Category Archives for "Applications of Analytics"

Oct 31

Four Use Cases for Healthcare Predictive Analytics, Big Data

By ganpati | Applications of Analytics

Predictive analytics in healthcare has long been the wave of the future: an ultimate goal to which everyone aspires but few can claim success. While the landscape is changing for healthcare predictive analytics as more organizations figure out how to harness big data and implement the right infrastructure for generating actionable insights from a slew of new sources, some providers may still be wondering how the pie-in-the-sky world of big data can actually work for them.

Luckily, a number of pioneering organizations have taken it upon themselves to test the waters of healthcare predictive analytics, generating use cases that spur interest and help carve a path through the wilderness. This article explores some of the ways healthcare organizations have already found success by turning big data into a strategic asset that can help providers react quickly and effectively to the ongoing challenges of quality care delivery.

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Oct 31

Data Aggregation and the Single Source of Healthcare Analytics Truth

By ganpati | Applications of Analytics

In the healthcare industry, data is everywhere. It is frequently fragmented among a variety of information systems, such as electronic health records, laboratory systems, radiology systems, adjudicated claims, spreadsheets, databases, and more that may or may not be compatible. Data ownership is often siloed at the team or departmental level, which hinders an organization’s ability to standardize or validate it. In this scenario, it’s easy to pick and choose data to provide support for a variety of viewpoints. But this method of “data shopping” provides no strategic insight into what’s really happening within the organization and prevents leadership from making data-driven decisions.

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Oct 31

Health Analytics Using Process Mining

By ganpati | Applications of Analytics

In many countries, healthcare organizations, such as hospitals, are under increasing pressure to improve productivity and reduce costs. Specifically, in most Western nations, the demand for hospital services is growing. Prolonged medical care for an ageing population, increasing costs associated with the management of chronic diseases, innovative but costly treatment possibilities, and the need for more healthcare personnel put pressure on care organizations. In order to deal with this situation, hospitals need to control and improve their care processes such that they are executed more efficiently and effectively.

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