Type 2 Diabetes-Related Health Economic Impact Associated with Increased Whole Grains Consumption among Adults in Finland

The prevalence of type 2 diabetes (T2D) is increasing rapidly worldwide. A healthy diet supporting the control of energy intake and body weight has major importance in the prevention of T2D. For example, a high intake of whole grain foods (WGF) has been shown to be inversely associated with risk for T2D. The objective of the study was to estimate the expected health economic impacts of increased WGF consumption to decrease the incidence of T2D in the Finnish adult population. A health economic model utilizing data from multiple national databases and published scientific literature was constructed to estimate these population-level health economic consequences. Among the adult Finnish population, increased WGF consumption could reduce T2D-related costs between 286€ and 989€ million during the next 10-year time horizon depending on the applied scenario (i.e., a 10%-unit increase in a proportion of daily WGF users, an increased number (i.e., two or more) of WGF servings a day, or alternatively a combination of these scenarios). Over the next 20–30 years, a population-wide increase in WGF consumption could lead to much higher benefits. Furthermore, depending on the applied scenario, between 1323 and 154,094 quality-adjusted life years (QALYs) could be gained at the population level due to decreased T2D-related morbidity and mortality during the next 10 to 30 years. The results indicate that even when the current level of daily WGF consumption is already at a relatively high-level in a global context, increased WGF consumption could lead to important health gains and savings in the Finnish adult population.

Conceptualizing breakthrough pain

The concept of breakthrough pain (BTP) is examined through the development of a conceptual model with a long-term goal of positively impacting the management of chronic pain patients who experience BTP when hospitalized. The model is based on a 2008 Health Economic Model of Breakthrough Pain developed by Abernethy, Wheeler, and Fortner, which will be referred to as the parent model. The conceptual model of BTP, titled, Novel Conceptual Model of Breakthrough Pain (NCMBP) shares a similar structure in regards to the relationships of major constructs. Like the parent model, the NCMBP is based on three major constructs which are analyzed and explained further with associated concepts. The NCMBP is primarily concerned with the importance of a pain management plan and the endpoint result of patient-perceived analgesia. The NCMBP is viewed as a necessary foundation for continuing safe and effective pain management in the setting of a current opioid overdose epidemic in the United States. The structure and conceptual relationships of the NCMBP are preliminary and will continue to undergo revision as conduction of research is attempted to test the model.

Immunoglobulin Replacement Therapy is critical and cost-effective in increasing life expectancy and quality of life in patients suffering from Common Variable Immunodeficiency Disorders (CVID): A health-economic assessment

Background Common variable immunodeficiency disorders (CVID), the most common form of primary antibody deficiency, are rare conditions associated with considerable morbidity and mortality. The clinical benefit of immunoglobulin replacement therapy (IgGRT) is substantial: timely treatment with appropriate doses significantly reduces mortality and the incidence of CVID-complications such as major infections and bronchiectasis. Unfortunately, CVID-patients still face a median diagnostic delay of 4 years. Their disease burden, expressed in annual loss of disability-adjusted life years, is 3-fold higher than in the general population. Hurdles to treatment access and reimbursement by healthcare payers may exist because the value of IgGRT is poorly documented. This paper aims to demonstrate cost-effectiveness and cost-utility (on life expectancy and quality) of IgGRT in CVID. Methods and findings With input from a literature search, we built a health-economic model for cost-effectiveness and cost-utility assessment of IgGRT in CVID. We compared a mean literature-based dose (≥450mg/kg/4wks) to a zero-or-low dose (0 to ≤100 mg/kg/4wks) in a simulated cohort of adult patients from time of diagnosis until death; we also estimated the economic impact of diagnostic delay in this simulated cohort. Compared to no or minimal treatment, IgGRT showed an incremental benefit of 17 life-years (LYs) and 11 quality-adjusted life-years (QALYs), resulting in an incremental cost-effectiveness ratio (ICER) of €29,296/LY and €46,717/QALY. These results were robust in a sensitivity analysis. Reducing diagnostic delay by 4 years provided an incremental benefit of six LYs and four QALYs compared to simulated patients with delayed IgGRT initiation, resulting in an ICER of €30,374/LY and €47,495/QALY. Conclusions The health-economic model suggests that early initiation of IgGRT compared to no or delayed IgGRT is highly cost-effective. CVID-patients’ access to IgGRT should be facilitated, not only because of proven clinical efficacy, but also due to the now demonstrated cost-effectiveness.

