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- Aim: To understand the impact on payers, providers, and patients of introducing a new product
- Cost-effectiveness, cost-utility, cost-benefit, and cost-consequence models, e.g., suitable for reimbursement submissions, or to communicate value in hospital settings
- Budget-impact and return on investment models
- Conjoint models to measure sales message impact
- Assess product profile for key drivers
- All models are developed de-novo in lie with any relevant local or international guidelines
- Informs: Messaging and interactions with healthcare providers and payers, patient segmentation, and product development
- See our work: Impact of product X on procedure Y: model example
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Models
- Cost-effectiveness
- Budget impact
- Value-based pricing
- Cost calculators
- Return on investment
Models
What is a budget impact analysis or budget-impact model?
Budget-impact analysis (BIA) or budget-impact model (BIM) is an essential part of any health-economic assessment. In many jurisdictions, BIA is required to gain reimbursement. Even when not mandated, many healthcare providers will not add new products to their formulary without a comprehensive BIA. The purpose of a BIA is to quantify (with an estimate of uncertainty) the financial consequences of adopting a new healthcare product within a specified healthcare setting. Specifically, the BIA predicts how a change in the product used or the product mix in use to treat a condition will impact overall spending on that condition. The BIA considers both the efficacy and safety of the products, and is generally focused on the short- to mid-term horizon of 1 to 5 years. A BIA is often complemented by a cost-effectiveness analysis (CEA). These sometimes cover a longer time horizon, up to patient lifetimes, and can include consideration of patient quality of life. A BIA is used mostly for private payer interactions, whereas a CEA is of more broader interest to physicians, national payers, and patients—and can be published in academic, peer-reviewed journals.
Further Reading:
- Report of the ISPOR Task Force on Modeling Good Research Practices
- Principles of Good Practice for Budget Impact Analysis. Mauskopf et. al, 2007
- Budget Impact Analysis—Principles of Good Practice. Sullivan et. al, 2014
What is a cost-effectiveness analysis or cost-effectiveness model?
The cost of healthcare is always an important aspect, but most decisions on product coverage and reimbursement are not made oblivious to patient outcomes. Clinical data is almost always required, and a key question is the balance between costs and beneficial outcomes. A cost-effectiveness analysis (CEA) or cost-effectiveness model (CEM) estimates the cost of healthcare provision and the potential patient outcomes, both positive and negative (e.g. adverse events), and quantifies the cost-benefit ratio between them. This can be in terms of the cost per health outcome (e.g. hospitalization) avoided or cost per patient life year gained. For healthcare providers, these are commonly presented as an incremental cost-effectiveness ratio (ICER). The ICER is the difference in cost between the two interventions divided by the difference in health outcomes between the two interventions.
Further Reading:
- Good Research Practices for Measuring Drug Costs in CEA. Garrison et. al, 2010.
- CEA Alongside Clinical Trials. Ramsey et. al, 2015.
- Cost-effectiveness versus Cost-Utility Analyses. Jakubiak-Lasocka et. al, 2014.

Literature review
- Structured or systematic
- Landscaping
- Evidence-base collection
- Competitor assessment
Literature review
- Aim: To identify, read, and summarize the current literature -> providing you with an overview of the market landscape and any data gaps
- Academic literature databases: PubMed, EMBASE, Cochrane
- Systematic or structured reviews
- Regulatory, guideline, and gray literature reviews
- Full PRISMA compliance
- Informs: Decisions on market potential, product development, product acquisition, and future studies
A literature review summarizes the information on a topic over a specified time period. The report draws common themes together and provides insight into the longitudinal trends where possible. The key to an informative literature review is identifying (all) the relevant literature. This is done via structured searches of bibliographic databases, making the literature identified transparent and reproducible. A structured search generally returns many more ‘hits’ than can be extensively reviewed, and many may not be pertinent to the research question. For this reason, only a limited set of the hits are read in full and summarized. Those selected for full-text review are identified via screening, in which the title and abstract of each hit is compared against pre-defined inclusion and exclusion criteria.
Unlike a research manuscript, literature reviews does not develop new arguments but considers the arguments of all authors/papers included in the review. They can, though, be published if the review leads to novel insights or identifies important data gaps. For publication, literature reviews in the medical field generally need to be systematic. A systematic review is a type of literature review that collects and critically analyzes multiple research studies and is considered to be one of the highest levels of evidence to inform healthcare decision making. Systematic reviews of randomized controlled trials can be found at the Cochrane library. Coreva Scientific performs both structured and systematic literature reviews, these options are compared below:

