This paper describes a methodology for increasing the scope and precision of diagnostic Knowledge Based (KB) Systems. It has been stated that medical KB systems are either highly specialised, lack accuracy or are just too simple. To resolve this problem of scope we propose the use of a phased approach to diagnosis. The first phase being the querying of a symptoms ontology, to direct diagnostic systems to the most appropriate domain or class reference given input symptoms. Additional symptoms can then be targeted, extracted and analysed with a domain specific set of KB systems. This process allows us to forecast key symptoms, patient characteristics and increase the value of available data in decision making. In addition this approach could allow a system to dynamically correct an inappropriate domain decision. Such an approach also has the potential to be used to build a bridge between existing specialised medical KB systems.