Time for Cooperation in Health Economics among the Modelling Community
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... Arnold and Ekins proposed multi-stakeholder collaboration across various sectors, which would involve greater transparency between members of the modelling community [28]. Decision models in many disease areas are necessarily complex, which can mean that peer reviewers are not adequately equipped to fully understand the work. ...
... Models are often created for a single purpose and then languish in journal archives, health authority databases, or various proprietary settings. Rather than using or updating a preexisting model, new models are often created for new medications or new indications at considerable time and financial expense [28]. The availability of reference models could help to avoid this situation, thus freeing up analysts' time. ...
... Publishers may also play an intermediary role in the debate between different researchers, companies, and other stakeholders. Greater transparency can raise issues of copyright and access, so there is a need to define how model sharing can be achieved in a fair and equitable manner [3,28,66]. We have developed a special interest group (SIG) within ISPOR to curate an ongoing dialogue around the creation, dissemination, sharing, evaluation, and updating of open source cost-effectiveness models. ...
Transparency in decision modelling is an evolving concept. Recently, discussion has moved from reporting standards to open-source implementation of decision analytic models. However, in the debate about the supposed advantages and disadvantages of greater transparency, there is a lack of definition. The purpose of this article is not to present a case for or against transparency, but rather to provide a more nuanced understanding of what transparency means in the context of decision modelling and how it could be addressed. To this end, we review and summarise the discourse to date, drawing on our collective experience. We outline a taxonomy of the different manifestations of transparency, including reporting standards, reference models, collaboration, model registration, peer review and open-source modelling. Further, we map out the role and incentives for the various stakeholders, including industry, research organisations, publishers and decision makers. We outline the anticipated advantages and disadvantages of greater transparency with respect to each manifestation, as well as the perceived barriers and facilitators to greater transparency. These are considered with respect to the different stakeholders and with reference to issues including intellectual property, legality, standards, quality assurance, code integrity, health technology assessment processes, incentives, funding, software, access and deployment options, data protection and stakeholder engagement. For each manifestation of transparency, we discuss the ‘what’, ‘why’, ‘who’ and ‘how’. Specifically, their meaning, why the community might (or might not) wish to embrace them, whose engagement as stakeholders is required and how relevant objectives might be realised. We identify current initiatives aimed to improve transparency to exemplify efforts in current practice and for the future.
... Pharmacoeconomics is a branch of health economics that usually focuses on balancing the costs and benefits of an intervention towards the use of limited resources, aiming at maximizing value to patients, healthcare payers and society through data driven decision making 1 . Pharmacoeconomics refers to the scientific discipline that compares the value of one pharmaceutical drug or drug therapy to another 2,3 . Pharmacoeconomics centers on the economic evaluation of pharmaceuticals, and can use cost-minimization analysis, cost-benefit analysis, cost-effectiveness analysis or costutility analysis. ...
Background: Pharmacoeconomic is an economic evaluation of pharmaceuticals in which the cost-effective analysis is one of the most important types of them that compares the relative costs and outcomes (effects) of different courses of action. Objective: The study aimed to Cost-Effectiveness analysis of some local and foreign antibacterial brands in Yemeni market. Method: Cost-effective analysis (CEA) was performed for four different antibacterial types (Azithromycin, Ciprofloxacin, Doxycycline and Amoxiclav), and there were four brands from each type that were of different origin, this analysis was carried out by antibacterial test for all brands against two types of sensitive bacteria (Staphylococcus aureus and Escherichia coli) and analysis of the efficacy of antibacterial brands in comparing to the cost or prices of this brands to calculate the cost-effectiveness ratio (CER) and select the best that was the lower value. Results: In the present study, from the pharmacoeconomic analysis, the Yemeni brands were the best in three types (Azithromycin, Doxycycline and Amoxicillin/clavulanic acid "Amoxiclav") with the smallest CER that were 10, 4.5, 32.11 in case of Staph. aureus and 13.33, 23.68 ,0 in case of E. coli respectively, while the Indian brand was the best in one type (Ciprofloxacin) with the smallest CER that were 8.13 in case of Staphylococcus aureus and 6.4 in case of Escherichia coli respectively, the four brands of amoxiclav type were showed ineffective against Escherichia coli in comparing to standard that was effective against Escherichia coli. Conclusion: This study was concluded the best brands to be selected was Yemeni brand in three antimicrobials (Azithromycin, Doxycycline and Amoxiclav) with 75% and the Indian brand in one type (Ciprofloxacin) with 25%. All the amoxiclav brands of different country were ineffective against E. coli.
