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Objectives: Decision analytic modelling is essential in performing cost-effectiveness analyses (CEAs) of interventions in cardiovascular disease (CVD). However, modelling inherently poses challenges that need to be dealt with since models always represent a simplification of reality. The aim of this study was to identify and explore the challenges in modelling CVD interventions., Methods: A document analysis was performed of 40 model-based CEAs of CVD interventions published in high-impact journals. We analysed the systematically selected papers to identify challenges per type of intervention (test, non-drug, drug, disease management programme, and public health intervention), and a questionnaire was sent to the corresponding authors to obtain a more thorough overview. Ideas for possible solutions for the challenges were based on the papers, responses, modelling guidelines, and other sources., Results: The systematic literature search identified 1,720 potentially relevant articles. Forty authors were identified after screening the most recent 294 papers. Besides the challenge of lack of data, the challenges encountered in the review suggest that it was difficult to obtain a sufficiently valid and accurate cost-effectiveness estimate, mainly due to lack of data or extrapolating from intermediate outcomes. Despite the low response rate of the questionnaire, it confirmed our results., Conclusions: This combination of a review and a survey showed examples of CVD modelling challenges found in studies published in high-impact journals. Modelling guidelines do not provide sufficient guidance in resolving all challenges. Some of the reported challenges are specific to the type of intervention and disease, while some are independent of intervention and disease.

Background and Objective: Patient heterogeneity is the part of variability that can be explained by certain patient characteristics (e.g. age, disease stage). Population reimbursement decisions that acknowledge patient heterogeneity could potentially save money and increase population health. To date, however, economic evaluations pay only limited attention to patient heterogeneity. The objective of the present paper is to provide a comprehensive overview of the current knowledge regarding patient heterogeneity within economic evaluation of healthcare programmes., Methods: A systematic literature review was performed to identify methodological papers on the topic of patient heterogeneity in economic evaluation. Data were obtained using a keyword search of the PubMed database and manual searches. Handbooks were also included. Relevant data were extracted regarding potential sources of patient heterogeneity, in which of the input parameters of an economic evaluation these occur, methods to acknowledge patient heterogeneity and specific concerns associated with this acknowledgement., Results: A total of 20 articles and five handbooks were included. The relevant sources of patient heterogeneity (demographics, preferences and clinical characteristics) and the input parameters where they occurred (baseline risk, treatment effect, health state utility and resource utilization) were combined in a framework. Methods were derived for the design, analysis and presentation phases of an economic evaluation. Concerns related mainly to the danger of false-positive results and equity issues., Conclusion: By systematically reviewing current knowledge regarding patient heterogeneity within economic evaluations of healthcare programmes, we provide guidance for future economic evaluations. Guidance is provided on which sources of patient heterogeneity to consider, how to acknowledge them in economic evaluation and potential concerns. The improved acknowledgement of patient heterogeneity in future economic evaluations may well improve the efficiency of healthcare.

Background: In the Netherlands, in low-risk pregnancies, the views of pregnant women and their partners on characteristics of obstetric care services are leading for the selection of place of birth. The aim of this study was to investigate whether there are differences between the decision-making process of pregnant women and their partners with regard to these attributes of obstetric care., Methods: This study was a prospective cohort study with low-risk nulliparae and their partners. A questionnaire, based on the method of discrete-choice experiment, was used to gather the data., Results: Possibility of influencing decision-making was, both for pregnant women (n = 321) and their partners (n = 212), the most important characteristic of the obstetric care. For women, a home-like birth setting was an important characteristic, while the partners found the possibility on pain-relief treatment during birth important., Conclusions: The results of this study suggest that women and their partners have clearly defined preferences for obstetric care. There are also some essential differences between the preferences of these two groups. The findings are important where policy issues related to aspects of maternity care service delivery are being considered.

