Recent studies have demonstrated that by using big data tools and database experts for integrating, normalizing and analyzing more information faster, the healthcare industry will be able to better meet objectives for managing patients.
A survey by IDC Health Insights reported that 66 percent of healthcare organizations plan to use analytics to better identify patients and members in need of care management. Another 64 percent of respondents intend to use planned analysis for clinical outcomes, and the same percentage will use the analytics to manage and measure performance. An additional 57 percent of respondents cited clinical decision-making at the point of care as a top priority for planned analysis. IDC explained that failures to improve quality and control costs are often due to inadequate data that is in an unusable format. Cynthia Burghard, research director for accountable care IT strategies at he research firm, commented on these analytic initiatives.
"Access to timely, complete, accurate, contextual, and digestible data is the lynch-pin for accountable care success," she stated.
Further research by IDC revealed that investments in data monitoring, mining and social graph analysis are top priorities in 2013. New data sources have also provided enhanced analytic advantages. While 42 percent of respondents cited mobile devices as a top priority in seizing analytics opportunities, another 32 percent cited social media and 29 percent emphasized unstructured clinical data.
InformationWeek reported that The UCLA Department of Neurosurgery in Los Angeles has already begun experimenting with the application of big data analytics to examine real-time information collected from patients' monitors. The new software can spot subtle changes in patients' vital signs in real-time by streaming and analyzing pulse, heart activity, blood and intracranial pressure and respiration. IBM fellow and Big Data Chief Architect Nagui Halim told the source that traditional clinical care involves a lot of time-consuming circulation for physicians and nurses, and handoffs between shifts leads to further inefficiencies. Big data technologies automate the process of observing patients' condition so that doctors can more quickly make decisions regarding the individual's current state and future health. UCLA's application of these technologies will be useful in studying the impact of intracranial pressure on brain-trauma patients. According to InformationWeek, the school received a $1.2 million grant for this research, which will include a predictive alarm system.
Mining big data and automating analytic processes can empower the healthcare industry to overcome challenges to ensuring consistent, accurate and high-quality diagnosis and treatment.
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