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6 Big Data analytics use cases for healthcare IT

Brian Eastwood | April 24, 2013
Making use of the petabytes of patient data that healthcare organizations possess requires extracting it from legacy systems, normalizing it and then building applications that can make sense of it. That's a tall order, but the facilities that pull it off can learn a lot.

The benefits of this process-in addition to meeting regulatory requirements-include research that takes into account demographic information as well as corollary tests related to specific treatments. This eliminates gaps in records that public health agencies often must fill with phone calls to already burdened healthcare organizations, Dixon notes. In return, the community data that physicians receive from public health agencies will be robust enough to offer what Dixon dubs "population health decision support."

5. Make Healthcare IT Vendors Articulate SOA Strategy

Dr. Mark Dente, managing director and chief medical officer for MBS Services, recommends that healthcare organizations "aggregate clinical data at whatever level you can afford to do it," then normalize that data (as others explain above). This capability to normalize data sets in part explains the growth and success of providers such as Kaiser Permanente and Intermountain Healthcare, he says.

To do this, you need to create modules and apps such as the ones D'Amore describes. This often requires linking contemporary data sets to legacy IT architecture. The MUMPS programming language, originally designed in 1966, has served healthcare's data processing needs well, but data extraction is difficult, Dente says.

Service oriented architecture is the answer, Dente says, because it can be built to host today's data sets-as well as tomorrow's, from sources that organizations don't even know they need yet. (This could range from personal medical devices to a patient's grocery store rewards card.) Challenge vendors on their SOA strategy, Dente says, and be wary of those who don't have one.

6. Use Free Public Health Data For Informed Strategic Planning

Strategic plans for healthcare organizations often resort to reactive responses to the competitive market and a "built it and they will come" mentality, says Les Jebson, director of the Diabetes Center of Excellence within the University of Florida Academic Health System. Taking a more proactive approach requires little more than a some programming know-how.

Using Google Maps and free public health data, the University of Florida created heat maps for municipalities based on numerous factors, from population growth to chronic disease rates, and compared those factors to the availability of medical services in those areas. When merged with internal data, strategic planning becomes both visually compelling (critical for C-level executives) and objective (critical for population health management), Jebson says.

With this mapping, for example, the university found three Florida counties that were underserved for breast cancer screening and thus redirected its mobile care units accordingly.

 

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