literature. Using standard techniques, we calculated incremental cost-effectiveness ratios (ICER) and net-monetary benefits (NMB). An intervention was considered cost effective if the ICER was less than the standard willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY) or when the NMB was maximized. Sensitivity analyses and a probabilistic Monte Carlo simulation modeled the impact of parameter uncertainty, including for the base case cessation rate and costs and effectiveness of interventions (TreeAge Pro). Results: All three interventions were cost effective based on the ICER: varenicline - $7,422/QALY, pharmacotherapy with counseling - $14,550/QALY, and monetary incentives - $23,280/QALY. In one-way sensitivity analyses, interventions costing up to $1,729 remained cost-effective. In a two-way sensitivity analysis varying the cost and effectiveness of smoking-cessation interventions, all three interventions were cost effective based on NMB (Figure). In 10,000 Monte Carlo simulations, smoking-cessation interventions were cost effective 90% of the time, as compared to brief counseling alone. Conclusion: Smoking-cessation strategies are cost effective in secondary prevention after stroke and TIA.

Cost-effectiveness of anticoagulants for preventing stroke in patients with non-valvular atrial fibrillation in mainland China.

With the high cost, the long-term persistence of new oral anticoagulants (NOACs) was lower than that of warfarin in Chinese patients with non-valvular atrial fibrillation (NVAF) for a long time. The prices of NOACs (apixaban, rivaroxaban and dabigatran) decreased significantly over the past year in mainland China. The objective of this study was to evaluate the cost-effectiveness of NOACs versus warfarin for preventing stroke in patients with NVAF from a Chinese healthcare system perspective. A decision tree and Markov model were used to assess the treatment strategies of four NOACs versus warfarin over a lifetime horizon. For each treatment strategy, the total lifetime cost, quality-adjusted life-years (QALY) and incremental cost-effectiveness ratio (ICER) were calculated. The impact of parameter uncertainties on base-case analysis results was evaluated using sensitivity analyses. In the base-case analysis, compared with warfarin, apixaban had a decreased total lifetime cost of USD 389 and rivaroxaban of USD 1482, while low-dose dabigatran had an increased total lifetime cost of USD 925 and high-dose dabigatran of USD 6641, with QALY increasing by 0.53, 1.32, 0.92 and 1.83, respectively. The ICER of low-dose dabigatran versus warfarin was USD 1005 per QALY gain, while those of apixaban (-USD 734 per QALY gain) and rivaroxaban (-USD 1123 per QALY gain) were negative. One-way and probabilistic sensitivity analyses indicated that the base-case results were robust by applying certain varying parameters to the model. These four NOAC (apixaban, rivaroxaban, low-dose dabigatran and high-dose dabigatran) treatment strategies were cost-effective compared with warfarin and recommended as substitutes for warfarin treatment for preventing stroke in patients with NVAF in the healthcare system of China, which might be driven by large drug price reductions in the past year.

Preliminary model assessing the cost-effectiveness of preoperative chlorhexidine mouthwash at reducing postoperative pneumonia among abdominal surgery patients in South Africa.

Pneumonia is a common and severe complication of abdominal surgery, it is associated with increased length of hospital stay, healthcare costs, and mortality. Further, pulmonary complication rates have risen during the SARS-CoV-2 pandemic. This study explored the potential cost-effectiveness of administering preoperative chlorhexidine mouthwash versus no-mouthwash at reducing postoperative pneumonia among abdominal surgery patients. A decision analytic model taking the South African healthcare provider perspective was constructed to compare costs and benefits of mouthwash versus no-mouthwash-surgery at 30 days after abdominal surgery. We assumed two scenarios: (i) the absence of COVID-19; (ii) the presence of COVID-19. Input parameters were collected from published literature including prospective cohort studies and expert opinion. Effectiveness was measured as proportion of pneumonia patients. Deterministic and probabilistic sensitivity analyses were performed to assess the impact of parameter uncertainties. The results of the probabilistic sensitivity analysis were presented using cost-effectiveness planes and cost-effectiveness acceptability curves. In the absence of COVID-19, mouthwash had lower average costs compared to no-mouthwash-surgery, $3,675 (R 63,770) versus $3,958 (R 68,683), and lower proportion of pneumonia patients, 0.029 versus 0.042 (dominance of mouthwash intervention). In the presence of COVID-19, the increase in pneumonia rate due to COVID-19, made mouthwash more dominant as it was more beneficial to reduce pneumonia patients through administering mouthwash. The cost-effectiveness acceptability curves shown that mouthwash surgery is likely to be cost-effective between $0 (R0) and $15,000 (R 260,220) willingness to pay thresholds. Both the absence and presence of SARS-CoV-2, mouthwash is likely to be cost saving intervention for reducing pneumonia after abdominal surgery. However, the available evidence for the effectiveness of mouthwash was extrapolated from cardiac surgery; there is now an urgent need for a robust clinical trial on the intervention on non-cardiac surgery.

