Big Data in Medicine and Life Style

David Duvall and Manish Barral

Big Data: Big Boon and Big Brother

Prof. Dr. Adalbert F.X. Wilhelm


Business intelligence software will analyze datasets to prevent adverse medical events by looking for patterns and trends. Medical professionals, hospitals and related healthcare center are working to reduce cost, provide excellent patient care, standardize healthcare quality and deliver effective patient outcomes.Health  data is becoming more complex. In 2012, worldwide digital healthcare data was estimated to be equal to 500 petabytes and is expected to reach 25,000 petabytes in 2020. There are several reasons for growing complexity of healthcare data like more incentives given to professionals/hospitals that use EHR( Electronic Health Records) technology, development of new technologies such as capturing devices, sensors, mobile applications, etc ; collection of genomic information, increasing patient social communication in digital forms, more medical knowledges and discoveries, etc. The different approaches of healthcare continuum like bio informatics, imaging informatics, public health informatics, DNA sequencing service, etc which are comprised of different methodologies in medical field. So, data in healthcare sector in increasing day by day. There are numerous big data challenges in healthcare like inferring knowledge from from complex heterogeneous patient sources, understanding unstructured clinical notes in the right context ,efficiently handling large volumes of medical imaging data, and extracting potentially useful information and biomarkers, analysing genomic data in computationally intensive task, capturing the patients behavioural data through different sensors, etc. These challenges should be eliminated. The overall goals of Big data Analytics in healthcare is to provide right personalized healthcare to the patient in right time with the use of massive data; and also potentially benefit all the components of the healthcare system i.e. provider, payer, patient and management. Different steps have been taken improve health sector with the help of health data. The US president unveiled a bold $100 million research  initiative designed to revolutionize our understanding of human brain (BRAIN Initiative), GE Head Health Challenge, penalties for poor care, identification of patients who will be admitted to hospital next year using data and helping to reduce the hospitalizations, etc are some examples of such steps taken in health sector using big data resource. Mainly there are three kinds of health data; i.e, Genomic data, Clinical data and Behaviour data.  Effective integrating and efficiently analysing such various forms of healthcare data over a period of time can answer many healthcare problems and helps to diagnose diseases properly. A sample EHR data consists of the standard elements like ICD codes( International classification of diseases), CTP codes( Current procedural terminology), Lab results by LOINC, medication of NDC( National Drug Code) and Clinical notes. Such various forms of data helps the healthcare sector. The combination of data and knowledge helps.
Home monitoring and sensing have become more prevalent over the past decade. Sensing technology allows for several types of data to be monitored in real time. This technology is useful for home monitoring and activity recognition on your cell phone, for example. Big data has become significant to the healthcare sector as it allows for large records to be kept which in previous decades would not have been possible. This is evident by the number of data repositories used by government agencies and organizations. It is becoming evident that a paradigm shift is taking place in which everything is becoming digital. It is predicted that by 2019 there will be approximately 5.5 billion users of mobile and wearable biometric technology. This is another example of how sensors are becoming a fundamental technology to health care. As more research and development is done, more advanced technologies will lead to a more seamless and integrated use of big data in health care. Big data in health care is primarily used for monitoring and tracking purposes this could include monitoring blood pressure, glucose levels, and tracking medications. Big data will continue to play an important role in the healthcare industry and has the potential to save the sector up to $450 billion. This will only be achievable if stakeholders steer the industry towards a patient-centered approach to value. Big data analytics are only in their infancy for the healthcare sector so it will likely only continue to become more significant for the industry as there will be an increasing demand for further big data analytics.


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“Big Data in Healthcare Made Simple.” Health Catalyst Where It Stands Today and Where Its Going Comments. N.p., 12 July 2016. Web. 10 Oct. 2016.

“Doctors and Hospitals’ Use of Health IT More than Doubles since 2012.” United States Department of Health & Human Services, 22 May 2013. Web. 10 Oct. 2016.

“GE Healthcare Taps SAS For Patient Safety Analytics – InformationWeek.” Information Week. N.p., n.d. Web. 10 Oct. 2016.

“Overview.” Electronic Health Records (EHR) Incentive Programs. N.p., n.d. Web. 10 Oct. 2016.

“Why Health Care May Finally Be Ready for Big Data.” Harvard Business Review. Harvard Business Publishing, 24 Nov. 2015. Web. 10 Oct. 2016.



2 thoughts on “Big Data in Medicine and Life Style

  1. An interesting development is also the emergence of private research institutions with the same scope of advancing medical knowledge, such as the Chan Zuckerberg initiative:
    Given their tech background it’ll be interesting to see whether or how their institution will harness big data.


  2. The traditional approach to treating illnesses and medical conditions starts by building profiles of each disease, based on the respective symptoms, laboratory tests, results of physical examinations, among other types of medical information.

    However, this method has gradually been proven to oversimplify medical treatment to such extent that it can result in mistakes with terrible implications on patients’ health. Factors such as the gender, age, nutrition patterns, daily routines, living environment and genetic makeup of an individual add to the complexity of diagnosing diseases, which is why an “one-size fits all” style of providing medical treatment simply does not work.

    Big data has the potential of transforming the healthcare system by changing the focus from a disease/condition profile, to individual-specific profiles. This way, doctors can construct highly accurate predictive models around each patient, in order to improve diagnosis and medical attention.

    To read more about this new phenomenon denominated “personalized” or “precision” medicine, go to:

    And for to get an insight on the debate between supporters and opponents of this medical trend, check out:


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