Navigating Big Data

This entry is part 1 of 2 in the series Seeing the Big Picture in Big Data

Those of us in health care imagine large quantities of useful, easily accessible, accurate and meaningful data at our fingertips, helping us improve the way we provide individual patient care while reducing costs and advancing health care systemically. Unfortunately, while this is where we want to be “when health care grows up,” we’re not there yet. Are we even close? Yes – we have access to more data than ever before, but the expertise we need to sift through this data and understand its impact on both individual patient care and systemic change is still “on the drawing board.”

In 2008, Hersh and colleagues reported on one of the first modern Health Information Technology (HIT) workforce studies. 1

] They proposed that to support the rapid adoption of clinical information systems, the U.S. health care delivery system needed at least 40,000 new HIT professionals, an estimate recently adjusted even higher. This study also led the Office of the National Coordinator (ONC) to fund training programs for developing 12 new HIT work roles. Six of these roles require university-based training and include: clinician/public health leader, health information management and exchange specialist, and research and development scientist. The remaining roles require up to six months of intense training and include: practice workflow and information management redesign specialist, implementation support specialist and technical/software support staff.

The skills and competencies of these 12 roles focused on workforce support required for U.S. HIT adoption over the last decade – skills such as requirements definition and clinical system acquisition and implementation. With these phases mostly completed, many major organizations now envision a next phase.

With apologies for leaning on an over-used buzzword, we enter an era of “big data,” or very large and complicated data difficult to analyze using traditionally available database management tools. Data analysis, examining data to understand it, and data analytics, discovering and communicating meaningful data patterns, are central to health system transformation and improving individual patient care at lower costs. With reliance on clinical systems, most health care delivery organizations now have an almost infinite amount of data from individual electronic patient records – all of which could prove valuable to new or improved data examination.

We find ourselves in this situation somewhat by surprise. Health care, like most industries, is highly data and information intensive. By definition and necessity, health care is an IT industry – and IT solutions serve two primary purposes: collecting AND examining data. Over the last decade health care leapt from analog to digital at an extremely high rate of speed, with  our attention focused almost single-mindedly on IT’s data collection aspect. When preparing requirements, acquiring and implementing electronic health records, we focused primarily on features and functions for data input and considerably less on data examination needs once we entered that data.

This leads us to where we are today – “Gosh, now that we have all this data, how can we use it?”

Not only is our HIT workforce missing the full range of competencies for examining data, we now realize just how challenging this work is. The sheer data volume is daunting, but the biggest part of the challenge is the quality (or more accurately the lack thereof) of the data we now have available. Because we never fully defined requirements for it, we are not sure how to effectively analyze the data we are now collecting – and we failed to adequately define, acquire or implement our new systems with this in mind.

It isn’t surprising then that recent efforts to assess HIT workforce needs draw attention to this dilemma. In early 2012, Fenton 2 and her colleagues published the results of a large workforce assessment where they completed surveys and focus groups with over 50 Texas health care delivery organization leaders, asking  about their views on current and future workforce skills and competencies. Their findings are much like prior results. For example, employers indicated that most current employees have sufficient basic HIT skills (medical terminology, basic computer skills, and understanding patient information flow). However, their current staff have less proficiency and require more training at both intermediate (e.g., data management, data mining/report creation, data sharing, problem solving and critical thinking) and advanced (e.g., ability to implement and manage HIT to support strategic plans, use data for planning and management purposes, and design databases/systems to support organizational goals) levels.

This piece first appeared in the Journal of Healthcare Information Management (JHIM) Spring 2013 / Volume 27 / Number 2 issue.

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Posted on April 5th, 2013 in Innovating Health Care IT
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