... Although influential and widely used, health economic models can be skills and resource intensive to develop. One suggestion for making health economic modelling projects more tractable is for health economists to re-use each other's models [3]. ...
We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.
Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.
... 5 This often entails subjective decisions regarding methodology, evidence, and model structure. 6 As a consequence, there may be alternative valid modeling choices that lead to different resultsoften referred to as structural uncertainty. 7 Uncertainty affects various elements of any given health economic model, which is importantly not limited to imprecision of the model parameter estimates. ...
Objectives
Decision makers adopt health technologies based on health economic models that are subject to uncertainty. In an ideal world, these models parameterize all uncertainties and reflect them in the cost-effectiveness probability and risk associated with the adoption. In practice, uncertainty assessment is often incomplete, potentially leading to suboptimal reimbursement recommendations and risk management. This study examines the feasibility of comprehensive uncertainty assessment in health economic models.
Methods
A state transition model on peripheral arterial disease treatment was used as a case study. Uncertainties were identified and added to the probabilistic sensitivity analysis if possible. Parameter distributions were obtained by expert elicitation, and structural uncertainties were either parameterized or explored in scenario analyses, which were model averaged.
Results
A truly comprehensive uncertainty assessment, parameterizing all uncertainty, could not be achieved. Expert elicitation informed 8 effectiveness, utility, and cost parameters. Uncertainties were parameterized or explored in scenario analyses and with model averaging. Barriers included time and resource constraints, also of clinical experts, and lacking guidance regarding some aspects of expert elicitation, evidence aggregation, and handling of structural uncertainty. The team’s multidisciplinary expertise and existing literature and tools were facilitators.
Conclusions
While comprehensive uncertainty assessment may not be attainable, improvements in uncertainty assessment in general are no doubt desirable. This requires the development of detailed guidance and hands-on tutorials for methods of uncertainty assessment, in particular aspects of expert elicitation, evidence aggregation, and handling of structural uncertainty. The issue of benefits of uncertainty assessment versus time and resources needed remains unclear.
... It is hoped that through the development of an accepted standard, replication testing could act as a catalyst to promote changes in the way modelling studies are presented. Importantly, this will also indicate how well currently used checklists (such as Consolidated Health Economic Evaluation Reporting Standards [CHEERS] [32] and Philips [33]) identify reporting thoroughness and may also provide further evidence to support the multiple calls for modelling registries [62][63][64]. There may also be scope to further the application of such standards. ...
The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) modelling taskforce suggests decision models should be thoroughly reported and transparent. However, the level of transparency and indeed how transparency should be assessed are yet to be defined. One way may be to attempt to replicate the model and its outputs. The ability to replicate a decision model could demonstrate adequate reporting transparency. This review aims to explore published definitions of replication success across all scientific disciplines and to consider how such a definition should be tailored for use in health economic models. A literature review was conducted to identify published definitions of a ‘successful replication’. Using these as a foundation, several definitions of replication success were constructed, to be applicable to replications of economic decision models, with the associated strengths and weaknesses of such definitions discussed. A substantial body of literature discussing replicability was found; however, relatively few studies, ten, explicitly defined a successful replication. These definitions varied from subjective assessments to expecting exactly the same results to be reproduced. Whilst the definitions that have been found may help to construct a definition specific to health economics, no definition was found that completely encompassed the unique requirements for decision models. Replication is widely discussed in other scientific disciplines; however, as of yet, there is no consensus on how replicable models should be within health economics or what constitutes a successful replication. Replication studies can demonstrate how transparently a model is reported, identify potential calculation errors and inform future reporting practices. It may therefore be a useful adjunct to other transparency or quality measures.
... Pharmacoeconomic research serves to guide optimal healthcare resource allocationin a standardised and scientifically grounded manner. 2,3 As part ofhealth economics, public health requires evidence-based advocacy, communication and social mobilisation (ACSM) interventions. Evidence-based programming underlines the importance of collecting baselineand follow-up data in the design and assessment of ACSM activities that cater to populations or specific sub-groups. ...
