Dataiku – the software developer behind the advanced analytics platform Data Science Studio (DSS) – uses their data science expertise to outline clear steps to build and run predictive applications that leverage data to answer specific needs and solve costly problems in healthcare.
The fact is that the healthcare industry has a data problem. There is an abundance of raw data and few really know what to do with it. From patient records to heart rate monitors, hospitals produce reams of raw data that, after an initial reference, is usually forgotten. The good news is that all of this data can be used to solve a multitude of common, day-to-day problems using advanced analytics.
In “Advanced Analytics for Efficient Healthcare,” Dataiku uses “appointment no shows” to illustrate how the healthcare industry could solve common and extremely costly problems by merging siloed data and building advanced analytics solutions from that data. The goal of the e-book is to walk readers through the process of building a data product – in this case a data-driven scheduler to pre-emptively reduce ‘no-shows’ – from raw data to deployment.
The truth of the matter is that the possibilities for predictive analytics in the healthcare industry are endless. By efficiently leveraging the vast amounts of data that healthcare institutions create every day:
• providers will be able to deliver better care while reducing costs,
• payers will be able to accurately monitor population clusters and predict their associated costs,
• and time consuming processes like cleaning, merging, and analyzing siloed data, optimizing staffing needs, measuring institutional quality, and physician profiling, will be automated.
Download Dataiku’s complimentary e-book “Advanced Analytics for Efficient Healthcare.”