One of the most exciting parts of any project is the point when the period of anoesis ends and members of the project team drift back to reality, back to a period of having to come to terms with what they have wrought. That is the point at which you know things will feel better once they stop hurting.
For those inclined to argue that the project was a success because of the number of people who use it, may we visit that notion a little before we buy in all the way? Arguing that use is the same as acceptance is a little like arguing the same about our use of gravity—after all, it is not as though we have much of a choice as to whether we are going to use gravity. Maybe we should allow users to rename user acceptance to grim resignation.
User Acceptance may be a good thing, and it may be better than no user acceptance. Therefore, User Acceptance is a necessary but not sufficient condition of how well you spent the millions.
What could possibly be wrong with having one hundred percent of the user community using the application? Well, if users have no choice, or if penalties are involved with not using the application, merely using the application does not tell you if the application is any good, it simply tells you it is being used.
Electronic Health Records (EHR) systems are deployed in many hospitals. In some hospitals, user acceptance is quite high. In many of those hospitals productivity has dropped, and this productivity drop is being traced directly to using the EHR. Written in a different way, and with other factors remaining constant, doctors were able to see more patients prior to the implementation of the EHR. The EHR, more specifically how they use the EHR, has resulted in them being able to see fewer patients.
Many physicians in large service provider environments are reporting that they are only able to see about eighty percent of the number of patients they had been able to see. Now one school of thought would have you believe that seeing twenty percent less patients is not a problem because sooner or later all of the patients are seen. This argument does not work.
Let us look at an example of a hundred and forty physician orthopedic practice that before implementing EHR its doctors were seeing four patients an hour over a ten hour day. So as to not scare anyone, let us also assume that on any given day only half of the doctors were scheduled to see patients. Since what we are looking at is the productivity delta of pre and post EHR, we are assuming that all other factors are similar. Before EHR the group saw twenty-eight-hundred patients a day; after EHR they only saw twenty-two-hundred and forty patients.
In this example we see a net loss of five-hundred and sixty patient visits each day. Seeing those patients tomorrow does not solve the problem. The problem is that real revenue was lost today, and will be lost again tomorrow and the next day and so forth and so on.
In this example we can put an exact figure on the amount of revenue lost due to an unproductive yet fully user accepted EHR system. This example also shows that this service provider cannot hope to grow because it cannot even manage its current patient load. To get back to its old revenues, the provider would have to hire twenty-five percent more doctors.
So, does it make any sense to not deal with the distinction between user acceptance and productivity? Why would a provider accept having to go from one-hundred-forty physicians to one-hundred-seventy-five physicians just to see the same number of patients? In theory, they would have to increase the number of physicians by twenty-five percent to attain pre-EHR revenues. Even if they added thirty-five physicians, although revenues would recover, costs would go way up, and margins would take a pounding.
What exactly does a twenty percent productivity drop look like? I think some people only think of it in terms of inefficiencies and ineffectiveness and forget that it has real dollars attached to it. Let us calculate the cost to our orthopedic practice. Just in round numbers, forgetting labs and scripts and therapy, five hundred and sixty visits a day multiplied by two-hundred and fifty days a year equals one-hundred and forty thousand missed patient visits a year. Just to keep the math simple, if the average missed visit results in a revenue loss of one hundred dollars, the loss to the business is about fourteen and a half million dollars.
Maybe that is enough incentive to come up with a name for the project whose purpose is to offset the EHR productivity loss. The good news is you can recapture the lost productivity but you will need to look outside of IT and your EHR vendor to do it.