A Cloud-based Surveillance and Performance Management Architecture for Community Healthcare

Abstract

Governments and healthcare providers are under increasing pressure to streamline their processes to reduce operational costs while improving service delivery and quality of care. Systematic performance management of healthcare processes is important to ensure that quality of care goals are being met at all levels of the healthcare ecosystem. The challenge is that measuring these goals requires the aggregation and analysis of large amounts of data from various stakeholders in the healthcare industry. With the lack of interoperability between stakeholders in current healthcare compute and storage infrastructure, as well as the volume of data involved, our ability to measure quality of care across the healthcare system is limited. Cloud computing is an emerging technology that can help provide the needed interoperability and management of large volumes of data across the entire healthcare system. Cloud computing could be leveraged to integrate heterogeneous healthcare data silos if a regional health authority provided data hosting with appropriate patient identity management and privacy compliance. This thesis proposes a cloud-based architecture for surveillance and performance management of community healthcare. Our contributions address five critical roadblocks to interoperability in a cloud computing context: infrastructure for surveillance and performance management services, a common data model, a patient identity matching service, an anonymization service, and a privacy compliance model. Our results are validated through a pilot project, and two experimental case studies done in collaboration with a regional health authority for community care.