As if the volume, variety, and velocity of pharmaceutical data aren’t already flowing at a head-spinning rate, health economics and outcomes research (HEOR) data is adding another layer of complexity - as well as opportunity.
The Wild West of HEOR Data
As the ROI on drug development overall stalls
, it’s no longer enough to collect data that proves the efficacy and safety of therapies. Pharmaceutical & biopharmaceutical companies
need to prove the economic viability of drug products
as well. This puts greater pressure on organizations already overwhelmed with data.
The available HEOR data – both proprietary and public, structured and unstructured
– needs to be wrangled for more timely, manageable and useful consumption. This includes more recent contributions to big data in pharma – from social media posts and online patient forums
to wearable monitoring device outputs – which have emerged as a substantial source of information
on a wide range of medical conditions, treatments, and costs.
• through pharmaceutical or insurance companies’ contact centers
• with healthcare providers via email or web portal
• through online surveys, among others.
Although the primary reasons for this social sharing have been information, education, and support for patients and their families, a secondary benefit has been the value such information can have on drug and medical device development
has 31 million data points on disease
, covering more than 2,500 conditions. The forum says the real-world health experiences of its 400,000+ members helps organizations that focus on its members’ conditions.
Finding Value in Big Data
• Strengthening HEOR
• Targeting drugs at specific patient populations
• Accelerating drug development
• Improving clinical study patient recruitment and retention
In one empirical study
of clinical trials eligibility criteria for chronic lymphocytic leukemia (CLL) and prostate cancer, unstructured data was “essential to solving” 59% of CLL and 77% of prostate cancer trial criteria. The study found that “structured data alone is insufficient in resolving eligibility criteria for recruiting patients into clinical trials” for the two diseases.
But how can you easily and rapidly source relevant data from disparate databases? What if, as in HEOR, the data sets are wildly different, from highly-structured lab values and medication lists to unstructured data captured in physician notes and online patient forums?
Empowering Scientific Decision-Making
What empowers scientists working in pharma or CROs today, who must understand the implicit relationship between data sources across the expanding data universe?
Scientists and business analysts who have a unified view – including structured, semi-structured, and unstructured information – dramatically reduce their time to insight and improve the quality of their decisions and actions. Arming them with a self-service data source discovery portal helps to quickly identify and link relevant project-based data sets across disparate systems. This moves you faster to better insights, more quickly to better decisions, more effectively to market.
Are you equipped to leverage big data
and gain a competitive edge by mining the depths of HEOR data? If so, hear, hear! If not, see here