Healthcare operations generates large volumes of data. Big data analytics methods are needed to derive actionable and decision-quality 'intelligence' from 'big' healthcare data in order to improve patient care. Given the technical challenges to big health data analytics, in this paper we present a specialized health analytics platform-H-DRIVE (Health Data Reconciliation Inferencing and Visualization Environment). H-DRIVE is an integrated, end-to-end health data analytics service-oriented workbench designed to empower data analysts and researchers to design analytical experiments and then perform complex analytics on their health data. We present the high-level functional and technical architecture of H-DRIVE. As a case study, we demonstrate the application of H-DRIVE in the context of optimizing the operations of a provincial pathology lab, where we analyze province-wide lab orders to prepare scorecards outlining physician lab testing performance and offer an operational dashboard to provide an overview of lab utilization.

The Integrated Management Program Advancing Community Treatment of Atrial Fibrillation (IMPACT-AF) is an investigator designed, prospective, randomized, un-blinded, cluster design clinical trial, conducted in the primary care setting of Nova Scotia, Canada. Its aim is to evaluate whether an electronic Clinical Decision Support System (CDSS) designed to assist both practitioners and patients with evidence-based management strategies for Atrial Fibrillation (AF) can improve process of care and outcomes in a cost-efficient manner as compared to usual AF care. At least 200 primary care providers are being recruited and randomized at the level of the practice to control (usual care) or intervention (eligible to access to CDSS) cohorts. Over 1,000 patients of participating providers with confirmed AF will be managed per their provider's respective assignment. The targeted primary clinical outcome is a reduction in the composite of unplanned cardiovascular (CV) or major bleeding hospitalizations and AF-related emergency department visits. Secondary clinical outcomes, process of care, patient and provider satisfaction as well as economic costs at the system and patient levels are being examined. The trial is anticipated to report in 2018.

Health is generating large volumes of data that can provide invaluable insights into clinical and operational aspects of healthcare delivery. There is a general lack of specialized and integrated health data analytics platforms that offer technical methods to support the entire health data analysis pipeline-i.e. health data selection, integration, analysis, visualization and sharing. This paper proposes the technical architecture of a health data analytics platform that offers a technical solution for analyzing 'big' health data originating from multiple sources with heterogeneous terminologies and schemas. A key aspect of the architecture is data standardization, where we have used SNOMED-CT as a terminology standard to standardize health data from multiple sources. We offer a single step health data integration solution where users can select the data sources and the data elements from multiple sources, and our platform performs the data standardization and data integration to prepare an integrated dataset. We present a case study involving large volumes of laboratory data that is integrated and analyzed using our platform.

An extension to the lattice algorithm for designing decision-making organizations subject to cultural constraints is presented. Hofstede dimensions have been used to incorporate cultural attributes in the design process in the form of constraints on the allowable interactions within the organization. An example is used to illustrate the approach.

This paper discusses the specifications, methods, and constructs to implement end-to-end Service Oriented Architecture (SOA)-based systems engineering across a federation of information domains. It addresses the necessity and benefits of a repeatable service design framework and its ability to consistently yield quantifiable results for SOA performance evaluation. An illustrative example of the approach is presented.prise Service Bus (ESB)-enabled, event-driven SOA for our design framework. The discrete event simulator OMNet++ 1 provides the behavior environment in which SOA-based performance is evaluated. Thus, a framework wherein servicebased information solutions can be evaluated across a federation is established. By demonstrating how service-oriented architectures can be evaluated in quantifiable terms, SOA architects will have a reliable tool at their disposal for evaluating design options and overall service performance.