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A medical algorithm is any computation, formula, statistical survey, or look-up table, useful in healthcare. Medical algorithms include decision-tree approaches to healthcare treatment (i.e., if symptoms A, B, and C are evident, then use treatment X) and also less clear-cut tools aimed at reducing or defining uncertainty. An example would be an algorithm used to determine what next investigation or management to apply to a possible DVT.

The intended purpose of medical algorithms is to improve and standardize decisions made in the delivery of medical care. Medical algorithms assist in standardizing selection and application of treatment regimens, with algorithm automation intended to reduce potential introduction of errors.

Many medical algorithms are paper questionnaires or checklists where only one form is necessary, which often leads to over-simplification, or a cumbersome process with many decision-tree points where errors, sometimes life-threatening, can be introduced. With the increasing use of electronic notes and with the intelligent use of coding and classification systems, algorithms may be applied to hooks in the notes. There is a temptation to introduce algorithms that do slowly something that doctors do well and quickly. That temptation must be balanced against various other considerations.

A wealth of medical information exists in the form of published medical algorithms. These algorithms range from simple calculations to complex outcome predictions. Most clinicians use only a small subset routinely. Computerized algorithms can provide timely clinical decision support, improve adherence to evidence-based guidelines, and be a resource for education and research.

In common with most science and medicine, algorithms whose contents are not wholly available for scrutiny and open to improvement should be regarded with suspicion.

A grammar - the Arden Syntax - exists for describing algorithms in terms of Medical Logic Modules. An approach such as this should allow exchange of MLMs between doctors and establishments, and enrichment of the common stock of tools.

Medical algorithms based on best practice can assist everyone involved in delivery of standardized treatment via a wide range of clinical care providers. Many are presented as protocols and it is a key task in training to ensure people step outside the protocol when necessary. In our present state of knowledge, generating hints and producing guidelines may be less satisfying to the authors, but more appropriate.

Computations obtained from medical algorithms should be compared with, and tempered by, clinical knowledge and physician judgment.

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