Setting wait time targets in a multi‐priority patient setting

In current clinical practice, priority-specific wait time targets are usually determined based on the consensus of medical specialists and health care administrators. The rationale behind this approach considers urgency but it does not consider efficient use resources patient volume associated with each priority class. we present here aims to determine in a systematic fashion that both respects clinically acceptable maximum recommended times clinic size demand distribution across classes. First, discuss performance several advance scheduling policies literature terms average overtime select one for illustrative purposes. Second, simulate chosen policy given fixed system capacity approximate (using regression neural networks) class as function potential targets. Finally, using parameterized cost function, formulate forward inverse mathematical problems when implicit unit costs drop zero target values increase. Using examples two classes, practical application four demonstrate managerial benefits proposed improved efficiency reduced times. This ensures set minimum value still achieves maximal resource ensuring patients service is extended unnecessarily.