Economic burden of road traffic injuries in Nepal

The evidence of the economic burden of road traffic injuries (RTIs) in Nepal is limited. The most recent study, conducted in 2008, is now considered outdated because there has been a rapid increase in vehicle numbers and extensive road building over the last decade. This study estimated the current economic costs of RTIs in Nepal, including the direct costs, productivity costs, and valuation of pain, grief, and suffering. An incidence-based cost-of-illness analysis was conducted from a societal perspective, employing a bottom-up approach using secondary data. All costs incurred by the patients, their family members, and costs to society were estimated, with sensitivity analyses to consider uncertainty around the data estimates available. Productivity loss was valued using the human capital approach. The total costs of RTIs in 2017 were estimated at USD 122.88 million. Of these, the costs of productivity loss were USD 91.57 million (74.52%) and the pain, grief, and suffering costs were USD 18.31 million (14.90%). The direct non-medical costs were USD 11.50 million (9.36%) whereas the direct medical costs were USD 1.50 million (1.22%). The economic costs of RTIs increased by threefold since 2007 and are equivalent to 1.52% of the gross national product, indicating the growing national financial burden associated with preventable RTIs

Adjusting estimates of the expected value of information for implementation: theoretical framework and practical application

Background: Value of information (VoI) calculations give the expected benefits of decision making under perfect information (EVPI) or sample information (EVSI), typically on the premise that any treatment recommendations made in light of this information will be implemented instantly and fully. This assumption is unlikely to hold in health care; evidence shows that obtaining further information typically leads to “improved” rather than “perfect” implementation. Objectives: To present a method of calculating the expected value of further research that accounts for the reality of improved implementation. Methods: This work extends an existing conceptual framework by introducing additional states of the world regarding information (sample information, in addition to current and perfect information) and implementation (improved implementation, in addition to current and optimal implementation). The extension allows calculating the “implementation-adjusted” EVSI (IA-EVSI), a measure that accounts for different degrees of implementation. Calculations of implementation-adjusted estimates are illustrated under different scenarios through a stylized case study in non–small cell lung cancer. Results: In the particular case study, the population values for EVSI and IA-EVSI were £25 million and £8 million, respectively; thus, a decision assuming perfect implementation would have overestimated the expected value of research by about £17 million. IA-EVSI was driven by the assumed time horizon and, importantly, the specified rate of change in implementation: the higher the rate, the greater the IA-EVSI and the lower the difference between IA-EVSI and EVSI. Conclusions: Traditionally calculated measures of population VoI rely on unrealistic assumptions about implementation. This article provides a simple framework that accounts for improved, rather than perfect, implementation and offers more realistic estimates of the expected value of research. </jats:p

Effectiveness and cost effectiveness of cardiovascular disease prevention in whole populations: modelling study

Objective To estimate the potential cost effectiveness of a population-wide risk factor reduction programme aimed at preventing cardiovascular disease

Towards optimum smoking cessation interventions during pregnancy: a household model to explore cost‐effectiveness

BACKGROUND AND AIMS: Previous economic evaluations of smoking cessation interventions for pregnant women are limited to single components, which do not in isolation offer sufficient potential impact to address smoking cessation targets. To inform the development of more appropriate complex interventions, we (1) describe the development of the Economics of Smoking in Pregnancy: Household (ESIP.H) model for estimating the life‐time cost‐effectiveness of smoking cessation interventions aimed at pregnant women and (2) use a hypothetical case study to demonstrate how ESIP.H can be used to identify the characteristics of optimum smoking cessation interventions. METHODS: The hypothetical intervention was based on current evidence relating to component elements, including financial incentives, partner smoking, intensive behaviour change support, cigarettes consumption and duration of support to 12 months post‐partum. ESIP.H was developed to assess the life‐time health and cost impacts of multi‐component interventions compared with standard National Health Service (NHS) care in England. ESIP.H considers cigarette consumption, partner smoking and some health conditions (e.g. obesity) that were not included in previous models. The Markov model's parameters were estimated based on published literature, expert judgement and evidence‐based assumptions. The hypothetical intervention was evaluated from an NHS perspective. RESULTS: The hypothetical intervention was associated with an incremental gain in quitters (mother and partner) at 12 months postpartum of 249 [95% confidence interval (CI) = 195–304] per 1000 pregnant smokers. Over the long‐term, it had an incremental negative cost of £193 (CI = –£779 to 344) and it improved health, with a 0.50 (CI = 0.36–0.69) increase in quality‐adjusted life years (QALYs) for mothers, partners and offspring, with a 100% probability of being cost‐effective. CONCLUSIONS: The Economics of Smoking in Pregnancy: Household model for estimating cost‐effectiveness of smoking cessation interventions aimed at pregnant women found that a hypothetical smoking cessation intervention would greatly extend reach, reduce smoking and be cost‐effective

A systematic review of research guidelines in Decision-Analytic Modelling

AbstractBackgroundDecision-analytic modeling (DAM) has been increasingly used to aid decision making in health care. The growing use of modeling in economic evaluations has led to increased scrutiny of the methods used.ObjectiveThe objective of this study was to perform a systematic review to identify and critically assess good practice guidelines, with particular emphasis on contemporary developments.MethodsA systematic review of English language articles was undertaken to identify articles presenting guidance for good practice in DAM in the evaluation of health care. The inclusion criteria were articles providing guidance or criteria against which to assess good practice in DAM and studies providing criteria or elements for good practice in some areas of DAM. The review covered the period January 1990 to March 2014 and included the following electronic bibliographic databases: Cochrane Library, Cochrane Methodology Register and Health Technology Assessment, NHS Economic Evaluation Database, MEDLINE, and PubMed (Embase). Additional studies were identified by searching references.ResultsThirty-three articles were included in this review. A practical five-dimension framework was developed that describe the key elements of good research practice that should be considered and reported to increase the credibility of results obtained from DAM in the evaluation of health care.ConclusionsThis study is the first to critically review all available guidelines and statements of good practice in DAM since 2006. The development of good practice guidelines is an ongoing process, and important efforts have been made to identify what is good practice and to keep these guidelines up to date

Multiple sclerosis risk sharing scheme: two year results of clinical cohort study with historical comparator

Objective To generate evidence on the longer term cost effectiveness of disease modifying treatments in patients with relapsing-remitting multiple sclerosis

Economic evaluation of typhoid - a review.

Introduction: To evaluate the potential economic value and likely impact of a hypothetical rapid test in its early stages of development requires the use of models. The model structure and the type of model (dynamic/static) to employ are key considerations. The aim of the review was to explore the literature on typhoid economic evaluations and to explore the types of models that have been previously adopted in this setting for test-treat evaluations and to capture data on model inputs that may be useful for a de novo model. Areas covered: A systematic review was conducted to identify economic evaluations focused on typhoid in established literature databases. Eight studies were identified and included for narrative synthesis. The review has revealed that there have been relatively few economic evaluations that have focused on typhoid fever, all of which have focused on the impact of interventions at the population level (vaccination) but not the individual level (test-treat strategies). Expert commentary: Under certain circumstances, either a static model or a transmission dynamic model may be appropriate in the evaluation of an intervention for typhoid fever. Typhoid test-treat modeling represents a gray area where further work is needed