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Big data within the medical industry will be close to to get even bigger due to the move toward electronic health records. Electronic medical records are getting a boost because of the implementation of the Affordable Care Act. As such, medical researchers may anticipate an enormous influx of healthcare data to analyze.

The scientific community is abuzz about the potential for big data within the medical research arena. According to Science 2.0, a science blog, some of the clearest opportunities recently identified in the area revolve around reducing costs in several key areas:

High-cost patients - Did you realize that just 5 percent of patients account for roughly half of all US healthcare costs? By targeting these high-cost patients, big data has the possibility to make a tremendous influence on total healthcare spending within the usa. This is the best example of the Pareto principle at the job.

Readmissions - With nearly one-third of readmissions deemed to be preventable, using big data to predict which patients are at a high risk of readmission could lead to better interventions and reduced re-admissions.

Triage - Big data could also be used to enhance the triage process by applying algorithms to send patients to the correct unit for care and ensuring that everybody associated with providing that care is promptly informed throughout the process.

Decompensation - Decompensation refers to a patient's worsening health condition. Patient monitoring tools such as pulse rate and blood pressure monitors are used to measure a patient's current condition. Using big data, researchers may be better able to determine the risk of decompensation, allowing healthcare providers to intervene prior to the patient's condition worsens.

Adverse events - No one wishes to experience an adverse health event for example infection, a drug reaction, great researcher or renal failure. These events often contribute to death, yet are often preventable. Big data could make huge gains in both preventing adverse events and slashing their associated costs.

Diseases affecting multiple organ systems - Systemic diseases that affect multiple organ systems are among the costliest to treat and manage. Using big data, medical researchers may be better able to predict the likely progression of a disease which, consequently, would help healthcare providers develop a more effective, as well as more cost-effective, treatment solution.

While these areas all represent significant opportunities for medical researchers as well as the health care sector at large, how can researchers possibly make sense of all that data? According to Dolphin, "Big Data relates to the very fact that today's business intelligence systems are experiencing record levels of data growth from terabytes to petabytes and beyond. The challenge is in maximizing the opportunity for real-time business intelligence while minimizing the impact of exploding data volume on productivity and total cost of ownership (TCO)."

This is done through the utilization of business intelligence and data archiving software. With the correct tools in hand, medical researchers possess the ability to make experience of the sheer volumes of healthcare data from the past, present, and future.