Citizens around the world want a health system that is accessible, unrestricted, affordable and high quality. Most governments are recognizing this and shifting from traditional fee for service model towards the fee for value or outcome-based care.

• How is data analytics impacting the health care industry?

There is tremendous pressure to balance better patient outcomes  with a healthier bottom line. Data-informed decisions is taking priority over ‘gut’ decisions. Additionally, more healthcare organizations are embracing paperless systems both from an operational and clinical perspective. They want to have a tool that can combine internal and external data for a comprehensive view of their patients or a specific business function..

• More precisely, what can prediction data analytics do for the health care industry?

Modern analytics tools are allowing healthcare organizations to use data science or predictive tools to generate richer insights from their data and embed them within routine workflows. Whether it is used to predict wait times or readmission rates, presentations to the emergency department or even the risk of diabetes, predictive analytics offers incredibly powerful use cases within healthcare. It can enable health professionals and organizations to take a more proactive approach to patient management and get ahead of the curve.

• The relevance of data analytics in the current crisis? Has it helped or impacted in COVID-19 situation?

It indeed has. One of the risks in crises like this is the overflow of data that is distributed and available. The incorrect use or understanding can have detrimental effects on both operations and patients' safety. Delivering that data in a governed environment, under approved dimensions and measures means it can enable the users to have a consistent and trusted view of the information they have to act on.

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Sophia

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Journal of Health Policy & Management.

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