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BigData & Healthcare Connections!!

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In my previous blog article talked about “BPM and Healthcare Connections

Here am back again….with the BigData and Healthcare Connection!!

Bigdata” is the most talked about buzz word these days be it any meeting, discussion, conference or event. It looks very promising considering the data (structured/unstructured) used for analytics and predictions than the regular transactional data.

The other field/domain that is catching-up these days after the BFSI(Banking & Financial Services – saturated by the IT implementations) is the Healthcare and Lifesciences domain!!. With the current steps, reforms and measures taken by the Government of US – all eyes are focused on this sector.

On what ground can we say BigData sounds promising in the Healthcare arena ?

Every time we step in to a hospital or do a medical checkup (blood pressure, ecg, ultrasound….etc…) the end result is some data points. The sensors used for monitoring the health of a patient or informations shared via social media everything adds on, making the data heavy and rich.

As someone has very rightly said “‘In God we trust. For all others, bring on the data’” 🙂

So, the data we collect in all these cases can be channelized to do some predictive analytics and study for assisting the patients better.

Quick snapshot of the channels via which we get all the health related data :

Business Benefits :

The business benefits we can think of, based on the predictive analytics done on the patient data are :

  • Better assistance to Patients at reasonable cost
  • Less burden on the Insurance Companies (as most of the data can be used to predict the health condition of the people and reduce unnecessary claims)
  • Reduction in hospital cost
  • Maintaining records of Patient data from multiple channels
  • ….and many more

 The “4Vs” :

From a Bigdata perspective “4Vs” that are pronounced loudly are shown in the image below

If we try to quickly relate it from a healthcare front :

Volume : 

  1. Lab Test Data
  2. Patient Data
  3. Drug Details
  4. Clinical Records and Sensor Data
  5. Scan, ECG and X Rays

Variety :

  1. Unstructured
  2. Multiple channel data
  3. Photos and videos

Velocity :

  1. Clinical Research
  2. Real time analytics
  3. Predictive analytics
  4. Archived Data
  5. Pattern of symptoms for patients

Value :

  1. Monitoring Patients
  2. Individual Test data
  3. Reported Results

So, this was a quick stab from my end as an amateur for connecting bigdata and healthcare  🙂

Veterans and Professionals in this arena can definitely throw some more insightful information in this context.


Happy Learning!! 🙂


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