Developing an accurate way to document technician workload in a Healthcare Technology Management (HTM) environment can be a daunting task1. This article will discuss the process of deriving workload metrics for a Clinical Engineering (CE) team at an Intermountain Healthcare facility. The CE team at Intermountain’s Utah Valley Hospital performed five different time studies of various lengths over a 10-year time frame, to gauge the different activities performed by our CE techs as well as the time spent doing these activities. These studies were performed during peak Preventive Maintenance (PM) periods and also during slower times. The goal was to gather time spent over a variety of work experiences so the data collected could be useful for workload history. The load tracking methodology outlined in this article has helped the Utah Valley Hospital CE team. It is not to be understood as an industry standard until piloted and validated by other CE teams.
Utah Valley Hospital is a 395-bed full-service tertiary and acute care facility serving Utah County and rural central Utah, as part of the Intermountain Healthcare system2. It is a Level II Trauma Center3. The CE and imaging engineers at Utah Valley Hospital manage Utah Valley Hospital, four rural hospitals in Central Utah and 35 medical clinics which are all part of the South Region system of Intermountain Healthcare.
Tracking CE Workload
Healthcare technology managers should be well versed in what it takes to run their department and to know how many biomedical equipment technicians (BMETs) it takes to keep the hospital equipment maintained. There have been many articles written on the pros and cons of having an in-house HTM program and we believe it works for us. More so, for over 30 years, productivity and staffing continues to be a debatable topic for the clinical engineering community4. However, as a department, we need to prove our worth to the facility and tracking workload had been the way to accomplish that. (Figure 1)
We decided to do a time study to establish a base line for the different activities that a BMET could perform in a normal day and also the time it took to accomplish that particular activity. We put the activities into two categories of “productive” and “non-productive” time (see Figure 1). Productive time, for the most part, can be defined as the time spent by a BMET working on medical equipment and documented on a work order in the computerized maintenance management system (CMMS). The activities include, but are not limited to, preventative maintenance (PM), repair, medical equipment or systems setup, and calibration. Non-productive time, in the traditional sense, includes activities such as attending meetings, education/training and time spent responding to emails.
We ran our first baseline time study for a full month. The BMETs were asked to document their activities in 10-minute time periods. This was overwhelming for the team members. However, after they understood the importance of the time-study they were willing to document their time. Each staff member was given a spreadsheet that would allow them to document their time. They placed a code from the list of productive and non-productive definitions next to the time slot. In some cases, a “P12” was placed in several consecutive time slots. After the month long tracking process, all of the time was combined from the different techs. This was put into a master spreadsheet so calculations could be performed (see Figure 2).
This first study set a baseline for future studies. Over the next 10 years this study was performed 5 different times. We had turnover of staff during this period which was beneficial to the other studies. Different people work in different ways, so we were able to get a fuller picture of how technicians spend their time. Once we established a baseline, the next step was to develop a spreadsheet that is updated monthly, so each technician could monitor their own workload. This data can also be combined as cumulative data which helps in management of our CE department (see Figure 3).
Productive or documented activities are easy to collect but we also should be tracking our “non-productive” hours. A technician will perform many beneficial actions during their work hours but some of these things will not be documented. That is where the time study has been useful. From the study, we can calculate how much time is spent in these non-documented activities and apply a percentage to help figure and round out a full day of work. (Figure 3)
We then take the process one step further and combine the data into a technician calculator (see Figure 4). This technician calculator was developed by Scott James, CBET, and CE director in the north region of Intermountain Healthcare. This was published in the Journal of Clinical Engineering, Oct/Dec 2007 edition5. The information from the tech calculator is what we use to justify hiring either replacement or additional staff. This calculator can show if you are running under or over staffed. It has become an effective tool in our human resource management. (Figure 4)
There is a certain amount of trust that goes with a technician’s documentation. In all honesty, it is not productive for a manager to micromanage an employee. You ask them to do the job, help them understand the importance of that job, and then trust that they will have enough integrity to do that job. We have explained to our technicians the reason for all of this documentation. They have been good about accepting the fact that in order for us to survive as a department we need this data.
After completing the first time study, we were pleased with how these calculated percentages helped to assess how team members were completing day-to-day activities. After completing the final time study, we found that the percentages stayed quite close to the first study. Our first time study gave us a results of P=78.68% and N=21.32% our final study showed P=77.19% and N=22.82%. As you can see the numbers have stayed pretty consistent.
As we continue to spot check documented and undocumented time, we have found these averages continue to hold true. This has proven to be a valuable tool to both management and front-line team members. It has helped us gain trust with hospital administration and leadership teams. Our BMETs appreciate this feedback as they can review their productivity on a monthly basis and set goals for continuous improvement.
Mike Busdicker, MBA, CHTM, is the clinical engineering system director at Intermountain Healthcare. Larson Holyoak, BS, CHTM, is the south region clinical engineering director at Intermountain Healthcare. Priyanka Upendra, BSBME, MSE, CHTM, is the clinical engineering compliance manager at Intermountain Healthcare.
1. Joseph F. Dyro. Clinical Engineering Handbook. 1st ed. Burlington: Elsevier Academic Press, 2004; 200.
2. Hospital Information. Utah Valley Hospital. Available at: https://intermountainhealthcare.org/locations/utah-valley-hospital/hospital-information/. Accessed Oct. 5, 2016.
3. Hospital Information. Utah Valley Hospital. Available at: https://intermountainhealthcare.org/locations/utah-valley-hospital/hospital-information/. Accessed Oct. 5, 2016.
4. Wang B, Rui SIT, Fedele J, Balar S, Alba T, Hertzler L, Poplin B. Clinical Engineering Productivity and Staffing Revisited: How Should It Be Measured and Used? Journal of Clinical Engineering. 2012; 37: 135-145.
5. James, Scott. Biomed Tech Calculator: An Equipment Priority-Weighted Approach. Journal of Clinical Engineering. October/ December 2007; 32(4): 184-185.
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