Hi all,
I have been in radiology IT for 25 years and measuring productivity has been something I have put in a place a couple of times. I am the CIO of Wake Radiology and we are using Clario, a unified worklist to do this, but I doubt you want to put in a worklist just to get an RVU gauge. I know that Primordial had the ability to do this and since it was very modular you might want to talk to Nuance and see if they have a module you could use. Quantum imaging built a product calledPACE that might work for you. They sell it under the Q-IT brand https://q-itsolutions.com/. It is based off the GE worklist, but in my talks with them it might be adapted to work off other things. RadAI recently acquired a company Equium Intelligence https://www.equium.io/ that is really meant for efficient scheduling of radiologists, but one of the ways it does it is to figure out the complexity of cases and estimate time taken to read. They might have a widget that would tell you estimated and actual rvu.
I am currently working on a doctorate in healthcare administration, and I plan on doing my dissertation around this topic. According to some papers non countable time (non RVU time) can account for more than 32% of the time in private practice and almost 52% in academic practice.(Brady, 2011) Another study said only 37% of a radiologists time was spent actually looking at images.(Dhanoa et al., 2013)
An application was developed at MCSU to capture non RVU tasks(Kovacs et al., 2018), and Clario also has this ability.
What I am hoping to do is build an algorithm that is better than RVUs, that could be used by the industry. RVUs don't take into account complexity of cases such as if an exam is an ER exam which is most often negative or a cancer case where there are lots of measurements to be done on the case, or just comorbidities in general. In Australia they have started to do research on using study ascribable time instead of RVUs.(Pitman et al., 2018) If you are interested in this and would like to help please let me know.
Thanks,
Matt
Brady, A. P. (2011). Measuring radiologist workload: how to do it, and why it matters. Eur Radiol, 21(11), 2315-2317. https://doi.org/10.1007/s00330-011-2195-2
Dhanoa, D. B. M. D. M. B. A., Dhesi, T. S. B., Burton, K. R. M. M. B. A. M. D., Nicolaou, S. M. D., & Liang, T. B. (2013). The Evolving Role of the Radiologist: The Vancouver Workload Utilization Evaluation Study. Journal of the American College of Radiology, 10(10), 764-769. https://doi.org/10.1016/j.jacr.2013.04.001
Kovacs, M. D., Sheafor, D. H., Thacker, P. G., Hardie, A. D., & Costello, P. (2018). Metrix Matrix: A Cloud-Based System for Tracking Non-Relative Value Unit Value-Added Work Metrics. J Am Coll Radiol, 15(3 Pt A), 415-421. https://doi.org/10.1016/j.jacr.2017.10.028
Pitman, A., Cowan, I. A., Floyd, R. A., & Munro, P. L. (2018). Measuring radiologist workload: Progressing from RVUs to study ascribable times. J Med Imaging Radiat Oncol, 62(5), 605-618. https://doi.org/10.1111/1754-9485.12778