Background: Decision making about resource allocation for guideline implementation to change clinical practice is inevitably undertaken in a context of uncertainty surrounding the cost-effectiveness of both clinical guidelines and implementation strategies. Adopting a total net benefit approach, a model was recently developed to overcome problems with the use of combined ratio statistics when analyzing decision uncertainty., Objective: To demonstrate the stochastic application of the model for informing decision making about the adoption of an audit and feedback strategy for implementing a guideline recommending intensive blood glucose control in type 2 diabetes in primary care in the Netherlands., Methods: An integrated Bayesian approach to decision modeling and evidence synthesis is adopted, using Markov Chain Monte Carlo simulation in WinBUGs. Data on model parameters is gathered from various sources, with effectiveness of implementation being estimated using pooled, random-effects meta-analysis. Decision uncertainty is illustrated using cost-effectiveness acceptability curves and frontier., Results: Decisions about whether to adopt intensified glycemic control and whether to adopt audit and feedback alter for the maximum values that decision makers are willing to pay for health gain. Through simultaneously incorporating uncertain economic evidence on both guidance and implementation strategy, the cost-effectiveness acceptability curves and cost-effectiveness acceptability frontier show an increase in decision uncertainty concerning guideline implementation., Conclusions: The stochastic application in diabetes care demonstrates that the model provides a simple and useful tool for quantifying and exploring the (combined) uncertainty associated with decision making about adopting guidelines and implementation strategies and, therefore, for informing decisions about efficient resource allocation to change clinical practice.

Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources.

Given the potential role of economic information in healthcare decision making, it is of interest to assess its influence on decisions at a national or regional level (macro level), at a healthcare facility level (meso level) and at the healthcare provider level (micro level). This literature review summarises 36 empirical studies that examined the influence of economic evaluations on these three healthcare decision-making levels. Economic evaluations are considered useful and important; however, their direct influence on decision making (instrumental use) is moderate, especially at the macro and micro levels. A major influence was observed at the meso level, leading to the conclusion that economic evaluations have the most pronounced influence on decision making within healthcare organisations. However, unexpectedly, our literature search did not reveal an empirical study analysing the considerable influence of economic evaluations on decisions by the National Institute of Health and Clinical Excellence in the UK. Our findings indicate that results of economic evaluations cannot be considered the dominant decision criterion for healthcare decision makers at either the macro, meso or micro levels. Enlightenment use (where scientific evidence provides a background of information, ideas and concepts that affect the way policy makers view problems and solutions) of economic evaluations in decision making remains to be proven.

Objectives: To assess the cost effectiveness of home telemonitoring (HTM) and nurse telephone support (NTS) compared with usual care (UC) in the management of patients with chronic heart failure, from a third-party payer's perspective.Methods: We developed a Markov model with a 20-year time horizon to analyze the cost effectiveness using the original study (Trans-European Network-Home-Care Management System) and various data sources. A probabilistic sensitivity analysis was performed to assess the decision uncertainty in our model.Results: In the original scenario (which concerned the cost inputs at the time of the original study), HTM and NTS interventions yielded a difference in quality-adjusted life-years (QALYs) gained compared with UC: 2.93 and 3.07, respectively, versus 1.91. An incremental net monetary benefit analysis showed €7,697 and €13,589 in HTM and NTS versus UC at a willingness-to-pay (WTP) threshold of €20,000, and €69,100 and €83,100 at a WTP threshold of €80,000, respectively. The incremental cost-effectiveness ratios were €12,479 for HTM versus UC and €8,270 for NTS versus UC. The current scenario (including telenurse cost inputs in NTS) yielded results that were slightly different from those for the original scenario, when comparing all New York Heart Association (NYHA) classes of severity. NTS dominated HTM, compared with UC, in all NYHA classes except NYHA IV.Conclusions: This modeling study demonstrated that HTM and NTS are viable solutions to support patients with chronic heart failure. NTS is cost-effective in comparison with UC at a WTP of €9000/QALY or higher. Like NTS, HTM improves the survival of patients in all NYHA classes and is cost-effective in comparison with UC at a WTP of €14,000/QALY or higher. [ABSTRACT FROM AUTHOR]

