Real-World Evidence in Economic Modeling
In today’s technology-driven world, real-world evidence (RWE) is becoming key in modeling the economy. In an environment where information is a valuable resource and data analysis is important for decision-making, the use of real data becomes an integral part of understanding and predicting economic events. The use of RWEs also allows for a more accurate reflection of the actual conditions and factors shaping the economic environment. This not only strengthens the robustness of models but also provides the opportunity to build strategies and policies based on the analysis of real-world circumstances.
In this article, we will discuss the essence of real-world data, and its growing importance in modern economic modeling.
Understanding RWE in Economic Modeling
Real-world data is information related to a patient’s health condition or the delivery of health care, collected regularly from a variety of sources. Unlike controlled clinical trial conditions, RWE is based on real patient experiences in real medical scenarios.
Key sources of RWE include:
- electronic medical records;
- claims data;
- patient registries;
- Information obtained from wearable devices.
This data provides a more complete and realistic view of patient health, making it a valuable resource for analyzing and making healthcare decisions.
Integration into economic models
Economic modeling in healthcare is a tool for evaluating the financial and economic aspects of healthcare decisions (to learn more, check out this page). Integration of real data into economic models is becoming a key focus, increasing their accuracy and realism.
Above all, RWE integration enables more accurate assessment of the cost-effectiveness of medical decisions. Access to actual data on healthcare utilization and outcomes allows predicting real costs and benefits, which improves strategic planning and decision-making.
Budget impact also becomes more transparent as real data helps determine the optimal allocation of resources in healthcare. This promotes more efficient use of finances and allows for better adaptation to changes in consumer demand and medical trends.
Data integration also facilitates patient-centered analysis, which allows healthcare strategies to be more precisely tailored to individual patient needs, improving the quality of care provided.
RWE in drug development and market access
As healthcare becomes increasingly outcomes-driven, pharmaceutical companies are turning to a variety of data sources beyond traditional randomized clinical trials to measure and demonstrate the added value of their products. The use of evidence-based data has a long history, but recent advances in digital and advanced analytics are opening up new opportunities to use it more effectively. It enables:
- A deeper understanding of how patient characteristics and behaviors affect their health;
- which can help predict disease progression;
- monitor responses to therapy and risks of adverse events.
It also helps to increase the efficiency of R&D investments and shorten the time to market for a drug.
For years, pharmaceutical companies have successfully applied real-world data to make informed decisions, meet stakeholder demands, and improve the competitiveness of their medicines in the marketplace. More recently, some have been able to realize even greater benefits from using RWE, helped by:
- Growing acceptance by regulatory agencies in the U.S., Canada and other high-income countries where regulatory agencies have long begun using RWE to assess the safety and efficacy of medicines;
- increased interest from payers and healthcare providers;
- greater understanding of digital technology and analytics.
For example, Pfizer used electronic medical record (EMR) data to gain approval for Ibrance to treat breast cancer in men, and AstraZeneca used real-world data to demonstrate the efficacy of its diabetes drug Farxiga against competitors.
Case studies
RWE can be successfully integrated into studies of the effectiveness of medical drugs or treatment protocols to improve the quality and validity of their results. For example, a study conducted at the Cancer Institute of the Japan Cancer Research Foundation showed that a combination of chemotherapy and hormone therapy is more effective than chemotherapy alone for the treatment of breast cancer. The study was based on data from 1,612 patients with recurrent or metastatic breast cancer who received the combination therapy at a Cancer Institute hospital. The study was designed as a retrospective review of the patients’ medical records and resulted in confirmation that the combination of chemotherapy and hormone therapy can lead to a reduction in breast cancer mortality.
McKinsey estimates that the average pharmaceutical company that has implemented RWE’s advanced analytics at all stages of value creation for its products can expect benefits of more than $300 million annually over the next three to five years. Savings of $100 million in development costs are realized through:
- optimizing clinical trial design;
- using RWE instead of some randomized clinical trials;
- introduction of synthetic experimental groups.
Implementing advanced RWE analytics can also help companies accelerate time-to-market, improve drug listing position and payer negotiations, and provide stronger evidence of the uniqueness and balance of benefits and risks of their products. Analysis shows that applying these strategies to key assets could result in additional revenues of $200 million or more.
Future Trends
Going forward, technological advancements will continue to shape trends in the use of real-world data in healthcare. The development of more powerful analytical tools, machine learning and artificial intelligence will strengthen the ability to process and interpret large amounts of data, making RWE a more accurate and valuable tool for medical decision-making.
Potential collaborations between pharmaceutical companies, healthcare providers, and technology firms will drive the development of innovative approaches to the use of RWE, such as in personalized medicine and disease prediction.
In the realm of healthcare policymaking, the role of real data will also continue to evolve. RWE will become a more important tool for evaluating the effectiveness of medical interventions, making decisions about listing medications, and developing health care strategies. Legislators and regulators will increasingly rely on RWE to make decisions related to regulation, insurance, and resource allocation. This will contribute to more effective and adaptive health policies, as well as improve the quality of care provided.
Conclusion
In conclusion, it can be summarized that real-world evidence plays a crucial role in healthcare. Their incorporation into the research, development and economic justification of the cost of drugs or health services not only provides a more accurate picture of the costs and effectiveness of medical decisions, but also opens up new opportunities for more adaptive and efficient management of health care resources and strategies.
