Do you really know your data?
Updated: Oct 29, 2020
Data science plays a major role in helping piece together data sets such that one has actionable metrics to work with. Much of this involves using algorithms, science and technology to present this back to the stakeholder in a meaningful way for analysis. So, how does this apply to Behavioral Health? It's all about the data - your Electronic Medical Record or Care Coordination System is a treasure trove of data waiting to be turned into information. Pull in outcomes data or financials and now you need to tie these disparate data sets together in a meaningful way. Dashboards are the favorite vehicle used these days to understand KPI's (key performance indicators) and the resulting changes that are made leading to process improvement.
Back to Data Science - "Can you trust your data?"
Once properly scoped, every engagement begins by reviewing your data. Organizational hierarchies, service codes, billing, amount paid, hours worked, etc. all matter. Further complicating things (before one can get to the science) is the fact that there are dozens of electronic medical records - each using a different approach to the capture and storing data. Making sure this can be pulled into a well refined and data model in a consistent way is key to any successful analytics - dashboard project. One can not underestimate the experience needed to work at the data level; all of which must be rock solid long before one overlays the Business Intelligence platform.
This KPI can't be right!
We hear this all the time which is why the data science is so important. Sure, data validation is important but, it goes way beyond that. Missing records, duplicate billing, different client id's for the same client are all part of understanding how to piece together meaningful KPI's that are well aligned to the business. Including the necessary drill-downs, hierarchies, slicers, filters and finally the visualization all make for a useful platform for analysis. To the end user, it may seem more like magic than data science. We know differently. Experience matters.
Call Doug Philipon at 603-893- 3922 x703 or email email@example.com today to hear more.