... Model registration has been proposed as a solution to these and other problems [25][26][27]. Sampson and Wrightson [25] argued that a registry combined with a linked database of model-based economic evaluations could help overcome publication bias (though the feasibility of pre-registration of all analysis plans in the context of model-based economic evaluations is less than in clinical trials), and may promote collaborative validation exercises. ...
Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.
Objectives
Efficacy of venetoclax plus obinutuzumab (VenO) compared to chlorambucil plus obinutuzumab (ClbO) for treatment-naïve CLL adult patients with coexisting medical conditions was investigated in CLL14 (NCT02242942). Our aim was to evaluate the cost-effectiveness of VenO versus ClbO for these patients from a Dutch societal perspective.
Methods
A three-state partitioned survival model was constructed to evaluate the cost-effectiveness of VenO. The outcome of the analysis was the incremental cost-effectiveness ratio (ICER) with effectiveness measured in quality-adjusted life-years (QALYs) gained. Uncertainty was explored through deterministic and probabilistic sensitivity analyses (DSA & PSA), scenario analyses, and value of information analysis (VOI).
Results
The base case resulted in a discounted ICER -49,928 EUR/QALY gained (with incremental negative costs and positive effects). None of the ICERs resulted from DSA and scenario analyses exceeded the chosen willingness-to-pay threshold of 20,000 EUR/QALY, and more than 99% of the iterations in the PSA were cost-effective. VOI analyses showed a maximum expected value of eliminating all model parameter uncertainty of 183,591 EUR.
Conclusions
Our study demonstrated VenO being dominant over ClbO in adult, treatment naïve CLL assuming a Dutch societal perspective. We concluded that our results are robust as tested through sensitivity and scenario analyses. Additionally, the VOI analyses confirmed that our current evidence base is strong enough to generate reliable results for our study. However, further research based on real-world data or longer follow-up period could further contribute to the robustness of the current study’s conclusions.
Objectives
Health economic (HE) models are routinely used to support health policy and resource allocation decisions but are often considered “black boxes” that may be prone to error and bias. Open source models (OSMs) have been advocated to increase the transparency, credibility, and reuse of HE models. Previous studies have demonstrated interest in OSMs among the health economics and outcomes research community, but the number of OSMs remains low.
Methods
We conducted an online survey of ISPOR (the leading professional society for health economics and outcomes research) members’ perspectives on the usefulness of OSMs and barriers to their development and implementation.
Results
Respondents (N = 230) included academics (27%), pharmaceutical (or related) industry representatives (23%), health research or consulting representatives (21%), governmental or nonprofit agency representatives (10%), and others (19%). Respondents were generally not familiar with barriers to the development and adoption of OSMs. Most agreed that OSMs would improve transparency (92%), efficiency (76%), and HE model reuse (86%) and promote confidence in using HE models (75%). The use of OSMs by health technology assessment authorities was considered a very important indicator of the usefulness of OSMs by 49% of respondents. Three-quarters of respondents perceived legal concerns and the ability to transfer data as important barriers to the development and use of OSMs.
Conclusions
Respondents believe that OSMs could increase the transparency, efficiency, and credibility of HE models, but that several barriers hamper their widespread adoption. Our results suggest that fundamental changes may be needed across the health economics and outcomes research community if OSMs are to become widely adopted.
Phytomedicine can be defined as the science of medicines from plants. History of phytomedicine dates back to 60,000 years ago while written evidence dates back to approximately 5000 years ago. Isolation, extraction, and purification of drugs from medicinal plants in ancient times have presently led to existing miracle compounds, which directly or indirectly, relieve mankind from ill-health. Phytomedicine includes analysis and characterization of biomolecules, continuously being characterized for further applications. On the background of emerging super infections, new superbugs and strains are resistant to all types of infectious species; natural therapies have raised fresh hopes. Keeping a wider interdisciplinary approach, if phytomedicine is combined with other disciplines of medical sciences, it may prove to be a revolutionary step in the present health care scenario. Present deliberation aims at discussing phytomedicine, with respect to its history and future scope, which will help researchers in future endeavors in this direction.
