Full-time equivalent (FTE) is a way to measure a worker's involvement in a project, or an assigned task for his or her organization. The definition of FTE is the number of working hours that represents one full-time employee during a fixed time period, such as one month or one year. FTE simplifies work measurement by converting work load hours into the number of people required to complete that work. These are numbers based on annual budget submission and authorized funding credit. An FTE of 1.0 means that the person is equivalent to a full-time worker, while an FTE of 0.5 signals that the worker is only half-time or part-time. An FTE of 1.0 (40 hours/week x 52 weeks/year = 2080 / year) is calculated based on negotiated annual personnel salary for a typical 8-hour period minus over-time. Additionally, base pay is added into the annual budget for 10% overtime plus 40% benefits. Typically, different scales are used to calibrate this number, depending on the type of institution (schools, industry, research, government,etc.) and scope of the report (personnel cost, productivity or manpower). The strong message to all hospital administrators (CEOs) is they want to know did the hospital organization make the right choice hiring additional personnel by using a technique called Return on Investment.[1]

FTE Management

FTE management is the analysis, decision making, and change implementation processes that determine:

  • how many employees are needed
  • the skills each job position needs and the total available skill hours the department needs
  • how work will be assigned to employees
  • how organizational and staff performance will be measured

Proper staffing levels will ultimately radically improve overall productivity, reduce outside contract costs, improve patent safety and quality, and achieve organizational growth.

For example, clinical engineer managers spend about 7 to 8 hours over 2 to 3 weeks on a major project meeting. Typically, These three Project Phases & Deliverables is what a manager would perform without any unforeseen problems (a perfect world!)

1. Project preparation meeting This meeting occurs a few days before the start of data collection. We discuss your performance goals and problems, show you our project approach, and discuss the final models that your problems require.

2. Model assessment and review meeting This meeting delivers your models and reports. Using an analysis of the root causes of your problems, organizational costs, training opportunities to quickly solve them, and the cost/benefit of these solutions.

3. Wrap-up meeting This meeting evaluates your project experience, lessons learned, and your new cost models.

Basic FTE example

To calculate the very basic formula here it is...

FTE = Scheduled Hours + unscheduled (work performed) Hours / 2080 (hours)

Although this is not the most accurate calculation and working 100% of the time is impossible it is still the very basic formula.

First FTE example

This is the author's preferred method of calculating FTEs for BMETs. In fact, an inaccurate medical device inventory (e.g. missing or dropped inventory equipment, poor data quality management, and submitting erroneous work order hours) can "all" result in inaccurate FTE calculations or measurements.

First, a clinical engineering manager will calculate the PM hours, calibration hours, parts replacement hours, travel, etc... per medical device type or class. Additionally, he or she will add total unscheduled hours to the scheduled hours to an accurate benchmark. For example, we use the following factors below to calculate our FTEs.

  • 4800 total medical devices in our inventory
  • PM'd 100 infusion pumps in our inventory.
  • Performs 2 PMs per year on every infusion pump.
  • Average time to perform the PM is 30 minutes (.5 hours)
  • 1200 unscheduled hours per year

Next, a manager will calculate how many recommended PMs to perform each year multiplied by how long does it take the average person to complete the necessary PM (.5 hours = 30 minutes or 1.0 hour)

So the formula looks like...

 1 (PM Hours /Device) = 2 * .5

Secondly, the manager will perform an additional calculation for the total PM hours per year. Earlier, we mentioned that we have a total of 100 infusion pumps in our hospital inventory. So, if it takes an average time of 1 PM hours per device that equals a total X of PM hours per year spent PMing 100 infusion pumps.

Again, the formula looks like...

 100 (PM hours / Year) = 1 * 100

Now, for 100 devices that appears small but calculate total hours for every device type and device model per year and it adds up. Recall that for for every device type and device model there are different hours to complete the PMs. The manager will have to do research to find out those exact times to ensure accurate results.

Lastly, 1380 total available chargeable hours is divided by the total hours for scheduled (inspections, PMs, parts replacement, and calibrations) and unscheduled maintenance acceptance inspections, projects, and repairs). In our example 1200 unscheduled hours plus an estimated 2800 scheduled hours equals 4000 total labor hours.

the FTE formula looks like...

