I’m in the process of reading a very good research paper entitled, Buffer Management to solve bed-blocking in the Netherlands 2000-2010. Cooperation from an integrated care chain perspective as a key success factor for managing patient flows. This paper is from the International Journal of Integrated Care. For anyone interested in reading this paper, just send me an email to ras8202@live.com and I’ll be happy to send it to you. This is my very first posting related to healthcare, but everything we’ve discussed here applies to healthcare as well.
Let’s start with the definition of bed-blocking. A bed-blocker is a patient who has completed treatment in one part of the care chain (e.g. a hospital) and is waiting for admittance to the next part of the chain (e.g. a nursing home or home care). Bed-blocking has consequences at various levels. For example, at the micro level, bed-blocking increases the waiting time for new patients while at the macro level, it impacts healthcare costs as an occupied bed in a hospital is more expensive than an occupied bed in a nursing home or even an occupied bed at home. These days we are all concerned about the soaring costs of healthcare. This paper that I referenced seeks to first explain the theory of buffer management and secondly, to discuss previous assumptions that the authors had apparently made.
Buffer Management builds upon the Theory of Constraints’ drum buffer rope that we have discussed in previous blogs. DBR attempts to maximize the throughput in the chain by first identifying the system constraint and then taking measures to manage it. One key point made by the authors is that the constraint determines the flow of the entire value stream and that when the constraint is identified, DBR can be used to balance patient flow into the next part of the chain. One of the goals of DBR is to determine how many patients should be admitted to the hospital as well as the throughput from the hospital to places like nursing homes. When the buffer overflows, the rope, which is an information stream, closes the hospital doors for potential (elective) buffer patients. These type patients are typically ones with mobility problems, rehabilitation needs or cardiovascular problems.
The authors tell us that correct execution of Buffer Management requires that the following prerequisites for successful BM be taken into account:
· In order to balance the flow, the entire process including its sub-processes must be considered.
· Total flow can only be effectively increased by increasing the flow of the bottleneck.
· In order to prevent queues, the buffer needs free space to absorb fluctuations which are most frequently caused by non-elective patients. A maximum occupancy of 70% is considered acceptable.
· The use of a rope to adjust input rate at the beginning of the process is necessary to prevent overflow in the sub-processes.
The authors go on to explain that in practice, the buffer is often used incorrectly and that these prerequisites are infrequently considered and the rope is rarely used. They also tell us that another misconception is that if the sub-processes are optimized, the flow of the entire process will increase. Of course, those of us who practice TOC know that this is referred to as local optimization which leads to unbalanced flow simply because flow is determined by the constraint. We also know that we should always be striving for system optimization.
As I said in the beginning of this posting, if anyone is interested in receiving the full research report, just email me and I will be happy to send it to you. In my next posting, I'll present why the authors believe that care providers fail to to establish the prerequisites.
Bob Sproull
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