By 2025, the amount of data generated by the healthcare industry will expand 36% per year – faster than virtually any other industry in the world. That holds huge potential value for stakeholders across the industry – but only if they can ascertain how to extract consistent insights from this mountain of information.

So far, they haven’t seen a lot of success.

There are several challenges to overcome to realize the value of healthcare data, evidenced by the fact that 97% of healthcare data go unused after their initial creation. For instance, of healthcare data is unstructured in narrative notes, reports, images, and other formats. Furthermore, the average healthcare system has patient data in as many as 15 disparate systems – a challenge of both systems interoperability and multiple unharmonized coding and naming conventions. Set alongside complex regulatory requirements, it is no surprise so little healthcare data is efficiently used. In an industry built on innovation, it is frustrating to lose so much value, which is why industry leaders, like IQVIA, have been working for years to tear down these obstacles and automate our access to insights. And we are making tremendous strides in this journey.

In our latest webinar, Automate Data Transformation To Accelerate Healthcare Insights, IQVIA healthcare data and artificial intelligence (AI) experts Georg Turi, Maciek Piotrowski, and Dr. Calum Yacoubian, discussed the challenges the industry currently faces generating value from healthcare data, and how applications that combine data standardization, natural language processing (NLP), privacy preserving techniques, and versatile extract, transform and load (ETL) processes are helping healthcare organizations leapfrog their competitors in the quest for better, faster data analytics.

Insights at your fingertips

A poll of attendees at the webinar found the majority of industry professionals say their biggest challenge with healthcare data today is interoperability across complex and expanding data sources. They are also frustrated over working with large volumes of unstructured data.

These results reflect what IQVIA’s experts have heard for years. Most healthcare organizations and life sciences companies who are trying to generate insights from healthcare data spend 80% of their time cleaning, and wrangling data assets, and only 20% realizing any value from them. They also struggle to balance strict data privacy regulations and lack of central governance frameworks with efforts to maximize data utility.

None of these challenges can be overcome by human effort alone. They require a digital environment that is purpose-built to curate, integrate and standardize structured and unstructured health records from any data source using any coding standard. To do that, these digital solutions have to be able to de-identify and anonymize every data point and perform complex data transformations that link raw data from different sources into a single standardized location for more robust analysis at scale.

The ideal digital platform will automate most of these steps, freeing healthcare experts to spend their time asking questions, and using the insights generated to make more informed decisions. Once companies achieve this future state, the data paradigm flips allowing healthcare teams to spend 20% of their time on data management tasks, and 80% realizing value from them.

IQVIA’s Health Data Transformation Platform already delivers this digital vision today by combining AI-driven technology, global real-world healthcare data sets, and industry-leading expertise to bring life sciences companies into the future of automated data analytics. This automated, multi-functional platform curates complex patient healthcare information from heterogenous data sources, and then de-identifies, standardizes, and transforms it into an analytics-ready, unified output – that is easily queryable and searchable for use case specific insights generation.

34 million notes reviewed

The platform is helping healthcare organizations tackle individual and population healthcare challenges that have plagued the industry for years. Clients are using it to identify burdens of care in at-risk populations, to enable better prioritization of care delivery, and to improve the quality of care and reduce costs among other applications.


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