Analytics in healthcare enables smarter decisions to be made
Healthcare organizations today understand the value of data and how analytics technology can solve many of their biggest challenges, streamline processes, increase staff productivity and improve patient outcomes. However, the implementation may be more complicated than expected. One of the biggest obstacles to using big data in healthcare is finding the right platforms and solutions for analyzing unstructured data, which often accounts for more than two-thirds of a clinic’s total data collection. Pure Storage provides an insight into how the management and evaluation of unstructured data is both a challenge and an opportunity at the same time.
In contrast to structured data, such as demographic data or treatment information in the electronic medical record (EPO), unstructured data is difficult to organize, categorize and search.
They can consist of:
- Image files, e.g. X-ray images and video material
- Free text content, such as a nurse’s notes in a patient record, for example, when someone says: “I have a dull pain on the right side.“
- Patient photos of wounds or injuries
- Information on voice search
- Comments from site users
- Data of medical devices
Decades ago, according to Pure Storage, it was virtually impossible to correlate all this data from so many different sources and gain actionable insights from it. This was simply beyond human capabilities. With today’s technology, this is changing.
The Power of AI and Machine Learning
Artificial intelligence has massively advanced the field of data analysis. Increasingly intelligent algorithms have been developed to recognize patterns, analyze human language in all its imperfect forms, and make meaningful connections between millions of scattered data points. With the help of AI and machine learning as well as related tools such as natural language processing and text mining, unstructured data reveals its previously hidden secrets and provides new insights about patients and processes.
The following are some examples of what these findings can do for the healthcare sector:
- Detection of gaps in care, e.g. of processes that do not work, or of situations in which certain patients fall through the cracks.
- More accurate identification of cancer cells using an intelligent system that has been taught to recognize specific markers of the disease.
- Detect hidden trends in admissions, such as a high number of patients admitted to the emergency department of several hospitals from a certain location, which could indicate environmental causes.
- Support the nursing staff in providing information through machine-read medical journals, which then forward the most important information to the people who need it.
- Detection of potential fraud, e.g. in patients who exhibit drug-addicted behavior or abuse opioids.
- More efficient customer service by analyzing notes in contact management and understanding positive and negative interactions.
- Prediction of diagnostic warning signals through doctor’s notes, which are evaluated to identify and predict disease outbreaks, treatment complications and much more.
How to simplify the use of unstructured data
Finding the right technology to unlock the value of unstructured data in healthcare is critical. This also includes finding the right solution for storing and managing this data. However, the challenge of storing unstructured data is that it often comes in multiple types, including files and objects. Older storage systems separated the types and made it difficult to manage and access all this data in an integrated way. This is where Unified Fast File and Object (UFFO) Storage comes in, a high-performance, scalable solution for all unstructured data. It is intuitive, flexible and powerful enough to handle even extensive analytics in healthcare and AI/ML workloads. UFFO-Storage scales with the growth of the company and is thus ready to ensure competitiveness.