Advanced analytics is changing the world of the pharmaceutical industry. The tools can integrate and process millions of structured and unstructured data such as medical transcripts, physician notes, patient records, and even social media posts. The deep and often unique insights into the patient’s health outcomes, disease’s progress, or patient response to vaccine or therapy are known as real-world evidence (RWE). Real-world data analytics allow pharmaceutical companies to invest wisely in new drugs and develop sophisticated sales strategies to gain a competitive edge and secure success. This article at McKinsey & Company discusses how pharma companies must set up analytics teams for success.
Real-World Data Analytics: Critical Success Factors
Patient data analytics is often the most challenging undertaking for the healthcare industry. Organizations struggle with:
- Implementing real-world data analytics across a variety of therapeutic areas
- Generating patient insights from analytics
- Identifying an appropriate real-world data source for a specific use case
Here are some focus areas that can help you scale patient analytics, make better decisions, expand a drug’s use, and advance scientific knowledge more broadly.
Integrated Data Environment
Create a process to manage and track data access, lineage, metadata, and compliance frameworks. The process will help you ensure that the workflow is robust and real-world data analysis maintains transparency and integrity.
RWE has become the cornerstone of modern healthcare operations. Therefore, you must replace your fragmented computing resources with distributed computing tools. Establish a flexible and scalable environment to handle different analytical approaches. “Data engineers must be able to access scalable resources as and when needed to support data-processing workflows,” says the author.
Real-World Data Analytics for Product Analysis
Product analytics platforms offer numerous features such as segmentation, tracking, notifications, and measurement tools. Furthermore, they also help you build user profiles based on specific criteria. In other words, product analytics save you time and effort by narrowing down what you look at based on your goals.
With a sound and well-equipped real-world data analytics foundation, pharma companies can significantly progress toward improving patient health outcomes. Additionally, they can support the broader goals of delivering the right drug to the right patient. To read the original article, click on https://www.mckinsey.com/industries/life-sciences/our-insights/generating-real-world-evidence-at-scale-using-advanced-analytics.