20Q: Measuring Clinical Productivity—the Hunt for the Right Metric

9. It sounds like a great accomplishment. What do you mean by ‘major’ CPTs?

Well, there are a lot of codes that our clinics used that didn’t seem to make sense to include. For example, there are codes related to dispensing hearing aid accessories that we believed did not contribute to clinician time or effort. We found that there was a lot of inconsistency in how our hearing aid services were delivered vis-à-vis the billing codes selected for those services. Discussion with audiology leaders outside of our triad revealed that this was a broad problem. To illustrate, we have these codes available for hearing aid service: V5014: Repair/modification of a hearing aid, V5020: Conformity evaluation, and 92592: Hearing aid check. Not all clinics use all three of these codes. Some clinics bundle the three under V5014. Some clinics never bundle the codes. So, in this case, we had to throw up our hands. We are confident with our custom RVUs for diagnostic services and cochlear implant services (as there are so few codes), but we are not able to gauge the productivity of dispensing audiologists very well in a universal approach.

10. What was the next step?

Well, we thought we had done it. We decided to see how our clinics compared to each other now that we have created these custom RVUs. A reasonable starting point was to determine what was the total number of RVUs our clinics billed during a one month period. We contacted our billing departments to pull the CPT codes billed during that time period, and we multiplied the total times each code was billed by its respective custom RVU and added that up. And do you know what we found? We found that the centers that had more patients had greater productivity.

11. That doesn’t seem to be very enlightening. That’s all you had to show for all your effort?

Kind of. The thing to remember about productivity is that it is a ratio of the amount of work done over a period of time. Up to now, we had spent all of our effort working on only half of the ratio: the amount of work done. We had yet to look at the denominator, the measurement of time.

12. I thought you did. You specified one month’s worth of time, right?

We did, but within that month, there were different numbers of person-hours available in each clinic. If you compare a clinic with 10 providers against a clinic with 5 providers over a one-month period, their productivity will clearly look different. We needed to refine our metric to reflect the amount of time providers were in each clinic.

13. That seems pretty straightforward, right?

Well, like anything else here, there is more than one way to do it. One approach is to use the number of hours of full-time equivalents (FTEs) assigned in a clinic. In a clinic with 5 full-time staff, the time unit would be 200 hours per week (5 people working 40 hours). FTE assignment is a relatively stable value but does not always reflect the actual amount of available work. During weeks when employees are out due to illness or vacation, productivity will look poorer compared to weeks when the clinic is fully staffed. This, of course, makes sense for observing general clinical trends. But if you want to control for actual changes in staffing when looking at productivity, you could not use the FTE approach.

We found in the literature on productivity that labor can be measured using paid-hours or worked-hours. Simply put, paid-hours includes paid time off (essentially the clinic FTE), and worked hours does not include paid time off. 

14. If you are trying to compare individual productivity, then worked hours would be the better option, right? It would describe the provider’s availability most accurately.

Exactly right, and so worked hours was the value we wanted for the other half of our productivity ratio. But it is not a simple task to obtain the worked hours for a certain period of time for a multi-satellite medical center with 30 audiologists working across 6 clinical sites. Of our three medical centers, two were able to access a worked hours report from the payroll department; for the third center, this information was not accessible. 

Joy Peterson at CHOP brought to our attention that there are operational efficiency metrics used in healthcare called Paid Hours Per Unit of Service (PHPUOS) and Worked Hours Per Unit of Service, or WHPUOS. Joy liked to pronounce them as Puh-HOO-Poo-Oze and Wuh-HOO-Poo-Oze respectively, which of course Wendy Steuerwald at CCHMC and I liked to tease her about. But our efforts had essentially brought us to a place where we could calculate custom PHPUOS and WHPUOS for our clinics. We already had found the paid hours and worked hours, so that would now be our numerator instead of denominator in the ratio. We also needed to convert our procedure RVUs to hour equivalency; for example, tympanometry’s RVU changed from 1 (one 15-minute unit) to 0.25 (a quarter of a 1-hour unit). After making these updates, we were able to determine that, across our clinics, the average PHPUOS was 1.5, meaning for every hour’s worth of services billed, audiologists typically worked 90 minutes.

