Merging medical informatics and automated diagnostic methods.

In many instances disease diagnosis is more of an art than a science due to the complexity of disease, lack of detailed information on parameters that are indicative of the disease, and lack of sufficient data to apply these parameters to both diagnosis and treatment. Broad-based expansion of electronic health records (EHRs) will produce additional data for improved model development. However many obstacles remain. Patient record content is not broadly available because of privacy concerns and the lack of standardization of EHR formats. If available on a large scale, de-identified medical records can provide a basis for development of disease models by removing privacy concerns. Once comprehensive disease models have been developed that assist in identifying possible diseases and also include parameters that were utilized along with their relative importance, automated analytic methods can be used to indicate the likelihood of the presence of specific diseases. Although the physician will always remain as the final expert, these methods can provide an expanded information set and provide analysis that is too complex for standard methods.