AnalyticsMD (YC W15) Applies AI to Optimize the ER(techcrunch.com)
techcrunch.com
AnalyticsMD (YC W15) Applies AI to Optimize the ER
http://techcrunch.com/2015/01/28/analyticsmd/
7 comments
Good question. ER doctors hate when software gets in the way of their clinical decision making. We deliver recommendations to the front line managers but they decide what to act upon. One of the most frustrating things for the doctors often is when they are waiting to treat the patients but can't because there are no beds, or not enough staff or labs are not coming back. Our software anticipates those problems and recommends taking out those bottlenecks in advance.
Our hope is that we will make the day of the staff in the ER much less stressful and allow them to focus on spending more time with the patients.
Our hope is that we will make the day of the staff in the ER much less stressful and allow them to focus on spending more time with the patients.
How has this performed in the real world? Has it been tried in high traffic areas? (i.e. chicago/nyc)
Great question. Generally our system performs better in higher volume areas given the higher "n" in the data but we don't have a live deployment in a high traffic community ER yet. Hopefully we will have a more conclusive answer for you soon!
Does it get reinforced for doing an obviously bad or good job?
Yes. Our data feeds include the outcome variables we are optimizing for which helps the algorithms retrain as new patterns emerge.
Can you tell more about DecisionOS?
Is this something you've built inhouse or is it based on MLLib etc?
Is there any lash back from integrating with Epic within the Hospitals?
What is your tech stack?
What do you expect that this tool will do for the working environment of ER doctors and nurses? Or the relationship between them and their patients?