Jellybeans. Conversations with Care. The Jellybeans started here and are now also hosted on lifeinthefastlane.com (The Original) & www.IntensiveCareNetwork.com This is the complete collection. Sometimes containing more controversial offerings.
Big data. It’s very big. There’s a lot of it. It’s Jellybean time. Matt McPartlin strikes gold in Wollongong.
Moment to moment information on heart rate, respiratory rate, how much urine has come out, how much fluid has gone in, the sodium, the glucose, the pH and what was had for breakfast. And that’s just one hour, from one patient in one of sixteen beds, in one ICU, in one hospital, in one city, from one state.
That’s a lot of data. It takes machines and algorithm to process. Intelligence of the artificial type. Automated processing.
So who manages the machines? Who decides what patterns to watch for? What can be learned from it.
Big data is a term that has become increasingly tossed around at research meetings and medical conferences. The multi-centre RCT is under attack. It’s expensive, restrictive and only ever seems to beget more RCTs. Is Big Data here to replace RCTs or to refine it?
Big data may be more reflective of real world practice and variance. Like a mega-collection of annecdotal evidence – a Megadote, or maybe a Metadote.
Nik Kumar is an ICU registrar who trundled along to the ANZICS Datathon in April to see what all the fuss was about and whether he could use it for some of the projects he had in mind. He went with few expectations. He came back with a whole new perspective on not just data collection and analysis but on collaborative research and future directions for determining trends in practice. He also likes pizza.
Big thanks to Matt for recording another Jellybean. Thanks to Dr Nik Kumar for explaining some high end health focused data science. It is not a main stream thing. (Yet.) It is one of those interesting things that hang around at the edges of our working lives.
Here at the Jellybean podcast, we love the fringes. We love to learn a little more about the stuff that isn’t in the books, that’s not on any syllabus but is relevant. It might seem small but as we should all know; from little things big things grow.
Thanks to Big Data for making the music. We couldn’t resist using one of their tunes. The intro and outro music is from Big Data’s track Dangerous
You can find that here; https://itunes.apple.com/us/artist/big-data/614730110
You kind find more info on this big Big Data thing here;
ANZICS Datathon – http://datathon.anzics.com.au/
“SIH research engineer wins ANZICS Datathon” – https://informatics.sydney.edu.au/news/anzics/
Big data analysis – The Basics
– Data Science vs. Big Data vs. Data Analytics – https://au.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article (A non-medical overview)
– Medical big data: promise and challenges. Choong Ho Lee and Hyung-Jin Yoon. Kidney Res Clin Pract. 2017 Mar; 36(1): 3ñ11. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5331970/ (Full text)
– Big Data And New Knowledge In Medicine: The Thinking, Training, And Tools Needed For A Learning Health System. Harlan M. Krumholz. PMID: 25006142. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5459394/ (Full text)
Machine learning – The Basics
– What is Machine Learning? Andrew Ng. Coursera. https://www.coursera.org/lecture/machine-learning/what-is-machine-learning-Ujm7v
– Machine Learning in Medicine. Rahul C. Deo. Circulation. 2015 Nov 17; 132(20): 1920ñ1930. Circulation. 2015 Nov 17; 132(20): 1920ñ1930. (Full text)
Udacity – https://www.udacity.com/