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Digital Data Analytics Solutions for Healthcare Raw Data

Healthcare organisations collect and store large quantities of patient data - admission details, diagnostic reports, treatment lines, discharge data, details of all virtual interactions between providers and patients, and data on the providers. All these data varieties are immensely valuable and contain the potential to improve care and other services. However, this huge storehouse of raw data was largely underutilised until recent times. It is still a work in progress and the industry has probably just touched the tip of the iceberg.

Here’s an interesting fact - between 2010 and 2020, global raw data increased by 5,000%. Once it is analysed and converted to business intelligence, almost every industry stands to gain from it. The evolving healthcare industry is also poised to benefit tremendously. In fact, the healthcare industry is responsible for  30% of the global data volume. In 2020, the global healthcare analytics market was valued at USD 23.6 billion and is expected to grow at a compound annual growth rate of 23.8% from 2021 to 2028.


Digital health solutions are here to stay

Healthcare industry is undoubtedly complex, and gaining consensus on any issue is a challenge. A consensus is that digital health solutions have and will continue to transform treatment options and healthcare delivery. The Covid-19 pandemic forced healthcare to quickly adopt digital health tools. It’s been happening all around us - tele-health, social determinants of health (SDoH) databases, personal devices to access care and data storage solutions are some examples.


Data analytics in healthcare

The healthcare industry is constantly struggling to convert huge amounts of data it generates into a form that improves operational efficiency and patient outcome. The application of advanced analytical techniques and the continuous growth of data are expected to affect all areas of healthcare - from cancer treatment, disease prediction, and drug discovery to the use of artificial intelligence (AI) in diagnostics, calculating accuracy of insurance rates, and automation of administrative processes.

The purpose of data analytics in healthcare is many-fold:

  1. Make the data easier for the public to visualise as well as share among fellow healthcare providers and external partners. Additionally, healthcare professionals must have ready access to relevant data, in an easily usable form.
  2. Provide data-powered forecasts so that healthcare providers can respond quickly to changing environments and markets.
  3. Enhance data collaboration and innovation among healthcare organisations and convert data into business intelligence. This is achievable through automating low-impact data management tasks.
  4. Besides collection, analysis and interpretation, the data must be secured too.

An overarching digital solution to improve an organization’s “sentience”, the essential quality that makes every customer interaction value-adding, can help in this regard.*


How can data analytics be used in healthcare?

Data analytics can be applied to many facets of healthcare. Some of the areas that would be most impacted are:

  1. Automation of hospital administrative processes
  2. Discovery of new drugs
  3. Early diagnosis
  4. More accurate calculation of health insurance premium
  5. More effective sharing of patient data
  6. Research and prediction of diseases
  7. Personalised patient care
  8. Prevention of unnecessary doctor’s visits

There are data analytics organisations working with oncologists to get quick access to cancer research pertinent to a patient, and, thereby enhancing the outcome through personalised treatment path. In other examples, public health officials are known to be using data analytics to prevent diseases and identify high-risk individuals. A data analytics organisation in this sector uses NLP (natural language processing) to analyse raw patient data from health records to identify lifestyle factors associated with high-risk patients.


Data security cannot be ignored

Healthcare data is highly sensitive, and the existence of multiplying amounts of data underlines that security is of utmost importance. So far, IT investment in healthcare has been one of the lowest; the hacking of patient records and ransomware attacks have become quite common.

Perhaps it is not very astonishing that patient care initiatives take precedence over cyber security measures. It cannot be ignored any longer, and healthcare organisations must invest in health IT as well as data analytics.

* For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.