In the 1988 movie Big, a young boy gets his wish and grows up overnight. In today’s world, the exponential growth of technology, power of computers, and availability of data has happened so quickly that it sometimes seems as though we’ve awakened after a long dream, much like Tom Hanks in the film. In fact, the enormity of data stored around the world is now so large it’s referred to as…wait for it…’big’ data. The actual definition of big data is, “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”
In healthcare, it’s the patterns, trends and associations that get many of us excited, especially when we have the ability to look at large volumes of data; and the more we examine, the more significant it becomes. One good example centers around the steps taken to treat a specific illness in the hospital. After a diagnosis is made, doctors perform step 1, which may be to order a lab test or radiographic procedure. This is logically followed by step 2, then step 3, and so on – do you see where I’m going here? If we collect and examine all of these steps for all of the doctors treating a group of patients, and then relate the doctor’s decisions to the outcomes of the patients – voila – best practices emerge!
Many hospitals and health systems are currently developing or implementing clinical pathways and algorithms designed to establish and follow best practices. And while this can certainly be done without big data, the ability to evaluate massive amounts of orders and critical outcomes, in real-time, will result in a better understanding of both the disease processes and the treatment protocols. And this is just a single example of the use for big data – the possibilities are endless.
Let’s look at another example that’s a little more 21st century sounding – genomics. What is genomics exactly? The simple definition is “the study of the complete genetic material, or genome, of an organism.” For the purpose of this discussion we’ll substitute in ‘human’ for ‘organism’. We’ve come a long way in the last 50 to 60 years in the understanding of the genome, due in no small part to technology and big data handling capacity. When the human genome was first sequenced, the total cost of that enormous feat was upwards of ten million dollars. Today, the cost to sequence a person’s entire genome is approaching the $1000 mark – and Zoltar had nothing to do with it!
The amount of data available from genomic testing, even at just the individual level, is staggering. Each person has tens of thousands of genes made up of millions of base pairs, resulting in about 100 gigabytes of data. That’s quite a few selfies and videos!
So why do we want all this data? Simple – it will allow us to personalize healthcare at every level, from diagnosis to treatment and even to disease prevention. Currently, when a doctor prescribes a medicine for a particular disorder, it’s the same dose for every adult. What we’re learning through genomics is that not everyone responds the same to every medication. Some people need lower doses, some higher, and some may not respond no matter the size of the dose. This personalization of medicine is the result of countless hours of research and development.
However, there are simpler ways of using big data to personalize the healthcare experience in the near term. If we look more generally at all the data that is ingested on a daily basis around physicians, patients, lab tests, and more, it is no surprise that we now have the ability to improve the processes involved in patient care. Increasingly even more common is the use of real-time data to engage providers and patients in new and more efficient ways for better outcomes and greater satisfaction for all involved. In this new age of consumerism, big data use will lead to opportunities for improvement that will change healthcare, literally overnight!
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