Data Analytics Success Requires a Human Touch

Technology in health care is in danger of going the way of the home exercise bike: Lots of potential, not enough use — and less-than-optimal results.

Take data analytics, for example. With more health care organizations than ever before using electronic health records, we’re finally getting what we have been asking for: A plethora of really good data that could inform decision making. In 2011, data from the U.S. health care system reached 150 exabytes. As growth continues, big data for U.S. health care will soon reach the zettabyte (1021 gigabytes) scale and, not long after, the yottabyte (1024 gigabytes), according to a report from the Institute for Health Technology Transformation. Kaiser Permanente, the California-based health network, which has more than 9 million members, is believed to have between 26.5 and 44 petabytes of potentially rich data from electronic health records, including images and annotations.

Certainly, if analyzed correctly, all this data could be used to vastly improve clinical decision support, disease surveillance, and population health management. In fact, a robust analytics platform can establish baselines and measure progress in better managing transitions of care, reducing readmissions, and documenting meaningful use requirements. And that’s just what emerging health care entities — such as accountable care organizations — are looking to do to succeed under the value-based care models that have emerged as a result of the Affordable Care Act.

A study from CHIME and the eHealth Initiative reveals a troubling sticking point. It shows that many health care organizations have not yet developed the strategic plans that will enable them to truly leverage analytics.

Organizations can’t just recognize the potential of analytics. They have to put a strategic plan together that will help them use analytics in their own specific situations.

Then, health care organizations actually have to put some boots on the ground. While technology is a fantastic tool, care planning and care management will always be a human endeavor. Consider the following: A recent study in the Journal of the American Board of Family Medicine regarding diabetes care management showed that the “the use of health coaches or nurses trained in diabetes self-management and active collaboration between practicing providers and key stakeholders in the development and dissemination of guidelines” are key elements of actually putting evidence-based best practices to use.

Just like the home exercise bike, data analytics is a tool with huge potential. But health care organizations both have to recognize that the tool is just a means. To get results, humans, themselves, have to put a plan in place — and then have the determination and where-with-all to implement it.



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