In this new world, where analytics is the basis of any business decision, data-driven analysis has become crucial, and the job of a data scientist has become one of the most lucrative in healthcare. At NTT DATA Services, we work with some of the largest life sciences organizations and health systems in the world, and constantly see the need for highly skilled data scientists to turn the proliferation of electronic information into insight that helps our clients improve quality of care while lowering costs.
Until recently, healthcare data (i.e., patient records, medical images, etc.) would be printed and stored; making the information largely inaccessible when it was needed. Sharing and accessing historical patient data used to be difficult, leading to insufficient information for real-time decision-making. Today, as the industry adopts digital storage of data, there is an opportunity to improve patient care by enabling healthcare professionals with actionable insight. And accessibility of data goes beyond digital storage; it includes other facets, such as quality-improved information, multi-source integrated views, advanced indexing, and real-time availability, just to name a few.
Today, industry experts believe that patient care can be augmented with useful data captured from a variety of sources, such as wearable devices. This data is very different than data from traditional sources, such as Electronic Health Records (EHRs). Wearables offer the ability to capture more information — lots more of it — at a more granular level, and in real-time than what point-in-time health records offer. However, with scale comes noise and non-relevant data. Therefore, two questions arise: whether organizations can leverage newer data sources to identify beneficial patterns and can making sense of this healthcare “big data” be done by statisticians?
Data scientists need to have the domain knowledge to be successful. For healthcare, it is important to understand the accuracy and the relevance of the data collected. It is important to understand whether data, such as the heart rate for the last few months, is relevant information that can help in diagnosis or the identification of relevant medication recommendation. We believe Healthcare Information Management (HIM) professionals, with the right training, can transform and perform the role of data scientists. Most of these scientists already understand the specialized field of healthcare technology. This gives HIM experts an advantage when considering specialization, but they still must invest in learning the skills required to be a data scientist.
NTT DATA’s Adam Nelson and Mayank Gandhi recently spoke to Lisa A. Eramo about how data science relates to HIM. You can read most of their discussion in Discovery Mission, which appeared in the March issue of For the Record. This article explores how data science has increased astronomically in healthcare over the last decade, and the struggles mid-size or smaller hospitals are having due to the budget needed to support a full-fledged data analytics function within these organizations. As a result, many hospitals and clinics are turning to companies dedicated to analytics and data science.
Looking forward, the need to have a data scientist in-house will grow, and the need for more qualified people to fill these roles will increase exponentially.