Personalizing Healthcare with Big Data & Clinical Analytics

A growing number of healthcare organizations view data and analytics as instrumental to achieving their objectives for improved quality and reduced cost. Glenn D. Steele Jr., MD, CEO of Geisinger, recently outlined how his organization is using analytics to advance their population health initiatives.

While healthcare is currently behind other industries when it comes to use of business intelligence and analytics, this is changing. The fundamental transformation driving this change is the (worldwide) migration from volume-based care to value-based care. Organizations with the capacity to optimize care based on the latest medical literature, their patients’ specific condition(s), and, ultimately, their genomic profile, will survive. Those that are unable to update their culture, rely only on personal experience, medical training, and (often times) a trial and error approach, will be left behind.

The above video excerpt from the Intel Health & Life Sciences Innovation Summit panel, Care Customization: Applying Big Data to Clinical Analytics & Life Sciences, lets you hear how leaders from provider, payer, life sciences and analytics organizations describe key use cases they have implemented, infrastructure trends, and practical steps to get started.

While payers are typically farther along in their use of analytics than providers (particularly in the area of claims analytics to optimize claims processing and reduce false claims), providers are using analytics in the following (representative) areas:

  • Reduce unplanned readmissions
  • Reduce hospital acquired infections
  • Identify cost inefficiencies
  • Measure quality / outcome improvements (across a health system if applicable)

One of the key barriers to the use of analytics we often see in healthcare is the organizational culture. This can be challenging as culture is something that doesn’t change overnight. So what can we do about it? I will leave you with two pieces of simple advice:

  1. Identify a clinical champion: Culture change won’t happen based on a top-down approach or through programs driven exclusively by the IT department. There must be a partnership between IT and the clinical side of the house to identify needs and create value for the organization.
  2. Start with real use cases: Before you build anything, identify a small set of use cases that will deliver value and demonstrate early success for your organization. Build on that success to scale.

Are you deploying big data or analytics solutions in your organizations?

Chris Gough is a lead solutions architect in the Intel Health & Life Sciences Group and a frequent blog contributor.

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