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Maximum Infusion Center Capacity: More Than Chair Counts

Sofia DeMarco

Director, Product Management, LeanTaaS

Infusion centers have the common goal of providing services to meet the needs of as many patients as possible, and before optimal patient scheduling can occur, an infusion center must first determine its maximum capacity.

We can think of determining an infusion center’s maximum capacity in two big steps. First, there’s the calculation of a center’s theoretical maximum capacity. Then, there’s the factoring in of real-world circumstances that affect how much of the theoretical maximum capacity can effectively be captured.

Calculating theoretical maximum capacity

Calculating an infusion center’s theoretical maximum capacity is a straightforward equation, and it’s represented by Total Available Chair Hours, a product of a center’s hours of operations multiplied by its total count..

Total Available Chair Hours = Hours of Operations x Chair Count

Total Available Chair Hours is a good starting point in defining a theoretical upper bound. There’s no possible way a center can deliver more patient hours than what chair hour capacity can accommodate. It’s a relatively fixed capacity unless the center is willing to make the capital investment of adding chairs and, if necessary, additional space, and/or make the operational investment of increasing the hours of operation. 

At its simplest, the two fundamental levers to push and pull on to impact Total Available Chair Hours are infusion chairs and operating hours, with nursing hours and pharmacy resources as additional key variables. Using basic geometry, the maximum capacity for an infusion center can be represented by the area of the rectangle, below. 

important to note that it’s never feasible for an infusion center to operate at 100 percent of theoretical capacity. Doing so would require starting as many patients as a facility has chairs the first thing in the morning, and then keeping every single chair occupied and in-service throughout the entire day. Not only does that model not take into consideration the inherent variability of infusion treatments, operationally it requires having the same number of nurses as there are chairs – 15 chairs would require 15 nurses to run them all simultaneously at full capacity since one nurse can only start the treatment for one patient at a time. 

Understanding effective capacity

As it’s not feasible to operate at a theoretical maximum capacity, the key to operating at an optimal capacity involves “shaving off” parts of the theoretical capacity that are not capturable to discover the effective capacity that can be utilized. 

The first cut into capacity is the determination of ramp up speed, or how long it takes to reach full capacity at the start of the day. Factors affecting ramp up speed include the following:

  • Nurse staffing (number of nurses available at each point throughout the morning, and the amount of time needed to start each patient)
  • Lab availability & capacity
  • Pharmacy availability & capacity

As it relates to ramp up speed for the infusion center, the capacities of both the lab and the pharmacy are constraints. For example, if the max capacity of a center’s pharmacy is to mix the drugs for eight regimens per hour, then an infusion center cannot ramp up any faster than that.

With the impact of resource constraints, the best method to determine ramp up speed is to follow the best case scenario, analyzing the data from recent days that were ramped up the quickest and applying those results to optimal capacity calculations.

In addition to impacting ramp up speed, nursing resources play an extremely important role in determining volume goals, with touch time, headcount-to-patient ratios, and expectations of patients seen per shift each playing a part. Touch time is the amount of time a nurse needs to get started with a patient, and it directly impacts the ramp up speed that is possible. Established nurse headcount-to-patient ratios imply an effective number of chairs that can be utilized during fully staffed portions of the day, and it may be less than the physical chair count. For example, if guidelines suggest a nurse can adequately serve four patients at a time, a facility with 10 nurses could serve a maximum of 40 patients at one particular time during the day, regardless of whether 50 chairs are available. Lastly, the expectations for the number of patients seen per nursing shift is another limiting factor; if there’s an upper limit of 8 patients seen per nurse and there are 10 nursing shifts, the capacity is limited to 80 patients. 

The second shaving cut into scheduling capacity involves the consideration of ramping down at the end of a day. Ramp down speed is a function of the following:

  • Number of nurses available at each point throughout the afternoon and the amount of time needed for patient disposition
  • Last appointment start time
  • Pharmacy availability & capacity

An infusion center will never have all of its chairs full until closing time, but how deeply the ramp down cuts into capacity can be influenced by adjusting the factors above. Managers can evaluate the impact of adjusting the final appointment start time or an extension of pharmacy availability to determine if a positive return on investment can be realized by stretching available capacity.

Calculating effective capacity

Once an infusion center has shaped its theoretical capacity into a more realistic effective capacity by adjusting for ramp up and ramp down time based on historical data and assumptions that are safe, reasonable and achievable, schedulers can begin to calculate the capacity available and place appointments to fit the space. 

Thus far, we’ve thought of the capture-able capacity of the infusion center is essentially the area of the trapezoid in the graph below, which we can easily calculate by summing the area of the ramp up time, the ramp down time, and the rest of the day in between. 

However, the capacity in terms of patient hours still isn’t the answer an infusion scheduler needs. Determining the number of patients that can be scheduled into this shape can be estimated quickly by dividing patient hours by the average treatment length. A more precise calculation involves a typical daily mix of appointment lengths – one hour appointments, two hours, three hours, etc. – and  scaling that mix until it reaches the number of patient hours previously calculated. 

A final consideration is the variability of the day, caused by add-on cases, no-show appointments, allergic reactions, patients who need more fluids, or any of the myriad of situations that can possibly affect patient hour capacity. One way to estimate variability is to examine historical data and contrast actual chair utilization with scheduled chair utilization. Typically, those analyses show a degree of over utilization with regards to plan or budgeted time, and in those cases, it’s wise to insert buffer time and schedule into fewer chairs than the total number available. 

If an infusion center is changing its schedule substantially, historical data may not be predictive of future variability. In those cases, a more precise forecast requires running simulations over a proposed schedule. Simulations can be run through a solution like LeanTaaS’ iQueue for Infusion Centers, or with healthcare systems’ data scientists. Regardless of how it is conducted, a simulation should effectively identify patterns in historical data and then measure the impact of those repeatable patterns over a proposed schedule. The number of buffer chairs needed depends on the level of variability in infusion operations, and the three most important variations to consider are: 

  • Variation in patient arrival time
  • Room-in variation, or the wait time due to operational delays
  • Room-out variation, or the variation in treatment length

Maximizing effective capacity

When looking to optimally schedule, it’s important to schedule to effective capacity, not theoretical capacity. But it is possible to expand an infusion’s center effective capacity to better accommodate the needs of patients and providers. The best practices for maximizing effective capacity include:

  • Smooth out scheduling. When fully staffed, avoid large peaks and valleys in patient hours scheduled, especially during the mid-day “hump.”
  • Quicken daily ramp up time. Align lab and pharmacy availability to the opening hours of the infusion operation, and increase morning nursing coverage.
  • Utilize the afternoon better by shortening ramp down time. Ensure sufficient nursing coverage at the end of the day, align pharmacy availability to the infusion operational hours so that appointments can start late in the afternoon, and plan to have provider coverage until the end of the day.
  • Extend hours or add chairs. Increase overall upper theoretical capacity limitations by changing previously fixed constraints. 

For more information on how to maximize an infusion center’s effective capacity, please watch the recorded webinar on demand, “Infusion Center Capacity: More than Chair Counts.” 

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