HEALTH INFORMATICS 

Healthcare Analytics

Resolving complex business problems by leveraging modern technologies and deep expertise in analytics, mobility , cybersecurity and digital sourcing

 

Analytics in Healthcare can be used to implement various descriptive, predictive and prescriptive use cases in healthcare. Healthcare organizations are heavily investing on integrating care delivery across the value chain. With a wide adoption of digital and mobile technologies, niche players are rapidly innovating to bridge the gap between consumer, provider, payer, regulator and researchers. Secondary use of healthcare data is emerging as a key component of the data infrastructure for care providers to achieve their care quality, operational efficiencies, real world evidence and compliance requirements.
Convergence of healthcare and life sciences with complete bench to bedside collaboration is helping achieve newer scientific frontiers for care providers. New biomarkers and diagnostics are helping healthcare organizations to bring innovative treatments faster to patients and in saving lives.


Healthcare organizations are looking to leverage data and analytics to improve patient experience and address regulatory needs effectively. By adopting mobility and digitization and effectively generating insights, healthcare organizations ranging from single-physician offices to multi-provider groups, large hospital networks, and accountable care organizations can realize significant benefits. Some key potential benefits:

  • Healthier lifestyle and better care

  • Patient-centric personalized medicine

  • Reduction in cost of care

  • Early detection of diseases driven by data

  • Fraud detection

  • Improved satisfaction

 

Analytics is playing a major role in transforming the healthcare industry. Here are some key analytics solutions for healthcare:

  • Improved fraud detection – Analyze large numbers of claim requests to detect and reduce fraud, waste and abuse (repeat billing, fake prescriptions, fictitious claims etc.) more quickly and efficiently

  • Healthier lifestyle and better care – Capture and analyze data to help providers recommend healthier lifestyle choices to patients

  • Patient-centric personalized medicine – Genetics, biomedics and big data can help deliver personalized medicine

  • Early detection of diseases - Detecting diseases at earlier stages when they can be treated more easily and effectively through patient data analytics

  • Improved satisfaction – Improved patient and provider satisfaction driven by improved quality of information available

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