New business models and technologies offer unique opportunities of combining patient demographics and clinical data with general consumer data. We are building a digital health platform using a new paradigm based on an open platform as a service (PaaS) that delivers data and analytics across a wide variety of cloud computing topologies. This new architecture gives us the ability to integrate devices, data sources and services very quickly to create, refactor, migrate, deploy and maintain scalable, secure, high quality healthcare and wellness applications while reducing the total cost of ownership.

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Mobile devices offer new ways for users to access health care data and services in a secure and user-friendly environment. These new applications must be easy to create, deploy, test and maintain, and they must rely on a scalable and easily integrated infrastructure. In this paper we present the motivations and technical choices for creating a REST API integrated with a mobile application (iPhone/iPad) that offer physicians, access to their patients' health records via a community, regional or state Health Information Exchange (HIE). We describe the architecture of the system, including how we address security and privacy concerns, the REST API operations and HL7 subset data format used for lab results and observations. We also explain why the early use of unit tests and integration tests were essential to the success of the project.

Portals are Web-based applications that give users a centralized point of access for information and applications of relevance. Therefore the portal paradigm is an attractive proposition for healthcare because it offers a solution to rapidly aggregate heterogeneous applications and services while offering a high level of customization and personalization to the users, patients, care givers and IT personnel. In this paper, we explain the motivations that led us to integrate a portal framework on top of our solution stack to create healthcare solutions for our partners and customers. We describe the challenges associated with this type of infrastructure for healthcare applications including security and context management. We present concrete solutions for specific portal applications integrating EHR, PHR, care and disease management functionalities.

The PAPAyA platform has been designed to ingest, store and process in silico large genomics datasets using analysis algorithms based on pre-defined knowledge databases with the goal to offer personalized therapy guidance to physicians in particular for cancers and infectious diseases. This new highly scalable, secure and extensible framework is deployed on a cloud-based digital health platform that provides generic provisioning and hosting services, identity and access management, workflow orchestration, device cloud capabilities, notifications, scheduling, logging, auditing, metering as well as specific patient demographic, clinical and wellness data services that can be combined with the genomics analytics results.