Predictive analytics: Roadmap to realize value from healthcare big data

A data-driven approach to healthcare delivery is the new standard key stakeholders – providers, payers, pharmaceutical companies and more – rely on to control costs while improving outcomes. Digitization of data is making this possible. From clinical and medical claims, electronic medical record (EMR), clinical trials, genomics and IoT data, to structured and unstructured data generated by patients and devices, digitalized data is paving way for evidence-based practice and personalized medicine. Data assets are now becoming new competitive advantages among healthcare organizations.       

Apart from traditional retrospective analytics and quality measure reporting, healthcare organizations are now investing in meaningful advanced analytic solutions such as predictive analytics and data mining, which will allow healthcare stakeholders to use digitized information to provide real-time clinical decision support, improve care and control costs.

The five V’s of healthcare data

Today, as healthcare is generating data in huge volume, with diverse variety, velocity and with improved veracity, big data is becoming the default solution to store, aggregate and process health information. The marriage of big data and predictive analytics is what enables the fifth ‘v’ of healthcare data: value.

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