For a specific diagnostic question either for an individual diagnosis or for an epidemiological assessment (“community diagnosis”) one has to find an adequate diagnostic strategy. The strategy has to be adapted to the severity and the curability of the disease and also to the impact a false diagnostic result may have on the patient. You now know that a diagnostic test can be characterised by its sensitivity, its specificity and its efficiency. In principle, all three test parameters can be optimised. Which one is, or should be, optimised depends entirely on the diagnostic objective being posed.

Here, once more, the different possibilities:
 

1. Maximum sensitivity: leads to a minimisation of false-negative findings
     
   Example: if a false-negative result could lead to the death of the patient (malaria)
    
2. Maximum specificity: leads to a minimisation of false-positive findings
    
   
   Example: for diseases which cannot be cured; for assessing intervention studies comparing incidences in treated and untreated groups (e.g. vaccine-placebo)
    
3. Maximum efficiency: leads to a minimisation of false findings

Caution: Making a compromise on specificity and sensitivity is very often not an adequate solution!