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Big data is defined as large volumes of high velocity, complex, and variable data that requires advanced technology to capture, store, distribute, manage and analyze the information.  Big data is a relatively new concept in healthcare and it’s being used in many ways to interpret data in hopes of improving health outcomes and reducing healthcare costs.  This rapid digitization of massive amounts of data is being driven by mandatory regulations in the hopes of improving clinical decision making, disease surveillance and population management.  Big data comes from many types of information including:
·      Clinical data

·      Activity and cost data

·      Pharmaceutical research data

·      Patient behavior data

In the future, data will no longer be gathered from individuals and applied to the population, but vast amounts of population data will be used to predict what happens to an individual.

 

·  The term “Big Data” has been around for nearly 20 years. Originally meant a lot of data but has evolved to mean more. The term now refers to data management and analysis of large and complex data sets, integrating and mining internal and external data and using tools to analyze and view these data.

·  The term “Big Data” now has many different working definitions that can be useful for many different fields. In relation to nursing, one of those definitions is “large amounts of patient data that can give us insights about the patient experience.” It has also been called a “tsunami of data” and “Extremely large data volumes at high velocities.”

·  Originally started being used by the banking and retail industry but healthcare is one of the latest areas to catch on with respect to leveraging the concepts and tools of big data.

·   Can be traced back to the Human Genome Project in 1990’s as the launch of Big Data in healthcare.

·   Now being used by pharmaceutical industry, providers, insurance companies and more to analyze the data in order to address problems with healthcare, quality and spending and to determine which treatments and drugs are the most beneficial. The aims are to slow increasing costs, guide providers with practicing more effective medicine, empower patients and caregivers, support fitness and preventive self-care, and to create more personalized medicine.

·   The data that is now being used in healthcare includes things like health records, clinical trial data, risk analysis data, genomics, device readings and population and disease tracking.

·   In the healthcare field, in particular nursing, Big Data is being used to make discoveries that enhance nursing care.  Big Data is being used to advance nursing science that will drive the delivery of patient care.

 Increasing number of companies using Big Data in healthcare:                                              * Genome Health Solutions - personalized genomic medicine                                    * GNS Healthcare – outcomes management                                                                * DNAnexus - data management and analysis                                                              * Appistry Inc. - easy-to-read reports that can be used by doctors,                              patients, pathologists and hospitals 

              * NextBio – mines data focusing on focus on oncology and             
                  metabolic and autoimmune diseases. 

              * Health Fidelity – changes narrative medical records) into structured 
                 data that can be used for computer management, to address needs   
                in revenue cycle management, compliance, and analytics

    
Increasing number of companies that support patients and self-care

                  * Humetrix’s iBlueButton – pools data and provides device-to-device                         communication and data exchange at the point of care between 
                     patients and providers

                  * Ginger.io - collecting real-time passive and active behavioral data 
                     from patients’ cell phones focusing on mental health conditions

                  * Welldoc - automated, real-time coaching using behavioral and 
                     clinical messaging, as one element of its FDA Class II medical 
                     device platform, helps patients manage chronic diseases, such as 
                     diabetes

·  With the use of Big Data, issues have emerged that may challenge the successful use of healthcare Big Data, including privacy and security, who owns the data, regulations over the use of Big Data and many others.

Large data sets can be useful in the research community because it can guide the questions we are seeking answers to. What do we want to know from big data? We need to be asking questions to link the data to the questions we are after. Data is meaningless unless we interpret the data. We connect data together not only to make sense of it but to also generate answers to help solve problems. Data is derived for a purpose and it is our professional knowledge and judgment that helps to create the questions that leads to answers from data sets.

We can apply big data to help us educate our patients on their risks and promote individualized behavior change that can help promote better outcomes. For example, we have data that tells us who is more at risk for developing breast cancer, hepatitis, and many other diseases. Looking at trends and data we have learned that antibiotic resistance is a big problem right now and it is shaping the way we mange infections.

Meaningful data and meaningful use is data that has a meaning to humans and data that is happening in real time. Why is this important? It helps us look at what’s happening to look at trends and patterns and gives us the opportunity to prevent and intervene. Using standard terms in nursing and being mindful of how we label our information so our data can be useful to others, is one way we can help bring meaningful data. One of the biggest projects taking place that utilizes big data is the human genome project. Looking at the make up of humans is giving large insight to the health of the individual and risk for illnesses and disease.  Knowing this data can help guide proper treatments and prevention.