Healthcare& Life Science Analytics

Healthcare Analytics & Insights: Overview

Healthcare industry has been facing pressure from government, insurance industry and customer to provide quality healthcare at an affordable price. Healthcare cost as % of GPD across countries has gone up, e.g. from sub 6% to over 17% in US.


Healthcare organizations both profit and non-profit have objective to provide Accessible, Cost effective and Quality Healthcare and face pressure due to increased competition, government regulations and customer expectation for delivering on the objectives.

Key entities involved in providing healthcare are Patients, Government, Healthcare Organization and Insurance Providers.


Expecting to get healthcare accessible, quality and cost effective care from the healthcare organizations.


Monitor healthcare industry, and build & enforce regulatory framework to safeguard interest of the patients.

Health Care Organization:

Deliver healthcare to the patients and they look for ways to be effective & efficient, competitive and relevant to the patients, doctors & staffs and shareholders.

Health Insurers:

Health insurers absorb risk of healthcare cost for the individuals. They work to estimate healthcare cost across a list of diseases for underwriting risk for each segment appropriately.

Data Sources -> Process & Analytics -> Insights & Recommendations -> Value: Cost & Life Save

Due to increased digitization and availability of data (patient health records, Prescription information, clinical trial data, claim data,genomics sequences, sensor readings etc ), healthcare industry has been ahead of other industries in employing data analytics and statistical modeling. Data Analytics & Insights can help in improving process efficiency, personalizing medicines for the patients, generating triggers based on patterns of customer health indicators and developing new medicines.

Analytics and Insights themes used in healthcare are:-

  • Evidence Based Diagnosis Analytics:
  • Clinical Research & Analytics
  • “What if” Analytics: Creating scenario and insights even without running physical experiments
  • Prescription Analytics:
  • Patient Care Process Analytics: Collect & analyze data from patient admission to discharge and provide action for process effectiveness and efficiency