The 21st century has brought about significant technological advancement, allowing the collection of new types of data from the real world on an unprecedented scale. The healthcare industry will benefit immensely from this abundance of patient data from electronic health records (EHRs), patient-reported outcomes (PROs), laboratory, demographic, social media, digital, and even climate data. While conventional statistical methods still play a significant role in supporting the drug lifecycle, machine learning (ML) and artificial intelligence (AI) are assuming a more prominent role in the analysis of this “big data.” Moving forward, conventional statistics and ML/AI will work together to support descriptive, diagnostic, and even predictive analytics to further revolutionize drug discovery and development, regulatory approvals, and payer acceptance. In addition, counterfactual prescriptive analytics, such as causal inference analysis using real-world data (RWD) to generate insights that have cause-and-effect conclusions, will gain momentum as a methodology that can stand up against the rigor of regulatory review. Our real-world evidence/health economics and outcomes research (RWE/HEOR) field has evolved in ways that require us to integrate all the methods and data into a single framework that guides a holistic analytic approach and decision-making.
Won Chan Lee, Ph.D., Principal, HEOR/RWE Practice at Axtria has synonymized insight generation from RWD with the fable of the six blind men and the elephant. Even if the right RWD is identified, the right analytics should be applied; otherwise, it generates insufficient insights. Advanced real world evidence (RWE) is often about leveraging data analysis as perfectly as it should be, with inherently imperfect data. RWE is a combination of RWD and analytics. With the massive expansion in data availability and technology, the healthcare industry is able to perform analytics that will further revolutionize drug discovery, development, regulatory approvals, and payer acceptance.
Read this insightful paper to find out how the RWE and HEOR field has now reached a point where many different methods of data analytics can be used for effective decision-making.
