Using “Big Data” to find the “Binders of Women”
Ever since Governor Romney mentioned the existence of “Binders of Women” the search has been on to find them. This is a complex problem and a time sensitive problem. I’ve been following the issue closely because no one really knows how long women can survive in binders. The clock is ticking…
I am happy to report that our friends at www.floatingsheep.org, the geo-mapping website, have found someone who has the answer. Montse Compa, a Humboldt State University student has used “Big Data” to solve the problem. The graphic depiction to the right clearly shows where all the binders are and where all the women are in the U.S.. No where do we see binders and women together. Mystery solved! There are no women in binders!!
Now that we have that issue out of the way, let’s talk about “Big Data” in healthcare. According to the Cleveland Clinic “It is estimated that 2.5 quintillion bytes of data are created daily, so much that 90% of the data in the world has been created in the last two years. This is what’s called “Big Data”, and hospitals, medical centers, hospital systems…are awash in it.” And that includes workforce data. Think about the potential to answer critical quality and cost questions by combining workforce data and clinical data. Mining “Big Data” will bring to light the answers to issues of quality and cost that we so desperately need. The future is somewhere hidden in “Big Data”.
Here is one example of the power of “Big Data”. The Robert Wood Johnson Foundation funded research that has correlated nurse staffing to readmission rates in acute care settings. Interdisciplinary Nursing Quality Research Initiative (INQRI) team at Marquette University has found that hospitals with more registered nurses working on a unit and fewer R.N. overtime hours have lower rates of patient readmission and fewer post-discharge visits to the emergency department.
This is just the beginning. It is imperative that we begin to bring all the data together – clinical and workforce data – and let the answers emerge.
What do you know in your heart about workforce issues that impact clinical outcomes that just needs data to be substantiated?