Catch up on the latest life science and data analytics headlines with our weekly roundup of news, articles and reports.

How to Create a Competitive Advantage with Big Data Analytics in Pharma, by Pharma IQ

In this interview Nigel Hughes from Janssen R&D discusses the various ways in which pharma companies can tap into big data to improve product development and optimize the commercialization processes. With the rise of personalized/precision medicine there is a proliferated need for access to real-world-evidence data. To develop relevant therapies which win in the market, drug makers need to utilize RWE to access patient and provider data to assess the value of treatments and services based on actual health outcomes and the total cost of care. This is not just a competitive advantage – it is a must.  In the article Hughes addresses:

  • How data accessibility provides competitive advantage
  • The main challenges to accessing real world data
  • The key opportunities and threats in utilizing real world data
  • How the rise of personalized medicine will effect the use of real world data
  • Leverage critical data for actionable insights
  • And more!

Five Things You Never Suspected About Your Healthcare Data, by Forbes

The shift to value-based care has forced the healthcare industry to further explore its data in order to enhance patient care and outcomes. Unfortunately, 80% of healthcare data remains unstructured, leaving stakeholders at a loss when evaluating and analyzing the vast amounts of data. Life Sciences companies need a complete view of patient needs, (EHR, claims data, etc) to accurately assess patient needs. Robert Sczerba breaks down the aspects of your healthcare data that you haven’t thought about. The bottom line: If healthcare organizations find their way to the correct solution of accurately and efficiently managing patient data, it’s a win for everyone.

  1. First, healthcare data will only get more complex – and only advanced analytics tools in place will make sure that it is properly managed and utilized.
  2. Data errors are regularly included in the data analytics and medical record trails. The inaccuracies may come from patient behavior, the record trail itself or from the provider or physician and error rates range from 25-50%.
  3. Human error. With 8 Million new notes created every day organizations are just too overwhelmed to process that sheer volume of data accurately. Until hospitals and healthcare organizations adapt new technology that can transform vast amounts of data into real-time analytics at the point-of-care, mistakes will be made, reports will go overlooked, and patients won’t get the timely care they deserve.
  4. Critical findings are not being reported in a timely fashion. Time is of the essence when treating cancers and other maladies diagnosed from imaging services. Any delay can cause long-term effects that could have been easily avoided had there been a system in place to automatically notify patients as soon as a radiology report has been read.
  5. When applied correctly, healthcare data can be used to improve workflow – the trick is identifying the right tools.

The Data Analytics Journey: Healthcare Leaders Assess the Current Moment, and the Path Ahead, by Healthcare Informatics

Industry experts say that healthcare analytics is still in its infancy, and there remains “some degree of fuzziness regarding the path ahead”. The healthcare industry witnessed explosive growth in data use in 2014 and 2015 and is moving ahead now with the adoption of analytics in response to the demand by purchasers and payers to prove greater value for expenditure. However, most healthcare organizations are just beginning this journey and need to acquire the necessary resources to handle a comprehensive analytics program: the right tools, processes and people.

Are Big Data, Genomics, Precision Medicine the Cure for Cancer? By Health IT Analytics

The article argues that big data analytics solutions may play a significant role in curing cancer. Coupled with genomic sequencing, data analytics has the potential to harness the power of precision medicine and bring answers to some of medicine’s toughest questions. Large organizations are taking note and companies like IBM, Google, HP, Dell, and Intel are bringing their enterprise expertise in the healthcare industry. Cloud-based platforms are becoming viable solutions for integrating electronic health record data in a standardized way and complimenting the data provided by randomized clinical trials. Although the government is investing into modern technology solutions, it may be the vendor communities who will contribute the most for the best utilization of oncology big data.

The Bogus in Big Data, by Pharmaceutical executive

William Looney, the Editor-in-Chief of Pharm Exec, analyzes the New York Academy of Sciences talk on the implications of the big data revolution on drug development. Data analysis has the potential to take personalized medicine to a new level and provide both cost effectiveness and risk mitigation. While there’s no doubt that the data revolution is disrupting the traditional ways of commercialization of medicines, the biggest question for healthcare stakeholders remains how to turn data quantity into quality. Its volume and complexity hamper reliance to identify effective health solutions. Success lies in capitalizing on big data’s potential to drive understanding of how medicines affect patients in real world settings.