The Butterfly Effect: Improving the Chemotherapy Visit Experience

Gail Thompson

February 2018, Vol 8, No 2 - Practice Operations


The “butterfly effect” in chaos theory refers to a phenomenon in which a small, localized change in a complex system can have large effects elsewhere. Cody Boyd, BSHA, RT (R)(T), University of Texas Health Science Center at Tyler Cancer Treatment and Prevention Center, shared the experience of such a change at the ACCC National Oncology Conference in October 2017 in Nashville.

After a detailed analysis of the patient’s, provider’s, and organizational perspective of the “chemotherapy visit,” the cancer program team determined that multiple interactions and poor processes were leading to patient dissatisfaction and increased expenses.

The team decided to address this challenge, starting with the premise that “it takes too long for a patient’s chemotherapy infusion visit, from the time of arrival to the chemotherapy administration,” Mr Boyd said. Time seems simple, but even 1 minute wasted can cascade into a chain of events that cross the organization.

5 Areas for Value Assessment

The team identified 5 areas in which value can be added or subtracted:

  1. Registration/check-in
  2. Laboratory work
  3. Nurse triage
  4. Medical oncologist visit
  5. Chemotherapy infusion/injection.

In addition, they identified 5 areas in which “waiting,” or wasted minutes, would not add value and instead cause cascading problems elsewhere:

  1. Waiting after check-in
  2. Waiting for laboratory results to be processed
  3. Waiting to be triaged by a nurse
  4. Waiting to see the physician
  5. Waiting to receive an infusion/­injection.

Opportunities to Reduce Wasted Time

After a period of observation at each of these steps, several opportunities for reduction of wasted minutes were identified.

Patient check-in
Schedules were not truly followed, and patients were sent back to the laboratory after check-in was complete (a process labeled “pushing”).

In the laboratory
Patient wait time was generally clocked at between 4 and 30 minutes. The process of “pushing” patients to the laboratory rather than following the electronic health record (EHR) schedule (which was labeled as “pulling”) was backing up patients. Specimen batching was not in sync with patient needs or schedules. The average patient waited 16 minutes between specimen draw and transport.

In the pharmacy
Many excessive and repeated staff steps were showcased by performing a spaghetti diagram—using a floor plan map, the team drew lines for every step the staff took in the office while performing their process for pharmacy fills. This illustrated an alarming amount of additional work and wasted time. Inefficient placement of supplies was a big contributor to wasted team time in the pharmacy. Mixing time ranged from 2 minutes to as much as 90 minutes; the average was 22.3 minutes.

Patient Survey

The team also gathered patient experience input, with a simple form that patients received at check-in and completed filling out as they went through the process.

The data collection instrument recorded times when patients arrived at check-in, when the check-in process was completed, when they got to and were finished at the laboratory and pharmacy, when their physician appointment was, when the physician actually arrived, and when the physician finished the visit, as well as how long the nursing visits and waiting time were before the physician appointment. The patient data collection ended when chemotherapy began. Patients were also asked to rate their experience against their expectations.

The minutes surprisingly added up, with an average time spent in non–value-added processes far exceeding the time the patient spent in value-added processes. Patients spent an average of just under 1 hour in value-added time: registration, 2.25 minutes; laboratory, 15.38 minutes; nurse triage, 16.46 minutes; the physician visit, 20.92 minutes.

However, patients spent >150 minutes in non–value-added time waiting (between registration and the laboratory test, 1.38 minutes; between laboratory test and the nurse triage, 26.5 minutes; between the nurse triage and the physician visit, 25.42 minutes; and between the physician visit and chemotherapy administration, 94.44 minutes). Approximately 62% of the group’s patient time was spent waiting.

Through a series of value-stream mapping, problem analyses, and observations, Mr Boyd identified several key factors that were designated as problems:

  • Insufficient patient flow into the laboratory
  • Inconsistent chemotherapy schedules
  • Discrepancies between their EHR and MEDITECH (ie, pharmacy) schedules for patients and chemotherapy orders
  • Inconsistencies between actual staff practice and patient pushing related to laboratory schedules.

Suggested Remedies

Some of the solutions that were developed and implemented included development of standard processes for port draws, patient registration, and phlebotomy. A new infusion check-out process was instituted. Patients received education on the new processes. The staff followed the schedules and used the new systems to implement a “pull” rather than “push” system for patients from the start to the end of the process. New patient data collection cards were introduced, and restaurant-style pagers helped to keep the patient flow moving in a timely fashion between departments.

Mr Boyd described the problems that were solved by this new approach: they eliminated laboratory batching, the pharmacy was reorganized, the teams improved communication through use of huddles and more deliberate patient navigation, and the phlebotomy schedules were finally more consistent.

Most important, this project cost next to nothing to implement. The project’s goals were to decrease the total patient visit time by 20%, and to increase the value time quotient for patients by 20%. They were able to decrease the total patient visit time by 27%, to increase the patient value quotient by 14%, and also increase revenue by 17%, through more efficient patient throughput. Minutes mattered—in creating a problem, and in effecting a solution.