Spotlight: Healthcare Analytics

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How can patient data be used to detect significant geographic trends in disease?

Is the Hospital Standardized Mortality Rates (HSMR) within limits?

Does the re-admissions rate within 30, and 90 days, reveal a significant pattern for any physician or department?

How can performance metrics be applied to detect hospital mismanagement?

As healthcare comes within the reach of common people and foreign patients flock to India for medical treatment, the healthcare sector in India is witnessing a boom like never before. Hospital and healthcare chains in the private sector have been mushrooming all over the country. This has triggered an aggressively competitive environment in the healthcare industry. Government regulations and stress on hospital performance have therefore compelled hospitals to store massive volume of structured and unstructured data. To make sense of all this patient and hospital data, advanced analytics and metrics are applied for internal business insights and public health intelligence. For instance keeping check on healthcare irregularities, gross anomalies in hospital procedures, trends in admissions; besides extending insights to health related sciences and insurance.

The value of analytics in healthcare on both the clinical and business fronts is increasingly being felt. Although Descriptive analytics is already in practice, the need for predictive and prescriptive analytics in healthcare is fast growing.

It has been estimated that the global Healthcare Data Analytics market will grow at a CAGR of approximately 25.2% from 2013 to 2020, from the currently estimated $4,430.9 million(2013) to $21,346.4 million by 2020.  

In India, the healthcare analytics market is expected to grow to $120 billion by 2015, with data analytics and big data featuring prominently, as healthcare sector ushers in a data revolution.

So what is healthcare analytics?

Healthcare analytics or health analytics is the application of analytics and modelling to gain insights into the massive and complex data; unlock and apply such insights to drive clinical and operational improvements. This includes traditional transaction monitoring together with embedded real-time predictive analytics models to enable organisations to create dynamic and personalised healthcare, fraud detection and predict patient behavior for a business edge.

As health IT becomes more advanced with increased adoption of cloud and sophisticated database management technologies, the emergence of Big Data in healthcare has fueled analytics in a wide range of applications.

By Type

  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics

By Application

  • Clinical Analytics

     ~  Quality Care

     ~ Medical Error Reduction

     ~ Physician Performance Evaluation

     ~ Customer Relationship Management (CRM)

  • Financial and Health Insurance Analytics

       ~  Claims Analytics

       ~ Revenue Cycle Management (RCM)

       ~ Risk Management Analytics

  • Operational and Administrative Analytics

       ~ Supply Chain Analytics

       ~ Human Resource/Workforce Analytics

       ~ Strategic Analytics

       ~ Real-time forecasting

  •  Efficiency in Life Science and Social Science

            ~ Advanced analytics for better understanding of disease, identification of next    

               generation healthcare systems, optimization of strategies for drug discovery,

               clinical trials, sales, marketing, and manufacturing.

  • Public Health Analytics

Healthcare data is not standalone patient information data, but also medical imaging and diagnostic data, genetic data, epidemiological data, disease data, hospital admissions data, re-admissions data, medical insurance data, and much more. All of this constitutes a huge database in structured and unstructured data (both internal and external), that needs to be analysed in real-time for wide applications and scenarios.

As healthcare analytics becomes critical, the healthcare industry in India currently faces shortage of analysts capable of applying analytics to a Big Data ecosystem in the health sector.

For the student of data science, social science and analytics, the healthcare industry offers an excellent scope to work in a dynamic environment of healthcare sector where analytics has a philanthropic element.

 

Suggested Read:

IBM Executive Report – The value of analytics in healthcare


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