What is “Big Data”? There are many definitions. Here are three of them:
- “Big Data is an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information.”
- “Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”
- “A new attitude by businesses, non-profits, government agencies, and individuals that combining data from multiple sources can lead to better decisions.”
In the next few years organizations will begin to tap into the enormous amount of real-time and historical data available and use that information to make decisions about and improve their business. These same concepts apply to healthcare training.
“There is a big data revolution,” says Weatherhead University Professor Gary King. But it is not the quantity of data that is revolutionary. “The big data revolution is that now we can do something with the data.”
BIG TRAINING DATA
For some applications, Big Data means bringing together enormous sets of disparate data to attempt to find trends and patterns using huge computational power.
Healthcare training initiatives produce large amounts of data. The challenge with healthcare training data is not storing and accessing that data or applying abnormally powerful computational engines. The challenge is presenting the data in a manner that a facility can derive real benefit from their understanding of that data.
Access to large sets of training data combined with industry standard data and demographic and wage information will inform organizational decisions about the effectiveness of the training being delivered and also about ways to achieve new cost efficiencies.
The “secret sauce” is visualizations that allow administrators to comprehend large data sets using clear, easy to understand graphing and images. Good visualizations of the right data can quickly uncover comparisons, trends, outcomes and patterns that are not readily available by looking at the raw data by itself. They say that “a picture is worth a thousand words.” With Big Data, “a good visualization is worth a thousand decisions.”
What types of data can be used to enhance training decisions? Examples of useful training data include test scores, course completions, assignments, time spent in course, # of courses assigned, type of course, cost of staff time, national standards etc. Combining this data and displaying it in visualizations can yield surprisingly interesting and ACTIONABLE information. Most importantly, proper use of the data can get at the core metrics desired for most training initiatives – effectiveness and cost.
ANSWERING THE TOUGH QUESTIONS
Just some of the questions that could be answered with this type of data and the right visualizations are:
- How well-trained is our staff?
- How do we compare to national standards
- Are our training initiatives effective?
- Is knowledge increasing over time?
- Are scores increasing over time?
- What is our progress in delivering the training?
- What is the cost of staff time to access this training?
- Should we eliminate or redirect some of our training initiatives?
- How can we maximize training resources and dollars?
For the vast majority of training programs today, the full answers to these questions are inaccessible. Without Big Data and the visualizations possible from that data, the answers will remain elusive. Big Data can shed light on information that was previously hidden from view.
If Big Data can deliver an understanding of the quality and costs associated with training initiatives, it can provide huge value for healthcare organizations.
Stay tuned for more about Big Data for healthcare training in the coming months!