Data Enrichment

Empowering Data Dexterity for Meaningful Insights

Christian Evans
Wed 25 November 2020
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With healthcare organizations digitally transforming their processes, there is an acute need for data enrichment and curation to fill the gaps, bottlenecks, and delays created by poor data movement and quality. It’s important to implement actionable insights from the available data. As part of the evolution, organizations need to revamp the data integration layer to improve data practices and enhance the quality of data, facilitating the life sciences industry to make strategic decisions supported by analytics and data-driven insights.

The growing data dependency has put the spotlight on the need to refine, enrich, and curate data to extract the best insights and evidence from real-world data. And access to clean, robust data is a necessity to attain this goal. It facilitates drawing detailed conclusions for speedy drug development and medical innovations.

The real-world data (RWD) not only provides evidence for critical clinical decisions but also generates real-world insights that expand the industry perspective on the effective use of medicine. Amidst the increasing costs and complex clinical development processes, the real-world data (RWD), with advanced analytics, is proving its mettle as a powerful enabler for transforming the drug and clinical development lifecycle.

Real-World Data: Impacting the Healthcare Environment

The simultaneous use of RWD and predictive modeling has the potential to improve clinical development and operational processes that rely heavily on historical experience and assumptions. The prevalent adoption of RWE is also augmenting the information healthcare providers’ use for clinical decision making by adding information that is not collected as part of RCTs, including unrepresented patients with chronic illnesses, diverse population groups, and the elderly.

  • Impact on Drug Development - The RWE is synergistic to the traditional trial data, enabling richer and more diverse information to be collected from disparate sources from the real-world environment. It accelerates the drug development process by providing real-world usage and practice of the medicine and/or its supplements.
  • Impact on Regulatory Decisions - To promote the use of RWD and RWE as an evidentiary model for drug approval the US FDA legislated the 21st Century Cures Act, exploring opportunities for expanding the use of RWE in demonstrating efficacy for drug and medical device approval. The Cures Act also mandates the FDA to hold public workshops and create guidance documents to enhance the use of RWE in regulatory decision-making.
  • Impact on Medical Practice - The RWD enables the practitioners to take inference from richer data and evaluate the condition beyond the restricted criterion of the randomized clinical trials (RCT). It gives a broader scope of understanding for the providers by facilitating access to information from multiple sources and across millions of patients, more than what he/she individually sees. Such data can help shape the medical decisions, specifically in sync with patients’ individual characteristics and make healthcare better personalized and effective.

Real-world studies have heavily contributed to attaining the fundamental goal of advancing patient care through precision while minimizing the risks. RWD facilitates drawing insights before and after the market authorization of a new drug, assess the pharmacoeconomic properties of treatment, and explores the effectiveness in conditional reimbursement schemes in the new age of medicine aided by technology.

To learn more about the scope of RWD and predictive modeling in Life Sciences, get a demo.

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