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Application in the Real World 2018-03-01T02:22:54+00:00

Use by Different Stakeholders

One of the core goals of the IVI-RA model and accompanying web interfaces is to help inform the real-world decisions of a variety of stakeholders in the U.S. health care market. Health care decision-makers require high-quality evidence on treatment benefits and cost to make coverage decisions, negotiate prices, and make treatment decisions. Different decision-makers face very different decision contexts.  For instance, some treat very sick populations, while others treat patients with milder, earlier-stage disease.  Some care exclusively about health gains and costs, while others care about adjacent outcomes like workplace productivity.  The IVI-RA model provides flexibility that adapts to different circumstances.

The current version of the IVI-RA model is primarily designed to support a diverse range of population-level decisions around how to best allocate limited health care dollars, but the information it provides is valuable to a wide range of stakeholders making many different kinds of decisions.

Example Questions from Different Stakeholders

How do I identify sources of health care spending that will provide the most value to society?

Spending on health care is often an investment with long-term returns, but understanding the broader benefits of health care spending decisions requires approaches that take a societal perspective. The IVI-RA model allows users to include societal-level treatment benefits and costs recommended by leading scientists.  Examples of these societal value components include productivity effects and benefits that healthy individuals obtain from medical technologies due to the reduced risks of physical harm (also called insurance value).

What is the value of RA treatments to my unique and specific enrollee population?

Health plans and insurers must make complex coverage decisions and negotiate prices that maximize benefits while minimizing cost across their enrolled populations. Every population of enrollees is unique, but information on value and cost-effectiveness is often presented for an “average” patient in the general population. The IVI-RA model provides full flexibility in defining population characteristics and adjusting inputs such as prices and rebates to tailor measures of value to a health plan’s unique set of enrollees.

How do my treatment decisions fit into value-based reimbursement?

As payers move towards value-based purchasing, provider compensation will increasingly depend on the quality and cost of the care they recommend. In this new value-based world, providers need to understand the relative benefits and costs of different treatment strategies at a practice level. The IVI-RA model synthesizes evidence sources to allow providers to examine the long-term health benefits and potential costs of different treatment strategies.

How do my product’s treatment benefits and costs compare to competitor treatments?

The IVI-RA model leverages evidence from both clinical trials and real world data to ensure that measures of treatment value are up-to-date and relevant to real-world clinical practice. Furthermore, life science firms can use the online interfaces, iviRA R package, or even customize the underlying source code, to run analyses that incorporate more recent evidence (e.g., recently released price changes, payer-specific rebates, more recent clinical trial data) between IVI model updates.

How does value-based reimbursement affect patients with RA?

Rising drug prices and health care costs in the United States have generated discussions about paying for value rather than volume. At the same time, the value or cost-effectiveness of treatments may impact formulary decisions, prior authorization requirements, and other policies. In this context, the IVI-RA Value Tool can help patients and patient advocacy groups explore differences in value across treatments for RA. Moreover, as high-deductible health plans become more common, patients may want more information on whether a treatment is worth the cost.

A Flexible Modeling Approach at the Individual Level

The IVI-RA model is a patient-level simulation that models health outcomes and risks associated with sequences of disease-modifying anti-rheumatic drugs (DMARDs) for individual patients, each with their own characteristics, disease course, and health outcomes. The model is designed to be flexible so that:

  • Results can be tailored to the unique characteristics (e.g., age, gender, disease activity) of specific populations;
  • A range of modeling approaches based on the prior academic literature (384 possible models structures) can be selected, analyzed, and debated;
  • Users can decide to consider costs to the health care system alone or include broader societal costs such as effects on patients’ earnings;
  • Important values such as drug prices can be easily edited;
  • Users can consider components not usually included in value models—for example, the value of available treatments to the currently healthy and treatment attributes such as mode of administration.

To ensure that simulated outcomes reflect outcomes in routine practice, baseline events rates (i.e., the rate of disease progression, the mortality rate, the rate at which patients discontinue treatment), patient preferences, and costs are modeled using real-world data.

To enhance validity, relative treatment effects relative treatment effects (e.g., relative risks, odds ratios, and hazard ratios) are, when possible, based on randomized clinical trials (RCTs).

Application in Value Assessment

The IVI-RA model currently supports two approaches to value-oriented decision analysis: cost-effectiveness analysis and multi-criteria decision analysis.

Cost-Effectiveness Analysis

Cost-effectiveness analysis is a well-established approach for comparing the cost and benefits of alternative treatments. The benefits of treatment are typically assessed using the quality-adjusted life year (QALY), a measure that combines a patient’s life expectancy and quality of life. In cases where one treatment may be more likely to improve patient health, but also costs more than another, cost-effectiveness analysis is one quantitative approach for trading off health gains and cost. Decision-makers must determine how much they would be willing to pay for additional health benefits (i.e., the value of a QALY) and a treatment is deemed cost-effective if its cost per QALY is less than the decision-makers willingness to pay threshold.

Multi-Criteria Decision Analysis

An alternative approach to value assessment is multi-criteria decision analysis (MCDA), which recognizes that decisions are often made using a number of disparate criteria. MCDA lets decision-makers weight these different criteria (i.e., health outcomes, mode of administration, strength of available evidence, costs) based on their importance to the individual decision-maker. The different treatment options are scored on each criterion, and the decision-makers’ customized weights are then used to generate a single weighted average score for each treatment option.