Prescribing is often presented as having four steps, as follows:
1. make the most precise diagnosis possible;
2. identify all possible solutions;
3. choose the best solution and write a prescription;
4. execute this decision.
However, research on decision processes in businesses and organizations shows that this ideal model is rarely used because decisions are nearly always based on incomplete information. Uncertainties affecting prescription include, for example, the following.
- the diagnosis is uncertain; different diagnoses are equally likely or the real diagnosis is not known;
- treatment must be started quickly before the precise diagnosis has been established;
- trial of one treatment will help to make a more precise diagnosis by eliminating hypotheses;
- all possible treatments are not known to prescribers, or not known in very much detail;
- prescribers are not able to find the best prescription, from among the drugs known to them, to fulfil the various objectives of treatment;
- prescribers do not know how patients will react to the treatment prescribed.
These limitations on rational decision have been interpreted by Simon (22) in the following manner: decisions do not follow a substantive rationale of search for the optimum so much as a procedural rationale of search for a satisfactory solution. According to the procedural rationale, decision-making is an empirical process that draws upon experience and knowledge learned on the job. Decisions are reached by experimentation, trial and error, and recourse to routines.
However, the objectives pursued are not always attained. Analysis shows that prescriptions are often far removed from accepted science, even if special conditions are taken into account. The problem to be solved is not to upset but to modify the empirical nature of the process, giving it the necessary resources adapted to its nature.