Routine versus selective intraoperative cholangiography during cholecystectomy: systematic review, meta-analysis and health economic model analysis of iatrogenic bile duct injury

Background Bile duct injury (BDI) is a severe complication following cholecystectomy. Early recognition and treatment of BDI has been shown to reduce costs and improve patients’ quality of life. The aim of this study was to assess the effect and cost-effectiveness of routine versus selective intraoperative cholangiography (IOC) in cholecystectomy. Methods A systematic review and meta-analysis, combined with a health economic model analysis in the Swedish setting, was performed. Costs per quality-adjusted life-year (QALY) for routine versus selective IOC during cholecystectomy for different scenarios were calculated. Results In this meta-analysis, eight studies with more than 2 million patients subjected to cholecystectomy and 9000 BDIs were included. The rate of BDI was estimated to 0.36 per cent when IOC was performed routinely, compared with to 0.53 per cent when used selectively, indicating an increased risk for BDI of 43 per cent when IOC was used selectively (odds ratio 1.43, 95 per cent c.i. 1.22 to 1.67). The model analysis estimated that seven injuries were avoided annually by routine IOC in Sweden, a population of 10 million. Over a 10-year period, 33 QALYs would be gained at an approximate net cost of €808 000 , at a cost per QALY of about €24 900. Conclusion Routine IOC during cholecystectomy reduces the risk of BDI compared with the selective strategy and is a potentially cost-effective intervention.

Calculating the Expected Value of Sample Information in Practice: Considerations from 3 Case Studies

Background. Investing efficiently in future research to improve policy decisions is an important goal. Expected value of sample information (EVSI) can be used to select the specific design and sample size of a proposed study by assessing the benefit of a range of different studies. Estimating EVSI with the standard nested Monte Carlo algorithm has a notoriously high computational burden, especially when using a complex decision model or when optimizing over study sample sizes and designs. Recently, several more efficient EVSI approximation methods have been developed. However, these approximation methods have not been compared, and therefore their comparative performance across different examples has not been explored. Methods. We compared 4 EVSI methods using 3 previously published health economic models. The examples were chosen to represent a range of real-world contexts, including situations with multiple study outcomes, missing data, and data from an observational rather than a randomized study. The computational speed and accuracy of each method were compared. Results. In each example, the approximation methods took minutes or hours to achieve reasonably accurate EVSI estimates, whereas the traditional Monte Carlo method took weeks. Specific methods are particularly suited to problems where we wish to compare multiple proposed sample sizes, when the proposed sample size is large, or when the health economic model is computationally expensive. Conclusions. As all the evaluated methods gave estimates similar to those given by traditional Monte Carlo, we suggest that EVSI can now be efficiently computed with confidence in realistic examples. No systematically superior EVSI computation method exists as the properties of the different methods depend on the underlying health economic model, data generation process, and user expertise.

Estimating the Expected Value of Sample Information across Different Sample Sizes Using Moment Matching and Nonlinear Regression

Background. The expected value of sample information (EVSI) determines the economic value of any future study with a specific design aimed at reducing uncertainty about the parameters underlying a health economic model. This has potential as a tool for trial design; the cost and value of different designs could be compared to find the trial with the greatest net benefit. However, despite recent developments, EVSI analysis can be slow, especially when optimizing over a large number of different designs. Methods. This article develops a method to reduce the computation time required to calculate the EVSI across different sample sizes. Our method extends the moment-matching approach to EVSI estimation to optimize over different sample sizes for the underlying trial while retaining a similar computational cost to a single EVSI estimate. This extension calculates the posterior variance of the net monetary benefit across alternative sample sizes and then uses Bayesian nonlinear regression to estimate the EVSI across these sample sizes. Results. A health economic model developed to assess the cost-effectiveness of interventions for chronic pain demonstrates that this EVSI calculation method is fast and accurate for realistic models. This example also highlights how different trial designs can be compared using the EVSI. Conclusion. The proposed estimation method is fast and accurate when calculating the EVSI across different sample sizes. This will allow researchers to realize the potential of using the EVSI to determine an economically optimal trial design for reducing uncertainty in health economic models. Limitations. Our method involves rerunning the health economic model, which can be more computationally expensive than some recent alternatives, especially in complex models.