Improving medical diagnosis, testing with big data

The healthcare industry is rife with patient information that could be leveraged with big data tools to provide more focused treatment and reduce operational expenses for medical facilities. The increased adoption rate of electronic health record systems has given more healthcare organizations the datasets needed to glean meaningful insights about their operations. According to a report issued by the Office of the National Coordinator for Health Information Technology, the number of acute-care hospitals using EHR systems tripled between 2019 and 2012, rising to 44 percent. Although hospital officials have only just begun to scratch the surface of the potential presented by Hadoop big data, many facilities have launched analytics programs that showcase the benefits of the technology.

Providing more accurate diagnoses recently outlined several aspects of the healthcare industry that could be immensely improved with big data tools. For instance, data analytics could help mitigate the risk resulting from "cookbook medicine" diagnosis methods. A popular but often maligned practice, cookbook medicine is the process of physicians adhering to strict guidelines when making diagnoses. Patients exhibiting certain symptoms are quickly given a predetermined treatment course without considering the circumstances that might be unique to their condition. Many doctors use this technique when emergency rooms become flooded with patients and they need to quickly provide treatment. However, they run the risk of missing vital clues that could suggest a different course of action should be taken. Statistically, cookbook medicine may work, but there are risks for patient safety.

Physicians can increase the scope of their diagnosis using big data tools. Evidence-based analytics software can process medical records regarding patients exhibiting similar symptoms, lifestyle choices and demographics to provide a more accurate diagnosis. This could improve treatment efforts as well as reduce the costs of conducting unnecessary tests.

An alternative to traditional clinical testing
Data analytics software can also be used to reduce the amount of time and resources needed to conduct critical research. Normal clinical trials can be extremely expensive and take years to conduct. However, researchers can deploy big data software using existing datasets to glean insights quicker and with fewer resources. For instance, the Department of Veterans Affairs launched the Million Veteran Program that researchers use to analyze health information provided by more than 150,000 veterans to determine how genes affect patient health.

As data analytics software becomes more sophisticated and widely adopted, medical researchers and physicians will discover new uses for the technology. Even in its relative infancy, Hadoop big data solutions have been immensely valuable to hospital officials looking to reduce costs and improve patient treatment.

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