Abstract-Forms are a major source of input for getting data into the underlying medical databases of electronic health/medical record (EHR/EMR) systems. Standardizing encounter forms and integrating data collected from different forms into a single database would greatly reduce heterogeneity. In this paper, we describe a framework, the fEHR-plus system, that annotates, maps, and integrates user-specified encounter forms into a single database. The development of the framework incorporates machine learning, standard medical terminology, and the principles of database design. We conduct an empirical study with 52 forms collected from 6 medical institutions for evaluating the performance of the fEHR-plus system. The overall results show that the system is promising towards improving interoperability among electronic health record systems