Robust design approach to the minimization of functional performance variations of products and systems

Functional performance variations of products and systems are often used to measure the qualities of products and systems considering the changes in the design parameter values caused by uncertainties. A robust design approach has been developed in this research to minimize the functional performance variations considering the design parameter uncertainties by identifying the boundaries of the functional performance variations through optimization. In this work, a mathematical model is developed to describe the relationships among functional performance, design configurations and parameters, and design parameter uncertainties. A multi-level optimization model is established to identify: (1) The optimal design configuration, (2) the optimal values of design parameters, and (3) the boundaries of functional performance variations. Sensitivity analysis considering the impact of parameter uncertainties on functional performance variation boundaries has also been conducted. A case study on the design of a truss system has been conducted. Case study results show that the sensitivities of functional performance variation boundaries to the design parameter uncertainties can be reduced significantly using the new robust design approach.

Cost-effectiveness of dual influenza and pneumococcal vaccination among the elderly in Shenzhen, China

ObjectiveTo assess the cost-effectiveness of dual influenza and pneumococcal vaccination for the elderly in Shenzhen, China. MethodsA Markov state-transition model with a weekly cycle was developed to compare the outcomes of dual influenza and pneumococcal vaccination for the prevention of influenza and pneumococcal infections compared with no vaccination among 70–74 years old people in Shenzhen over 5 years. The model allowed seasonal variation of influenza activity. We calculated the incremental cost-effectiveness ratio (ICER) with costs and quality-adjusted life years (QALYs) discounted at 5% annually from the societal perspective. The impact of parameter uncertainty on the results was examined using one-way and probabilistic sensitivity analyses (PSA). ResultsIn the base case, dual vaccination prevented 5042 influenza infections, 26 IPD cases, 3 disabilities, 34 deaths, and cost US$7.1 per person while resulting in a net gain of 0.0026 QALYs compared with no vaccination. Using once the Chinese gross domestic product per capita in 2019 (US$10,289) as the willingness-to-pay threshold, dual vaccination was cost-effective with an ICER of US$2699 per QALY gained. One-way sensitivity analyses showed that the ICER was relatively sensitive to changes in influenza attack rates and influenza vaccine effectiveness. Based on the results of PSA with 1000 Monte Carlo simulations, receiving both vaccines was cost-effective in 100% of the repetitions. ConclusionThe current study provides evidence that dual influenza and pneumococcal vaccination is a cost-effective disease prevention strategy for the elderly in Shenzhen, China.

Protocol for an economic analysis of the randomised controlled trial of Improving the Well-being of people with Opioid Treated CHronic pain: I-WOTCH Study

IntroductionOver the last two decades, the use of opioids for the treatment of chronic pain in England has steadily increased despite lack of evidence of both long-term effectiveness in pain...