Meta-analysis
- Comparative effectiveness
- Indirect-treatment comparison
- Bayesian methods
- Network meta-analysis
Meta-analysis
- Aim: To combine multiple evidence sources into a single estimate of efficacy and/or safety -> quantifying the effectiveness of your product
- Meta-analysis is one of the highest levels of clinical evidence available
- Network meta-analysis to compare multiple products
- Indirect treatment comparison and Bayesian methods
- Informed by systematic review, these studies are publishable in high-aimpact journals and at congresses
- Informs: Value messaging, product positioning, medical communications, and sales strategy
What is Meta-analysis?
In most settings, healthcare providers and payers can select their product of choice from multiple available options. Each of these products is usually backed by positive clinical data, so the question becomes which product is backed by the most evidence and the most robust evidence. This question can be answered via a meta-analysis.
Meta-analysis is viewed as some of the highest levels of clinical evidence available and their outcomes are likely to publishable. It takes data from multiple randomized, controlled trials and synthesises the estimates of effectiveness from each individual trials into an overall estimate of effectiveness. Using meta-analysis, multiple trials showing non-significant or only minor benefits may result in a significant difference between products as the power of the individual studies is magnified. Alternatively, the significant benefit observed in a few trials may be outweighed by multiple trials showing no difference between products.
For further details on meta-analysis please contact us or consult:
- Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Mother et. al, 2009.
- The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration.Liberati et. al, 2009.
- Systematic review or meta-analysis? Their place in the evidence hierarchy. Paul and Leibovici 2013.
- Systematic review and meta-analysis methodology. Crowther et. al, 2010.
What is Network Meta-Analysis?
Healthcare providers and payers can often select their product of choice from multiple available options. As each of these products is usually backed by positive clinical data, so the question becomes which product is backed by the most evidence and the most robust evidence. This question can be answered via a network meta-analysis.
(Network) Meta-analysis is viewed as some of the highest levels of clinical evidence available. It takes data from multiple randomized, controlled trials and synthesises the estimates of effectiveness from each individual trials into estimates of head-to-head effectiveness. Using network meta-analysis, a probability of superiority per product can be calculated. As with meta-analysis, multiple trials showing non-significant or only minor benefits may result in a significant difference between products as the power of the individual studies is magnified.
In a network meta-analysis, multiple treatments (three or more) are being compared using both direct comparisons and indirect data. Indirect data are linked via a common comparator, e.g. the standard of care or control arm. If an analysis considers the efficacy and safety of two products only connected via indirect data, this is known as an indirect treatment comparison rather than a network meta-analysis. Network meta-analysis and indirect treatment comparison are statistically complex and involve Bayesian analysis. When compared with standard meta-analysis, this can make their outcomes more difficult to communicate effectively. The likelihood of publication, though, is also high and these studies are of interest to physicians as well as healthcare payers and providers.
Further Reading:
- Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making. Jansen et. al, 2011.
- Conducting Indirect-Treatment-Comparison and Network-Meta-Analysis Studies. Hoaglin et. al , 2011.
- Network meta-analysis. Tianjing Li et. al, 2011.

Environmental impact
- Environmental data management
- Reprocessing strategies
- Life-cycle assessment
- Carbon footprinting
- Waste analysis
Environmental impact
Aim: To assess the full environmental implications of medical devices and healthcare products, from their creation to their disposal.
Methods:
- Life-cycle assessment
- Waste analysis
- Reprocessing strategies
- Carbon footprinting
- Environmental data management
Informs: Opportunities for reducing the environmental impact of medical devices and improving sustainability practices.
Benefits: Having an eco-friendly product can benefit HTA decisions, improve tender success, and contribute to corporate social responsibility.
Regulatory: Ensure compliance with legal frameworks and international guidelines such as EU Green Deal or the Intergovernmental Panel on Climate Change (IPCC) report.
Life-cycle assessment
Life-cycle assessments (LCAs) consider all inputs and outputs during the whole life cycle of a product to quantify the impact on the environment. This takes into account: raw materials for production, supply chain and logistics, and device use and maintenance, through to the final disposal of the product. The environmental impact can take many different forms, including CO2 emissions, carcinogenic effects, water, or land use. An LCA can identify the processes in a products life cycle that have the largest environmental implications. This knowledge can be used as a starting point for discussions around possibilities to reduce a products burden on the environment.
Waste analysis
The healthcare sector generates a significant amount of waste, particularly through disposable devices. Due to strict regulations, transformation to a more sustainable practice is challenging in this sector. A waste analysis can help you identify waste prevention potentials and can also be used to compare different products or services. A waste analysis can inform decision-making on the hospital or healthcare system level.
Further reading:
Environmental Life Cycle Assessment in Medical Practice: A User's Guide. Link
The environmental footprint of health care: a global assessment. Link