Introduction: Describing the general and methodological characteristics of decision-analytical models used in the economic evaluation of early warning systems for the management of chronic heart failure patients and performing a quality assessment of their methodological characteristics is expected to provide concise and useful insight to inform the future development of decision-analytical models in the field of heart failure management.Areas Covered: The literature on decision-analytical models for the economic evaluation of early warning systems for the management of chronic heart failure patients was systematically reviewed. Nine electronic databases were searched through the combination of synonyms for heart failure and sensitive filters for cost-effectiveness and early warning systems.Expert Commentary: The retrieved models show some variability with regards to their general study characteristics. Overall, they display satisfactory methodological quality, even though some points could be improved, namely on the consideration and discussion of any competing theories regarding model structure and disease progression, identification of key parameters and the use of expert opinion, and uncertainty analyses. A comprehensive definition of early warning systems and further research under this label should be pursued. To improve the transparency of economic evaluation publications, authors should make available detailed technical information regarding the published models. [ABSTRACT FROM AUTHOR]

The article presents the study on the willingness of the consumer to invest money and time for health and public health intervention at lifestyle behaviour change (LBC) through contingent valuation (CV). CV survey and internal validity test were conducted to explore the association between willingness and explanatory variables including paid work, income, and experience. Results were outlined and conclude the relevance of broader quality of life outcomes to consumers decision making.

Economic evaluations can inform decisions about the efficiency and allocation of resources to implementation strategies—strategies explicitly designed to inform care providers and patients about the best available research evidence and to enhance its use in their practices. These strategies are increasingly popular in health care, especially in light of growing concerns about quality of care and limits on resources. But such concerns have hardly motivated health authorities and other decision-makers to spend on some form of economic evaluation in their assessments of implementation strategies. This editorial addresses the importance of economic evaluation in the context of implementation science—particularly, how these analyses can be most efficiently incorporated into decision-making processes about implementation strategies. [ABSTRACT FROM AUTHOR]

Results of cost effectiveness analyses (CEA) studies are most useful for decision makers if they face only one constraint: the health care budget. However, in practice, decision makers wishing to use the results of CEA studies may face multiple resource constraints relating to, for instance, constraints in health care inputs such as a shortage of skilled labour. The presence of multiple resource constraints influences the decision rules of CEA and limits the usefulness of traditional CEA studies for decision makers. The goal of this paper is to illustrate how results of CEA can be interpreted and used in case a decision maker faces a health care input constraint. We set up a theoretical model describing the optimal allocation of the health care budget in the presence of a health care input constraint. Insights derived from that model were used to analyse a stylized example based on a decision about a surgical robot as well as a published cost effectiveness study on eye care services in Zambia. Our theoretical model shows that applying default decision rules in the presence of a health care input constraint leads to suboptimal decisions but that there are ways of preserving the traditional decision rules of CEA by reweighing different cost categories. The examples illustrate how such adjustments can be made, and makes clear that optimal decisions depend crucially on such adjustments. We conclude that it is possible to use the results of cost effectiveness studies in the presence of health care input constraints if results are properly adjusted. [ABSTRACT FROM AUTHOR]

Objectives: Despite the emphasis on efficiency of health-care services delivery, there is an imperfect evidence base to inform decisions about whether and how to develop and implement guidelines into clinical practice. In general, studies evaluating the economics of guideline implementation lack methodological rigor. We conducted a systematic review of empiric studies to assess advances in the economic evaluations of guideline implementation. Methods: The Cochrane Effective Professional and Organisational Change Group specialized register and the MEDLINE database were searched for English publications between January 1998 and July 2004 that reported objective effect measures and implementation costs. We extracted data on study characteristics, quality of study design, and economic methodology. It was assessed whether the economic evaluations followed methodological guidance. Results: We included 24 economic evaluations, involving 21 controlled trials and three interrupted time series designs. The studies involved varying settings, targeted professionals,targeted behaviors, clinical guidelines, and implementation strategies. Overall, it was difficult to determine the quality of study designs owing to poor reporting. In addition, most economic evaluations were methodologically flawed: studies did not follow guidelines for evaluation design, data collection, and data analysis. Conclusions: The increasing importance of the value for money of providing health care seems to be reflected by an increase in empiric economic evaluations of guideline implementation. Because of the heterogeneity and poor methodological quality of these studies, however, the resulting evidence is still of limited use in decision-making. There seems to be a need for more methodological guidance, especially in terms of data collection and data synthesis, to appropriately evaluate the economics of developing and implementing guidelines into clinical practice. [ABSTRACT FROM AUTHOR]