Modified Polynomial Chaos Expansion for Efficient Uncertainty Quantification in Biological Systems

Uncertainty quantification (UQ) is an important part of mathematical modeling and simulations, which quantifies the impact of parametric uncertainty on model predictions. This paper presents an efficient approach for polynomial chaos expansion (PCE) based UQ method in biological systems. For PCE, the key step is the stochastic Galerkin (SG) projection, which yields a family of deterministic models of PCE coefficients to describe the original stochastic system. When dealing with systems that involve nonpolynomial terms and many uncertainties, the SG-based PCE is computationally prohibitive because it often involves high-dimensional integrals. To address this, a generalized dimension reduction method (gDRM) is coupled with quadrature rules to convert a high-dimensional integral in the SG into a few lower dimensional ones that can be rapidly solved. The performance of the algorithm is validated with two examples describing the dynamic behavior of cells. Compared to other UQ techniques (e.g., nonintrusive PCE), the results show the potential of the algorithm to tackle UQ in more complicated biological systems.

Asset Pricing in Production Economies with Learning About Rare Disasters

In rare disaster models, it is a major challenge to generate large equity premium and low risk-free rate by imposing realistic consumption jump size. This paper addresses this issue based on a dynamic general equilibrium production economy with learning about rare disasters. Essentially, the information about fundamentals driving rare downward jumps in the output process is not perfect and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. In the model, the belief dynamics are essential to reconcile the tension between financial markets and consumption data. Additionally, learning about high versus low disaster intensity can generate empirically plausible trend for the investment-output ratio. The economy also features that the impact of parameter uncertainty accounts for a substantial fraction of the total welfare effects of rare disasters.

The potential of a CLIA-certified prognostic/predictive molecular test to address the rising costs of non-small cell lung cancer.

e21671 Background: Treating recurrences of non-small cell lung cancer (NSCLC) is increasingly expensive but still rarely curative. Disease free survival (DFS) among resected stage I-IIA patients remains only 50-70%. Guidelines advocate adjuvant therapy in “high-risk” patients in this population to reduce these costly and deadly recurrences, but recognize that conventional criteria have not been validated to stratify risk or predict benefit. A CLIA-certified, commercially available 14-gene expression risk profile (DetermaRx) has been extensively validated among stage I-IIA non-squamous NSCLC patients; prospective data now suggest that the test predicts improved DFS with adjuvant therapy. We therefore studied the potential economic impact of this molecular test on early stage NSCLC. Methods: Model variables included: relative increase in DFS with adjuvant treatment of molecular intermediate- and high-risk patients (25.5%; range 12.3-41.3%); cost of adjuvant ($8,760; $8,144-$9,376) or late-stage ($284,500; $224,900-345,200) treatment; and compliance with recommendations for adjuvant therapy (75%; 60-90%). Ranges were based on: historical trials and recent prospective data, published cost literature, and published survey data, respectively. Parameters were varied in a multifactorial, one-way sensitivity analysis to assess the impact of parameter uncertainty. Results: Reduction of recurrences with implementation of the 14-gene assay resulted in an average cost savings of $11,608/patient (potential systems savings of ~$450 million), even when including the cost of molecular risk stratification ($4000/patient) and of cisplatin-based adjuvant chemotherapy for molecular high- and intermediate-risk patients. Lower bound assumptions for relative improvement, cost of care, and compliance yielded persistent savings of $3,699, $8,091 and $8,486, respectively. Conclusions: Utilization of this predictive molecular risk stratification assay in the management of stage I-IIA non-squamous NSCLC has the potential to significantly reduce lung cancer costs in an era of targeted therapy and immunotherapy, while at the same time improving DFS and saving lives.

Lessons from Assessing Uncertainty in Agricultural Water Supply Estimation for Sustainable Rice Production

