Three Data Trends in Healthcare and Life Sciences

Why data is growing exponentially and how to manage it 

Unstructured data is growing exponentially in the healthcare and life sciences industries .  With countless data sources including EHR free-form text fields, discharge summaries, progress notes and lab reports many companies are seizing the opportunity to develop a data-driven culture to provide more accurate insights, improve efficiencies and develop innovative approaches that can ultimately improve patient outcomes. 

Healthcare providers, pharmaceuticals and biotech companies all need easy access to data for R&D purposes and to improve plans for their patients. There are enormous opportunities to leverage data from the healthcare ecosystem. Many innovative technologies, such as nanotechnology, IoT, augmented reality and virtual reality, are being invested in to facilitate collaboration, data management and version control for the healthcare and life sciences industry. 

In this blog we will discuss three data trends which are impacting healthcare and life sciences organizations striving to manage their growing data sources:

  • the adoption of new digital technologies driving data silos
  • the adoption of Artificial Intelligence and Machine Learning technology
  • the expanding use of Real World Evidence (RWE)

1. Adoption of new digital technologies driving data silos

Having access to accurate and up to date data has always been one of the most important aspects in the healthcare industry. Implementing a data-driven culture, with the use of AI technology, has been providing several advantages to the healthcare industry. 

The significant increase in digital technologies such as Mobile Health (mHealth) apps, Electronic Health Records (EHRs), Electronic Medical Records (EMRs), personalized medicine and many more, has resulted in the volume, variety and velocity of data growing exponentially. With the fast reception of electronic clinical records and new information sources from patient applications or sensors from wearable gadgets, the quantity of data is constantly increasing.

This is causing an increase in data silos throughout the industry, meaning it is difficult to extract value from these new data sources. Currently,  in order to extract value from this data a lot of manual administration is required. This is both time consuming and therefore costly, but also opens the data to the risk of human error. 

2. Embracing artificial intelligence (AI) and machine learning (ML) technology 

Improving patient care has always been the priority for the healthcare industry. Patients today are demanding more convenience, customization, and control of their healthcare. Innovative technologies are giving these organizations the opportunity to provide more personalized medicines and treatments.

Using artificial intelligence and machine learning enables precise and specific predictions and recommendations to be provided by healthcare professionals. Patients have an expectation to take control over their own health data and this technology allows them to be more informed and empowered than ever before. 

However, the sensitivity and privacy of this data requires extremely dense data management. The increasing sources of data for patients from AI and ML technologies need to be centralized in a single and secure location, translated into one language. To realize the benefits of this data to improve patient and business outcomes,  it needs to be accessible, in real-time, and ideally automated so there is no delay that could impact efficacy. 

3. Expanding use of Real World Evidence (RWE)

C-Suite leaders in pharmaceutical companies view RWE as strategically important, because it can change how drugs are discovered, developed, commercialized and reimbursed. The significant increase of data has enhanced the use of RWE in new areas like R&D.

Life sciences are using RWE to improve better decision-making on target product profiles and development strategies, to inform trial designs and support regulatory filings for drug and medical devices. RWE can speed up the development of processes and lessen all costs of inserting clinical innovations developments in the market. 

Creating opportunities from data trends

Healthcare and life science organizations are increasingly looking to intelligent data management tools to drive their transformation from unstructured data to a data-driven culture that improves efficiencies, drives innovation and improves patient outcomes . 

With Kleene, you will be able to centralize, prepare and analyze your data, removing data silos and providing the complete picture. Our vision is to fully automate your data journey, getting you to knowledge and insights quicker, so you can create the solutions.

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