Analytics are expensive and labor intensive; we need them to be routine and ubiquitous. I complained earlier this year that analytics are hard for health care providers to muster because there’s a shortage of analysts and because every data-driven decision takes huge expertise.
Currently, only major health care institutions such as Geisinger, the Mayo Clinic, and Kaiser Permanente incorporate analytics into day-to-day decisions. Research facilities employ analytics teams for clinical research, but perhaps not so much for day-to-day operations. Large health care providers can afford departments of analysts, but most facilities — including those forming accountable care organizations — cannot.
So, a hospital system that has put together a data analytics package that not only works for itself for day-to-day operations – for example, helping doctors determine if a patient is likely to be readmitted and knowing what to do to help – but is working to get other systems to use it.
It works no matter what the electronic health records software a hospital uses, analyzes data in ways different institutions need.
Will be interesting to see how this plays out. I’ve had a lot of interactions with a healthcare system that has moved to electronic records in a big way. And the speed of making decisions because the data are available has been amazing.
Things that might take a week and a couple of different visits can be done right there. Instead of hours spent trying to schedule an diagnostic procedure that needed to be done after hours, the office made the appointment at another facility within minutes.
Heck, I called my insurance company with a question. I was talking with a human being within 30 seconds who had answered my question within a minute and actually went on to check out some other things that they came up with themselves, just to check.
I do not expect things to be perfect but I can see glimpses of how much better the system can be.