Agricultural water supply (AWS) estimation is one of the first and fundamental steps of developing agricultural management plans, and its accuracy must have substantial impacts on the following decision-making processes. In modeling the AWS for paddy fields, it is still common to determine parameter values, such as infiltration rates and irrigation efficiency, solely based on literature and rough assumptions due to data limitations; however, the impact of parameter uncertainty on the estimation has not been fully discussed. In this context, a relative sensitivity index and the generalized likelihood uncertainty estimation (GLUE) method were applied to quantify the parameter sensitivity and uncertainty in an AWS simulation. A general continuity equation was employed to mathematically represent the paddy water balance, and its six parameters were investigated. The results show that the AWS estimates are sensitive to the irrigation efficiency, drainage outlet height, minimum ponding depth, and infiltration, with the irrigation efficiency appearing to be the most important parameter; thus, they should be carefully selected. Multiple combinations of parameter values were observed to provide similarly good predictions, and such equifinality produced the substantial amount of uncertainty in AWS estimates regardless of the modeling approaches, indicating that the uncertainty should be counted when developing water management plans. We also found that agricultural system simulations using only literature-based parameter values provided poor accuracy, which can lead to flawed decisions in the water resources planning processes, and then the inefficient use of public investment and resources. The results indicate that modelers’ careful parameter selection is required to improve the accuracy of modeling results and estimates from using not only information from the past studies but also modeling practices enhanced with local knowledge and experience.

Cost-utility analysis of offering a novel remunerated community pharmacist consultation service on influenza vaccination for seniors in Ontario, Canada

BackgroundDespite the availability of free and accessible influenza vaccine to all Ontarians, uptake has remained suboptimal. Although reasons to not receive the vaccine vary widely, health care provider recommendations remain the most effective strategy to positively influence vaccination decisions. ObjectivesThis study aimed to predict the relative quality of life, costs, and cost-effectiveness of introducing a remunerated community pharmacist consultation service on influenza vaccination for Ontarians aged ≥ 65 years. MethodsA cost-utility analysis was performed from a third-party public payer perspective over 1 year. The delivery of consultation services by community pharmacists on influenza vaccination, billable at CAD $15 was compared with current standard practices (absence of remunerated consultations). Model inputs were derived primarily from existing literature. The impact of parameter uncertainties was assessed through deterministic and probabilistic sensitivity analyses. ResultsThe provision of influenza vaccine consultation services was predicted to prevent 2407 cases of mild influenza and 3 influenza-related deaths at an additional cost of CAD $2.03 per person over current practices. The incremental costs per quality-adjusted life-year (QALY) gained for the enhanced care strategy compared with standard care was CAD $2087. The interpretation of the base-case result was found to be robust across all sensitivity analyses. The projected additional costs of implementing pharmacist consultations in Ontario was estimated at CAD $1.15 million per year, and the anticipated benefits included a gain of 507 QALY per year. ConclusionPharmacist-delivered consultation services on influenza vaccination are cost-effective and lead to improved clinical outcomes for Ontario seniors. Introduction of such services offers a promising strategy to address challenges related to poor vaccine uptake in this group.

A Flexible Open-Source Decision Model for Value Assessment of Biologic Treatment for Rheumatoid Arthritis.

The nature of model-based cost-effectiveness analysis can lead to disputes in the scientific community. We propose an iterative and collaborative approach to model development by presenting a flexible open-source simulation model for rheumatoid arthritis (RA), accessible to both technical and non-technical end-users. The RA model is a discrete-time individual patient simulation with 6-month cycles. Model input parameters were estimated based on currently available evidence and treatment effects were obtained with Bayesian network meta-analysis techniques. The model contains 384 possible model structures informed by previously published models. The model consists of the following components: (i) modifiable R and C++ source code available in a GitHub repository; (ii) an R package to run the model for custom analyses; (iii) detailed model documentation; (iv) a web-based user interface for full control over the model without the need to be well-versed in the programming languages; and (v) a general audience web-application allowing those who are not experts in modeling or health economics to interact with the model and contribute to value assessment discussions. A primary function of the initial version of RA model is to help understand and quantify the impact of parameter uncertainty (with probabilistic sensitivity analysis), structural uncertainty (with multiple competing model structures), the decision framework (cost-effectiveness analysis or multi-criteria decision analysis), and perspective (healthcare or limited societal) on estimates of value. In order for a decision model to remain relevant over time it needs to evolve along with its supporting body of clinical evidence and scientific insight. Multiple clinical and methodological experts can modify or contribute to the RA model at any time due to its open-source nature.