We propose an Information Integration and Informatics (III) framework for healthcare applications that leverages the parallel computing capability of a computing cloud based on a large-scale distributed batch processing infrastructure that is built of commodity hardware. Healthcare information integration and informatics presents a potential for building advanced healthcare applications given the massive scale of data which is collected by EHR systems. Traditional EHR systems are based on different EHR standards, different languages and different technology generations. EHRs are mainly designed to store individual-level data on patient-provider interactions. EHRs capture and store information on patient health and provider actions. In this paper we provide a use case of the proposed III framework for development of a healthcare application for epidemiological surveillance. Epidemiological research involves collection, analysis, and interpretation of health data for describing and monitoring a health events. We demonstrate the effectiveness of the proposed III framework for developing advanced healthcare applications that are backed by massive scale healthcare data integrated from heterogeneous and distributed healthcare systems and a scalable cloud infrastructure.