2.89 (FTEs) = 4000 / 1380

So, our answer round-up is 3 BMETs. Other variant factors that can be added are:

  • Subtracting contractor service hours
  • Adding travel time
  • Adding administrative time

Second FTE example

"For the purposes of this article, we’ll assume the inventoried medical equipment can be categorized into four groups: biomedical (Bio), radiology (Rad), laboratory (Lab), and IT devices. We’ll further assume that additional device detail is available to subcategorize each of these groups into high-end or low-end groups in accordance with the complexity of its service needs. This method results in eight categories, which can be abbreviated Bio1, Bio2, Rad1, Rad2, Lab1, Lab2, IT1, and IT2. While many CMMS can easily break out an inventory by the radiology and biomed modalities, you may need additional customization or input to classify all devices into those eight modality and complexity-specific categories. For improved accuracy, the new FTE model should adjust for or exclude devices with full service contracts and should also include travel hours required between facilities. Through evaluating the best practices of specific technicians or sites, you may add efficiency-level expectations based on prior performance data (such as average hours per PM or repair by device). You can then set targets indicating how many devices one FTE can be expected to service at your desired level of efficiency. For example, a rough estimate could be 1,500 low-end biomed (Bio1) devices per FTE, 400 high-end biomed (Bio2) devices, 300 Rad1, 100 Rad2, 700 Lab1, 500 Lab2, etc. Multiplying the device counts in each category from the inventory by the device targets per FTE will yield a total number of FTEs needed for the facility.

A slightly more complex version of this new FTE model has been tested and verified at the facilities managed by my employer, TriMedx, and has yielded actionable information for sites with departments ranging in size from one to more than 30 technicians.[2]

Third FTE example

Each clinical engineering department has unique responsibilities that could lead to different staffing needs. For example, a 500-bed hospital by the above formula should have (500÷100 x 2.5) = 12.5 FTEs. Another variable is freestanding diagnostic centers that may include emergency treatment areas as well as diagnostic imaging, outpatient surgery, and laboratory services. By the bed-to-FTE model, these locations contain no "beds" and therefore do not add to the FTE count.[3] Various methods are currently used to determine the personnel needed, including number of devices per biomedical/clinical engineering personnel, number of beds per biomedical/clinical engineering personnel, and acquisition cost per biomedical/clinical engineering personnel.[4]

A First-Rate Model

The numbers presented here for an equipment maintenance model are derived from a mix of soft data and intuition based on experience. They relate best to university hospitals in the 250-400-bed range. They relate better to numbers of devices than number of beds. In summary, they are: 1. Ideal technician workload = 400 to 550 devices. 2. Average technician productivity or ;;hands-on maintenance time = 75%. 3. Average dollar value per device = $2,000. 4. Annual in-house maintenance ratio = 5% to 7% of value plus parts in excess of $200/item. 5. Effective rate per hour = $35 to $45/hr (depending upon region and labor costs in that region). 6. In-house maintenance costs should be less than outside costs. However, the in-house department should be aware of cost-effective outside options and employ them as appropriate. 7. Appropriate resources. 250 sq ft/technician, $20,000 capital equipment/technician, and $15 to $25/device in supplies. 8. Clinical engineers. One engineer to start the service and one engineer for each three additional technicians added. 9. Clerical support. One clerical FTE for a minimum 3 technician department, and one additional clerical FTE for each additional 1.5 FTE clinical engineers or each additional 5 FTE technicians. 10. Annual maintenance = 2.5 hr/device. (When clinical devices are distinguished from nonclinical devices, averages are 3 hr/clinical device and 2 hr/nonclinical device.) As clinical engineers, BMETs, and their departments gather experience to support or modify these numbers, I encourage them to share their findings in an experience pool available to all.[5]


  1. Orient Point Consulting LLC, 2009 FTE Definition,Calculation, Analysis, & Management
  2. Jernigan,James., "Staffing for Excellence: A New FTE Model". 24x7 Magazine. January 2011.
  3. Evans,Gary A. "Clinical Engineering Staffing Models". 24x7 Magazine. March 2009.
  4. Subhan, Arif. Personnel Management/Supervision-CCE Prep. 24x& Magazine. March 2011
  5. Johnston GI. IEEE Eng Med Biol Mag. 1985;4(2):19-24. doi: 10.1109/MEMB.1985.5006167.

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