Using big data can improve medical outcomes and efficiency, article contends.
Using “big data” to analyze information gathered by health IT is the key to improving medical outcomes, as well as making health care more efficient and cost-effective, say the authors of an article published online recently by the American Health Information Management Association.
“Today’s episode-oriented discrete data does not allow us to be as prescriptive as we need to be in delivering better health care and empowering consumers,” says Lisa Khorey, vice president of enterprise systems and data management, information technology at the University of Pittsburgh Medical Center, in the article. “Medicine can get closer to the action when it is prescriptive, predictive, and precise. Big Data allows organizations to focus on wellness and standardize care processes.”
The article, “Big Data, Bigger Outcomes,” by Lorraine Fernandes, Michele O’Connor and Victoria Weaver, argues that integrating big data into their operations lets providers “apply analytics to better understand the clinical and operational states of their business based on historical and current trends, and predict what might occur in the future with a trusted level of reliability.”
To realize the potential of big data on health care, the authors outline a four-step process for implementation:
- Establish data governance and define data objectives.
- Identify data and information requirements.
- Normalize, integrate and organize big-data solutions
- Protect security and privacy of big data.
“Big data offers [health information management] professionals the chance to play a strategic role in crafting the next level of health-care information management, and act as key stakeholders in advancing the strategic use of big data across the health-care ecosystem,” the authors contend.
“As the industry transforms,” they continue, “it becomes essential for HIM professionals to move beyond the principles of record maintenance and documentation and develop an understanding for data transport, mapping processes, and other big data characteristics.”