15. Did you finally find out what you wanted to know?

Pretty much. We found out that we were more or less in line with each other. We were also interested in how hospitals beyond ours compared, so we created an online survey that allows other clinics to calculate their productivity using PHPUOS based on our custom RVUs. This survey is still active at https://redcap.link/cometopapa if anyone would like to try it. It takes a fair amount of time to complete because it requires knowledge of the number of worked or paid hours spent in a clinic and the number of times each billing code was submitted during a set date range. For that reason, we did not get many respondents. But we did come up with a “PAPA Range” of expected productivity of between 1.2 and 1.5 PHPUOS. 

16. What are you using this information for now?

Currently, I am using it for monitoring. I set up some guidelines for how we set up schedule templates for providers to promote as much evenness of individual productivity as possible. I check the numbers monthly to make sure there aren’t any outliers. When there are, I check in with the audiologist’s manager to see if it’s something we need to address. 

Also I am expanding its use to evaluate productivity in our speech and language programs. I am at a different phase of productivity development, because we do not have custom RVUs for their CPT codes. So, I am using a volume-based adaptation of the WHPUOS: worked hours per patient.

17. I recall that earlier we talked about how staff might react negatively to the “measurement of productivity.” Did the clinic dynamics change when staff knew they were being measured?

It did increase staff awareness of productivity. Staff became more responsible in finding ways to fill empty appointment slots. They also checked in more when there were higher than normal no-show and cancellation rates, just to make me aware. When the staff realized that the measurements were not being used punitively, they relaxed more. I think if you are transparent with how you are using it, people are less negative. Staff who were curious about the business health of the clinic liked to see the productivity data. After we returned to work following the pandemic quarantines of Spring 2020, monitoring productivity became more important than ever in understanding how the department was performing. However, given the increased stress everyone felt during those times, sharing productivity information did not help mental health. We had several providers switch to a hybrid work schedule where patient contact hours were consolidated into larger blocks so that non-patient contact time could be spent at home, reducing potential exposure to SARS-CoV-2. Although productivity didn’t necessarily change, there was an increase in work-related stress. So until things normalize (whatever that means), I’m keeping the productivity work behind-the-scenes.

18. Are there other clinical metrics you use?

Oh yes, plenty. One thing I track is the proportion of visits we see. This was actually really interesting during the pandemic. Prior to the pandemic, patients being evaluated by Otolaryngology accounted for about half of our caseload. This population decreased significantly, whereas our electrophysiology patients increased significantly during the same period because they were considered time-sensitive following referral on the newborn hearing screening. We have only just recently started to see the proportions approach the pre-pandemic pattern.

Another I like to look at is appointment lag. This is the difference between the time an appointment was scheduled and the appointment date. It is essentially a measurement of wait times. Depending on how our schedule is set up, different visits can be accommodated earlier than others. When I see one type of visit having a longer lag than the others, that tells me that there might be something wrong with how the schedule is templated. Currently, our longest lag is with auditory processing testing. This we know is due to a limited number of providers qualified to administer the testing. Sometimes I have seen that our lag for ABR testing is larger than we’d like, so we’ll change some behavioral slots over to ABR slots to accommodate the demand. 

19. For those of us in smaller clinics, how might we benefit from all the work you’ve done? Does it apply to us too?

I’ve learned to appreciate the flexibility and scalability of productivity. I think any size clinic may have questions about performance that could be answered by exploring productivity. For example, a manager might have a gut feeling that productivity in summer is worse than other seasons, but not be sure if its due to staff taking vacations or decreased patient demand for services. Comparing WHPUOS across the seasons would give an answer. If the WHPUOS is lower in the summer, then there is likely decreased demand for services. 

20. Any final words?

My take home message would be that productivity is a tool that can be customized and used in lots of different ways. It can be a rough estimate or a very detailed calculation. It can reveal inequities in workload across clinicians or satellites. It can show you what direction to support expansion. It can be something you refer to regularly or just when a question comes up. Understanding how to measure productivity is a powerful skill for evaluating the health of your practice or clinic. I’m very happy to be contacted if anyone wants to learn more.