@CICMANZ Psychological saftey is so important that’s why receiving text messages like the below for reporting clinical incidents is behaviour that really should not be tolerated.
As we start using these data sets for machine learning projects we need to be aware of the inherent biases they contain. Is it time to monitor all patients with waveform level data?
When is human physiology not distributed as one might expect…..? when it’s stored in an electronic patient record! Excellent work by @OliverKleinig showing even number bias, and boundary effects associated with the ‘normal values’. https://t.co/TtmI2naMK9
@Uber_Support Incidentally, I can’t actually respond to your ‘specialist team’ as you say I am not responding from the same email address (@googlemail.com is the same as @gmail.com!!)
@UberEats does taking 40 minutes to collect and deliver pizza, so when it arrives it’s cold and like cardboard really the ‘premium’ service. To be refunded $1.51 (after the premium surcharge) is slightly insulting. (I was 7 mins from the restaurant!)
@DrTobyGilbert This would just be logistic regression..... an EMR will tell us which nurses/doctors/allied health interact with patients we can the look at an individual’s association with poor feedback. You will quickly find your problems and your stars!!!
@DrTobyGilbert I sincerely believe that patient experience can be hugely derailed by one clinician with well intentioned but poorly delivered communication.... I think we can detect this ahead of time and fix it!