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Healthcare industry sees big data as more than a bandage

Allen Bernard | Aug. 6, 2013
The promise of big data in healthcare—increased efficiencies, better outcomes, more personalized care—is undeniable. How the industry reaches the promise land will happen in many stages, but hospitals and insurers aren't wasting any time getting started.

From integrated healthcare giants like Kaiser Permanente, the University of Pittsburgh Medical Center (UPMC) and United Healthcare to solitary 25-bed community hospitals, big data is finding its way into how they go about the day-to-day business of providing care.

Hospitals and health insurers are applying big data in three primary and related ways: Improving care of chronic diseases, uncovering the clinical effectiveness of treatments and reducing readmissions. These improvements are expected to provide the most benefit for the entire healthcare system in the shortest amount of time. (All three come with a hefty price tag, though, both for the healthcare system and society at large—not to mention the hospitals that don't get them under control.)

Medicare, the single largest insurer in the United States, drives many of these changes. Medicare either has begun or will begin to impose penalties on hospitals that don't improve care in three critical areas:

  • The 30-day readmission rate of patients with acute myocardial infarction, heart failure or pneumonia
  • The meaningful use of electronic health record (EHR) systems
  • Beginning in 2014, hospital-acquired conditions, which you don't have when you are admitted but contract while you're in the hospital.

"If you play this out, in 2017 those three programs will account for 6 percent of a hospital's Medicare revenue being at risk. That's not trivial money for most hospitals," says Dr. Anita Karcz, chief medical officer at the nonprofit Institute for Health Metrics. IHM works with community hospitals on compliance and reporting and performs clinical effectiveness research on breast cancer surgery, total hip and knee replacement and readmissions risk by data mining the combined de-identified data sets of its customer hospitals.

Costs, Outcomes Driving Big Data in Healthcare
It's this combination of cost and outcomes that's the focus of most big data efforts today. Around the globe, aging populations are putting severe strain on national resources. These costs are projected to increase dramatically as percentage of GDP if the treatment of widespread age-related chronic conditions like diabetes, obesity and heart disease are not brought under control.

Health insurers' disease management programs, for example, aim to predict which customers are at risk for conditions such as diabetes or heart disease and then help them change their behavior, says Thomas Davenport, visiting professor at Harvard Business School and co-author of the recently published big data tome Keeping Up with the Quants.

That is where companies such as Scottish bioinformatics firm Aridhia enter the picture. Aridhia is working with the United Kingdom's National Health System to cut readmissions for 200,000 patients. Using the 80/20 rule, the initiative focuses on the 20 percent of patients who end up consuming, in any society, up to 80 percent of the available healthcare resources.

 

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