Quality improvement
- Paper or electronic data-collection forms
- Progressive web applications
- Digital data-collection tool
- Dashboard summaries
- Surveys
- Audits
Quality improvement
Aim: To collect real-world data on clinical practice to support healthcare improvement.
Possible methods:
• Digital data-collection tool
• Progressive web applications
• Paper or electronic data-collection forms
• Audits
• Surveys
• Dashboard summaries
Benefits: Quantification of general compliance, product usage data collection, getting customer engagement, capturing real-world practice and real-world evidence, suitable for peer-reviewed publications, and development of product evidence.
Regulatory: Compliance with international data-sovereignty and data-protection regulations. The collection of usage data for EU Medical Device Regulations.
Related work:
- Service evaluation of the impact of capnography on the safety of procedural sedation. Link
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Capnography for monitoring of physician-led procedural sedation procedures at gastrointestinal services (video)
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Clinical practice, monitoring, and patient safety during procedural sedation in five countries. Poster
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Interventions and costs associated with SIVA-defined adverse events during procedural sedation in five countries. Poster
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Patient safety during procedural sedation using capnography monitoring: a systematic review and meta-analysis. Link
- For other related work see our publications page

Market access
- Pricing
- Reimbursement and data source landscaping
- Strategic support
- NUB and MTEP submissions
- DRGs
- Clinical trial design
- Epidemiology
Market access
- Aim: To identify and overcome any barrier that prevents your product from being available to any patient that would benefit from its use
- Landscaping and competitor intelligence
- Budget-impact models
- Risk-sharing agreements
- Value-based healthcare and purchasing
- Pricing and reimbursement
- Informs: Sales strategy, pricing, and reimbursement
What is Risk-sharing?
No matter how beneficial, new products always need to gain sales momentum. This can result in delays in both patients and healthcare systems realizing the positive benefits of adopting new healthcare practices. One reason for this delay, is the uncertainty over potential cost increases or loss of efficiencies. To overcome this, risk sharing agreements have been developed. They are a relatively new and innovative payment or reimbursement model that spreads the risk and opportunity between the two key stakeholders: payers and manufacturers. Under a risk-sharing agreement, the manufacturer and payer agree to link reimbursement to the products effectiveness or benefit. The appeal of such “pay-for-performance” agreements is understandable, as the payer only reimburses the manufacturer for the beneficial health outcomes achieved, rather than for provision of products that may or may not be effective and/or used.
In general, a risk-sharing agreement incorporates a planned assessment period, during which the performance of product is tracked. This includes use of a defines set of patient outcomes and a defined patient population. The level of reimbursement is then linked to the number of positive outcomes achieved. In some cases, it may be that the manufacture offers a tiered rebate on its product if the outcomes pledged are not met.
Clearly, a risk-sharing agreement is about the acceptable splitting of risk. Manufacturers, thus, need to calculate how much they can offer a payer in order to access the payers’ market without taking on too much risk. Coreva Scientific are here to help with the scoping of risk-sharing agreements and to build models to quantify the balance in risk between manufacturers and payers.
Further Reading:
Performance-based risk-sharing arrangements—good practices for design, implementation, and evaluation: ISPOR Good Practices for Performance-based Risk-sharing Arrangements Task Force Report. See also the performance-based risk-sharing arrangements slides by Dr. Lou Garrison.
A powerful, data-driven value
story for your product
Making your product standout from the crowd requires a value message with impact. With healthcare budgets being continuously stretched, increasing the perceived value of a product is more important than ever. At Coreva Scientific we help our partners to develop new value for their products or to determine the best mix of services and treatments to offer customers. From initial study design or data collection through to market access, we move your product forward with scientific evidence always at the fore.

Product value creation

Customized data collection

Models

Market access
