A methodology to reduce the complexity of validation model creation from medical specification document

In this paper we propose a novel approach to reduce the complexity of the definition and implementation of a medical document validation model. Usually the conformance requirements for specifications are contained in documents written in natural language format and it is necessary to manually translate them in a software model for validation purposes. It should be very useful to extract and group the conformance rules that have a similar pattern to reduce the manual effort needed to accomplish this task. We will show an innovative cluster approach that automatically evaluates the optimal number of groups using an iterative method based on internal cluster measures evaluation. We will show the application of this method on two case studies: i) Patient Summary (Profilo Sanitario Sintetico) and ii) Hospital Discharge Letter (Lettera di Dimissione Ospedaliera) for the Italian specification of the conformance rules.