The Rise of Analytics in Healthcare

Recently published a study revealing that today only 50 percent of healthcare organizations make extensive use of analytics. Yet, the rest are getting started (40 percent) or are planning to implement (10 percent) – see Figure 1. This is no surprise. Like many industries, healthcare seeks to improve efficiency and reduce costs using analytics. But unlike many other industries, healthcare is a heavily regulated sector, shifting from a pay for service culture to a pay for performance approach. This requires healthcare providers to measure their quality of care performance metrics. In addition, the rise of evidence-based medicine is creating demand for analytics. Advanced analytics help providers gain scientific evidence for clinical treatments, instead of only using their conventional wisdom.

Figure 1

Among many interesting points, one interesting angle that the survey revealed is the predominant types of analytic functions that healthcare providers are looking to use in the near future. Based on this data in Figure 2, the two top analytics functions that the CIOs plan to use in the next two years include:

  • 1. Health Information Exchange (42%)
  • 2. Predictive Analysis of Diseases (43.6%)

Figure 2

Let’s explore the reasons behind each one:

Health Information Exchange

Historically, healthcare information systems have been built around special departmental needs. For example, a radiology department uses its own information system to log patient data, while laboratory services, patient admissions and urgent care each use their own systems to store information. This creates information silos, trapping patient data across multiple sources.

With the increasing populations of patients and higher demands for quality of care, having a single view of patients information has become much more important than what it used to be. However, because each of the information systems stores data in a particular shape, size, and format, creating a holistic view of a patient becomes increasingly harder.

To cope with this issue, HL7, a non-profit organization, has developed a set of standards for exchanging healthcare information. By using common standards, different information systems can communicate, exchange, and share information much easier.

Today HL7 is an international framework for information exchange among different healthcare organizations. More and more hospitals, health centers and medical services are adopting HL7 every day. With the growing adoption of these standards, the demand for data integration tools that can retrieve information from different repositories, parse, consolidate and transform it into these standards has become extremely high.

A vivid example of how better integration and exchange of health information has helped a healthcare organization accelerate its quality of care is St. Antonius Hospital. Based in The Netherlands and with six locations around Utrecht, St. Antonius Hospital uses Pentaho Business Analytics to build a holistic view of both hospital activities and patients. By using Pentaho as the central business analytics platform, St. Antonius was able to break down departmental silos, making data analysis available to the entire hospital staff, providing highest quality of care over a half-million patients a year.

Interested to find out how St. Antonius was able to overcome its health information challenges? Register for the webinar on December 1st: St. Antonius Hospital Improves Patient Services with Better Data Access and Analysis.

Stay tuned – in Part 2 of this blog, we will explore the reasons behind the high growth of Predictive Analysis of Diseases.

– Farnaz Erfan