In almost all instances, allow for placement of an unknown disease into one of the 10 major disease groups . Years of using the algorithm have convinced me that this problem-oriented approach is readily learned and is surprisingly accurate. I would, however, like to offer several caveats. First, algorithms, when applied too dogmatically, are inherently anti-intellectual, don’t stop thinking, and don’t forget to use common sense when you work with this (or any) algorithm. Second, an algorithm is a training device. Don’t become so dependent on it that you can’t function without it. As experience increases, your visual memory will become sufficiently accurate to use it and save yourself the extra steps involved with application of the algorithm. Third, sometimes will be hard to choose between the two groups at the end of a branch. In this situation, formulate your list of differential diagnoses from both groups. This still leaves you with only a small number of diseases for further consideration. Fourth,
in spite of your best efforts, there will be the occasional instance when you fail to obtain the correct diagnosis. When that happens, consider the following possibilities:
- the patient’s disease was too rare or too unimportant to be included in the “essential” list
- an error was made in your initial description of the lesions or
- a wrong turn was taken at one of the branch points while using the algorithm.
Nothing will help, of course, if the disease is not on the essential list, but the latter two errors can be rectified by reviewing the accuracy of the findings on physical examination and by readdressing the questions contained in the algorithm.
Tags:algorithm, disease, Disease Algorithms, disease groups, Human Anatomy and Physiology, Lesions oriented approach
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