Informatics and Systems Innovation
What Does the Big Data Revolution Mean for Nursing?
School Gains Access to Clinical Data on More Than 140 Million Lives as Optum Labs Partner
by Barb Schlaefer - March 2014
Imagine that your focus as a nurse scientist is to identify the most effective treatment and intervention plan to prevent emergency hospital visits for adolescents with severe asthma.
Now consider the possibilities if you could quickly recruit and qualify 50,000 subjects for your next research study. For each “participant,” you know their diagnostics and treatment plans as well as rich contextual information encompassing demographics, environmental factors, lifestyle, physiological and psychological health, patient and family knowledge, observations and outcomes collected over time. It’s all there, standardized, and at your fingertips.
This is the new frontier in health research - the reuse of deidentified electronic health records of millions of patients to discover patterns, cluster variables, and identify predictors and interventions that lead to decidedly better outcomes for patients. Through analysis of massive repositories of de-identified electronic health records and claims data, researchers are able to efficiently generate hypotheses that can then be tested through statistical analysis and traditional clinical trials. This emerging field of data science involves using rapidly changing, immense and multi-level data to discover the most relevant, cost-effective treatments to support the health of individuals, families and communities.
The end game is speeding up the process of translating what can be learned from electronic health records into actions and standardized procedures to improve patient care. Nurses in practice, research and education are playing central roles in this emerging data science.
Changes in the field
Clinical nurses will see a growing emphasis on more comprehensive documentation and coding of patient data using standardized terminologies that facilitate integration of data across patients, domains, health systems and even continents. Computerized information systems and software applications will emerge that can be queried by busy practitioners at the point of care, enabling them to apply the experiences and evidence from hundreds of thousands of lives to the individual patient sitting in the exam room in real time.
Revolutionizing nursing science
The expanding use and reuse of electronic health record data for research will open doors not yet imagined, leading to valid evidence for safe and effective care. Nursing research capacity will increase exponentially as comprehensive electronic health records databases are efficient sources for data. Meanwhile, federal funding sources are beginning to shift to support the efficient and secure use of comprehensive electronic health records databases for outcomes research.
The School of Nursing recently signed on as a research partner with Optum Labs to gain access to a rich pool of de-identified clinical data and claims on more than 140 million lives. In addition, through the University of Minnesota’s Center for Translational Science Institute, School of Nursing researchers also can access data for more than 2 million patient lives that includes important contextual data. Currently the inclusion of nursing data is unique among health datasets nationally, but the School of Nursing is leading this change.
As the field evolves, informatics leaders anticipate an accelerating translational timeline from exploration to discovery to delivery of practice improvements.
Click to enlarge: An example of visualization techniques developed by PhD student Era Kim, which in this instance illustrates the impact of hospital interventions on identified problems over time
“With the right data, technology and mining approaches, the data can suggest hypotheses, which, until recently, may have been hidden due to the cognitive limitations of the human mind,” said Associate Professor Karen Monsen, PhD, RN, FAAN. Students and faculty are developing visualization tools and techniques, drawing on design principals including color, shape, hue and shade to show what the human mind cannot readily comprehend.
“The financial industry has long used charts and graphs to illustrate trends,” said Era Kim, a PhD student in the University of Minnesota Institute for Health Informatics who was advised by Monsen on her research. “New access to enormous and highly dimensional health records databases calls for creative approaches to support pattern detection and inference analysis.”
New career opportunities
Nurses’ understanding of health system structures and roles combined with broad patient knowledge make them strong candidates for emerging careers in the management, oversight, translation and analysis of electronic health record data. The University of Minnesota School of Nursing offers a Doctor of Nursing Practice degree in informatics taught by leading scholars and nurse researchers in the field. Scholars use the resources of the Center for Nursing Informatics, which is home to several national big data initiatives and is one of 11 accredited Centers for Classification of Nursing Practice Research and Development in the world.
Graduates combine their nursing experience with project and academic experience to secure jobs leading change within health systems, software development companies and in higher education teaching and research. “Today there are far more opportunities in this field than there are people qualified to accept them,” said Associate Professor Bonnie Westra, PhD, RN, FAAN, FACMI.