Improving healthcare with Hadoop big data
Having access to information that epitomizes the three Vs of big data – volume, velocity and variety – is critical to bettering efficiency and reliability in the healthcare system. Singular doctor-to-patient interactions benefit from having a clear, organized and comprehensive picture of the patient's medical history, while large-scale medical breakthroughs rely on having an exhaustive picture of salient information, germane cases and prior developments. Medical professionals can ill afford to concentrate significant resources and instruction time on the improvement of data collection and usage, so they require an ad hoc, simple solution: Apache Hadoop.
The lack of successful big data analysis strategies means that the healthcare sector is merely scratching the surface of the certain benefits of information, according to PhysBizTech contributor Jeff Rowe. He identified three key areas of potential growth through data analytics: improving the patient experience, finding and fixing inconsistencies in data-driven integration and providing conclusive evidence for medical care best practices. Hadoop architecture can consolidate what could otherwise be an insurmountable pile of big data into useful relevant clusters with minimal effort on the part of users.
Healthcare will become more personalized in the future with the help of big data insights, according to InformationWeek, as doctors can leverage smart, crisp data insights into better patient interactions. In turn, people can become more attuned to their personal medical history and diagnostic care, an important aspect of improving attention to one's health outside the doctor's office. Hadoop big data programs can leverage electronic health records, from which medical professionals can derive more dynamic, sophisticated insights into a patient's condition. EHRs integrate data concerning genetic and molecular profiles, which doctors can use to better diagnose medical issues and watch for conditions for which a patient has increased risk.