This highly successful textbook is now available in its third edition. Over the years it has become the standard textbook in the field world-wide. It mirrors the huge expansion of the field of economic evaluation in health care, since the last edition was published in 1997. This new edition builds on the strengths of previous editions, being clearly written in a style accessible to a wide readership. Key methodological principles are outlined using a critical appraisal checklist that can be applied to any published study. The methodological features of the basic forms of analysis are then explained in more detail with special emphasis of the latest views on productivity costs, the characterisation of uncertainty and the concept of net benefit. The book has been greatly revised and expanded especially concerning analysing patient-level data and decision-analytic modelling. There is discussion of new methodological approaches, including cost effectiveness acceptability curves, net benefit regression, probalistic sensitivity analysis and value of information analysis. There is an expanded chapter on the use of economic evaluation, including discussion of the use of cost-effectiveness thresholds, equity considerations and the transferability of economic data. This new edition is required reading for anyone commissioning, undertaking or using economic evaluations in health care, and will be popular with health service professionals, health economists, pharmacand health care decision makers. It is especially relevant for those taking pharmacoeconomics courses.
Purpose of the Study
To estimate the cost-effectiveness of 2 different asthma care interventions: a peer leader–based physician behavior-change intervention (PLE) and a practice-based redesign called the planned asthma care intervention (PACI).
Study Population
Participants were 638 children (aged 3–17 years) with mild-to-moderate asthma. More than half of the subjects were on maintenance medication.
Methods
This was a 3-arm cluster-randomized trial conducted in 42 primary care practices. These practices were randomly assigned to PLE (n = 226), PACI (n = 213), or usual care (n = 199). The PLE strategy involved training a pediatrician at each of the practice sites as an asthma expert and champion. This leader provided support, education, and feedback to the other members of the practice with regard to asthma management. The PACI strategy included all the components of the PLE arm and also included scheduled asthma care visits with an asthma nurse, who provided standardized assessments, care planning, coordination with the primary care physician, and self-management tools. Practices in the usual-care arm received copies of the National Asthma Education and Prevention Program Expert Panel Report 2 and patient-information handouts 12 months into the study. The subjects were followed for 2 years. The primary outcome was symptom-free days (SFDs). Costs included asthma-related health care utilization and intervention.
Results
Patients in the usual-care arm of the study had in increase in SFDs of 14.8 per year. Patients in the PLE and PACI arms had an additional gain of 6.5 and 13.3 SFDs per year, respectively, compared with the usual-care arm. When the costs of development were excluded, the cost for SFDs gained compared with usual care was $18 for PLE and $68 for PACI.
Conclusions
It is possible to increase SFDs in children and to move organizations toward guideline recommendations for asthma management. However, the improvements were associated with an increase in the costs associated with asthma care.
Reviewer Comments
This trial was designed to provide cost analyses to both health care providers and health maintenance organizations. It is difficult, however, to establish a threshold for cost-effectiveness. The authors cite other trials to provide a context for this question. For example, the cost-effectiveness of inhaled corticosteroids in the treatment of children ranges from $7 to $12 per SFD gained. A social worker–based intervention had a cost-effectiveness ratio of $9 per SFD gained. What is it worth to patients, their families, and their health care providers to have an extra SFD?
ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
New vaccines against rotavirus, the leading cause of severe childhood gastroenteritis worldwide, are on the threshold of introduction into immunization programs in affluent nations. A reduction of the health burden and costs of severe rotavirus disease in these countries should be evident within 2–3 years of vaccine introduction. However, realizing the full potential of these vaccines will require demonstration of their efficacy and ensuring their affordability in the poorest populations where rotavirus kills >500,000 children annually.Section editors:Gary Woodnutt – CovX, San Diego, USAPaul-Henri Lambert – Centre of Vaccinology, University of Geneva, Switzerland
Government-run or-regulated health care systems have adopted complex systems of economic regulation to control pharmaceutical expenditures, which are generally an ad hoc mix of historical policies. There has, however, been a substantial increase in the number of third-party payers using formal cost-effectiveness analysis (CEA) or pharmacoeconomic approaches for assessing the value of drugs, vaccines, and other health technologies to inform decisions about pricing, reimbursement, and use within their health care systems. This article explores the theoretical and practical issues that have arisen in the application of CEA for drugs to resource allocation decisions in health care and in the regulation of pharmaceutical prices and use. It begins by outlining the evolution of CEA from the practice of health technology assessment.