What would you think if your process improvement experts said “we can remove 58% of a type of equipment that is often in shortage, provide better patient care, better response time and never have a shortage again”? Yeah right! Well, that’s exactly what happened. At The Hospital, PCA pumps were in shortage which created enormous frustration with the nurses and decreased patient care. Nurses couldn’t find equipment when needed to do their prescribed job.
PCA pumps are patient-controlled analgesia (PCA) is a method of pain control that gives patients the power to control their pain. The pump, which contains a syringe of pain medication as prescribed by a doctor, is connected directly to a patient’s intravenous (IV) line. The patient has control over when medication is delivered into the IV (with preset limitations of course). The patient pushes the button and gets a dose of pain medication. The advantages of using a PCA unit are:
- Patients having control over their pain medication have lower pain scores.
- Patient have greater satisfaction compared with nurse-administered medications.
- Nurses can be freed from evaluating pain levels and administering pain meds to do other work.
As you can image, when a patient is assigned to Post-Anesthesia Care Unit (PACU) and nurse knows the patient is going to experience more pain, be less satisfied and the nurse will be busier, it has got to be frustrating.
Discovering the Root Cause
The hospital had to perform “fire drills” to maintain an adequate pump supply on a daily basis. Adding more pumps improved the access to the pumps for a period time, but at significant increased expense.
During budgeting, decisions had to be made about acquiring additional pumps to address the persistent shortage. If pumps were added as requested by the nurses, the expense would be significant. The process improvement team decided they need to answer the following questions to determine if additional pumps were needed:
- When are pumps actually used during the day and by day of week?
- What is the “right” number of pumps needed to support The Hospital?
- What is causing the disparity between inventory and availability?
- What process improvements would be needed to reduce inventory and increase availability?
This was a perfect problem for discrete event simulation software. Orders for PCA’s were recorded in The Hospitals system with a date and time stamp. “We just had to extract the data and put it into Excel format.” Using the Healthcare Arrivals model object found in ProcessModel, the history of arrivals could be analyzed input into the model in minutes.
The tools supplied with ProcessModel not only analyse the data, but it also generate the ProcessModel code needed to predict what could happen in future weeks using simulation. This was a huge help in simplifying the model build. What would normally be difficult data manipulation was handled with a single mouse click.
PCA unit patient usage is recorded in the hospital system so that proper billing can be applied. This data could also be extracted from The Hospitals system and converted into a distribution that mimic’d the length of time a PCA might be required a patient.
The process improvement team then observed the handling of PCA units when they were no longer needed by the patient. It was found that most soiled PCA units were moved to a storage closet to be picked up later and cleaned. The observed method was not the approved procedure and little was being done to enforce the procedure. These observation allowed the team to make estimates of how long a pump would stay in storage before cleaning. The actual cleaning time was already documented.
A Simple Model
The process simulation used to depict the system was simple to build. The model was designed, data formatted and data entered in less than an hour. This model development time included creating charts and graphs that illustrate the problem. Below is the model:
The model does not have all the detail of wasting of medications, dual sign-off, etc. But it doesn’t need to have all the detail, because it will be the same in both the As-Is and To-Be. Additional time for wasting medications was added to the usage time. The model allowed the reporting of the predicted PCA pumps needed by hour of day and day of week. The delays caused by the handing of the pumps after usage helped to identify the disparity between the inventory and the actual quantity needed. The graph below shows one week of demand vs inventory. Multiple replication analysis with reports collected every hour provides a method of providing upper limit needs by day of week and hour of day.
The team reviewed the existing procedure and identified additional possible solutions that might provide savings. The main issue was storage of soiled pumps in a multitude of locations. The mismanagement of pumps showed, that on average, pumps would return to service after more than 12 hours (some requiring much, much longer) had elapsed. Many solutions were considered, one simple solution emerged — If you are working with a patient when a pump is not longer needed, return the pump to a central cleaning area within 10 minutes. Although the simple solution was initially balked, it was pointed out that nurses are currently spending more time trying to secure PCA units than would be required by returning pumps to a central location.
The new model provided a method of evaluating the simple scenario. It was found that immediate return of the units would provide for a significant drop in the required inventory and reduced capital requests by more than $200,000. The project may be labeled as common sense, but the problem remained: no one was able to answer the questions “what is the inventory of pumps needed based on demand, recover and cleaning.” The simulation answered those questions and provided a lower limit of PCA pumps, that if crossed, would start to cause waiting for PCA units. Furthermore, the simulation acted as a training tool to help staff understand the result of not returning pumps per the procedure.
Process improvement doesn’t always have to be long projects with huge budgets or projects that can only be tested by trial and error. This project brought the best of a Kaizen Blitz with a detailed statistical analysis to provide patient care improvements, budget reductions and job satisfaction increases for The Hospitals staff.