Most of the assignments can still be distributed following the defined probability ratios among eligible doctors regardless of how other assignments are distributed among eligible doctors.
#Anesthesia scheduler how to#
In this setting, how to distribute the probabilities among eligible assignments for each doctor (the probability distribution in the row direction) becomes a challenge. Note that these numbers do not represent the probability ratios in the row direction. The number in each cell represents the probability ratio among doctors, or how each assignment is distributed among doctors (the probability distribution being in the column direction). Now, in a more realistic group setting, every doctor does not do every assignment and each assignment may not be equally shared among doctors (Table 2). These constituent numbers can thus be treated as probability distributions for each assignment (in the column direction) as well as for each doctor (in the row direction). It will become clear later that the requirement for correctly defined probabilities is the summation of probability for each column, and each row is exactly 1.0 in distribution Table 1. With a correctly defined target, the scheduling is feasible.
The key in this example is not so much that each assignment is equally shared by every doctor, but that the probabilities for each doctor to do each assignment are correctly defined every day (in this case, they are all 0.1), or that the target is correctly defined for every doctor and every assignment. The resulting schedule will show that over a period of 100 days, each doctor will do each assignment 10 times, and each assignment will be assigned to each doctor 10 times as well. Here, the assignment distribution is defined. If every doctor does every assignment and does it equally, then every doctor’s fair share, or probability to be assigned to each assignment each day, is 0.100, as illustrated in Table 1. Now, let’s look at a group practice setting where we have 10 doctors and 10 assignments (A1 to A0) to be filled. Or each doctor has a 0.1 probability of being assigned to this assignment each day. Then, each doctor’s fair share is 0.1, which means over 100 days each doctor should be assigned exactly 10 times to this assignment. To illustrate, let’s assume one assignment is shared equally by 10 doctors (D1 to D0). In other words, the target needs to be defined first, because the scheduling algorithm is nothing more than a strategy developed to ensure the defined target is followed. To reach this goal, one must first figure out what the fair share is for each assignment for each member, and use it as the target in scheduling. A new strategy based on a totally different approach is introduced that effectively fixes the problem.Ī Fair Schedule: Accurate Distribution of Assignment ProbabilitiesĪs previously noted, a fair assignment schedule is one in which every member has his or her fair and predictable share of eligible assignments over a period of time. This situation, which should never happen, is undoubtedly a result of a poor scheduling strategy. A hole in a schedule means there is an assignment that no eligible member can do that day, because all the members eligible to do that assignment have been given other assignments and, at the same time, a member is left with no assignment to do, because all the assignments that member is eligible to do have been delegated to other members. In this article, the root cause of such statistical problems is delineated and a solution is presented.Īnother common deficiency in scheduling programs is the schedule that is generated often contains holes. Such a solution only perpetuates the problem.
A common theme of scheduling programs is that statistics get out of whack over time, and the solution as recommended by the developers is the statistics should be reset to zero.
#Anesthesia scheduler software#
That being said, there is hardly any scheduling software available that can achieve these results. It doesn’t seem difficult to expect that a scheduling program be capable of fulfilling such seemingly obvious requirements.
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