To continue from from the introductory post Big Data – Introduction (this link will open in a new tab of your current browser window) and Big Data – Big Data Basics (this link will open in a new tab of your current browser window), this first part will introduce the subject of big data in healthcare and end there.
As you would surely be aware even as a Health Information Management (HIM) / Medical Records (MR) practitioner from your practice of managing medical records that an individual patient’s clinical signs and symptoms, medical and family history, and data from laboratory and imaging evaluation found in his or her medical record is used by the attending doctor to diagnose and then treat the patient’s illnesses. This traditional clinical diagnosis and management approach to treatment has been and still is often a reactive approach, i.e., the doctor starts treatment/medication after the signs and symptoms appear.
However given the genetic variability between individuals and advances in medical genetics and human genetics eversince the Human genome project completed in 2003, medical genetics and human genetics have since provided both scientists and clinicians to understand health and manage disease, that is to say that it has been providing a more detailed understanding of the roles of genes in normal human development and physiology and the risk for many common diseases, not in the same way diseases have been understood in the traditional reactive approach.
Standard test data – of an individual patient’s clinical signs and symptoms, medical and family history, patient discharges, real-time clinical transactions and data from laboratory and imaging evaluation found in his or her medical record, and data in personalised medicine or PM when medical decisions, practices, and/or products are tailored or customised to the individual patient with the use of genetic information (genomic data) – from the study of biological data of the complete set of DNA within a single cell of an organism of the individual, or a combination of the two, creates vast collections of data – Healthcare Big Data..
Healthcare Big Data has tremendous potential to add value from analysing and mining these vast collections of data now available to hospitals in general.
But Healthcare Big Data must be managed, leveraged and integrated to help personalise care (as in PM), engage patients, reduce variability and costs, and ultimately improve quality.
In order to manage, leverage and integrate Healthcare Big Data, Big Data solutions are needed to transform health care with big data. Big Data solutions apply analytics to examine, better analyse and understand the large amounts of data of unstructured clinical data in the form of images, scanned documents, and encounter or progress notes in its native state, integrate it with operational structured data based on historical and current trends, to uncover whatever hidden patterns, unknown correlations and other useful information, and then they help predict what might occur in the future with a trusted level of greater reliability. Healthcare Big Data analytics is all useful information because such information can provide competitive advantages over rival hospital organisations and result in business benefits, for example more effective marketing and thus generate increased revenue.
In the next post on Healthcare Big Data, I shall be blogging about the challenges in aggregating the Healthcare Big Data from multiple sources.
References:
- Denise, A 2013, Leveraging big data analytics to improve healthcare delivery, ZDNet, viewed 30 March 2013, < http://www.zdnet.com/leveraging-big-data-analytics-to-improve-healthcare-delivery-7000013072/ >
- Geoffrey, SG and Huntington, FW (eds.) 2010, Essentials of Genomic and Personalized Medicine, Academic Press, Elsevier Inc, San Diego, CA, USA
- Lorraine, F, Michele, O’C, & Victoria, W 2012, Data, Bigger Outcomes, American Health Information Management Association, viewed 18 November 2012, < http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049741.hcsp?dDocName=bok1_049741 >
- Margaret, R, 2012, DEFINITION big data analytics, TechTarget, viewed 1 April 2013, < http://searchbusinessanalytics.techtarget.com/definition/big-data-analytics >
- Neil, V 2013, Big Data Use In Healthcare Needs Governance, Education, InformationWeek, viewed 30 March 2013, < http://www.informationweek.com/healthcare/clinical-systems/big-data-use-in-healthcare-needs-governa/240151395 >