Comprehensive patient view, communication and data sharing, and population health management are key components

Federal agencies have been incenting healthcare providers to leverage their electronic health records (EHRs) to get patients involved in the management of their care. Most organizations, however, haven’t moved beyond patient engagement as an item to be checked off in order to receive meaningful use incentive funding.

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Introduction

As healthcare providers face increasing pressures to lower costs and reduce readmissions, they're rapidly shifting towards accountable?care organizations (ACOs) and other coordinated, quality-based reimbursement systems. However, most providers have historically?organized their data and workflows in ways that best fi t the fee-for-service payment model. Now that so many providers are sharing?risks and rewards, they must also share and coordinate information by adopting more streamlined health information technology?solutions.

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Providing a reliable infrastructure for rapid, unattended, automated failover

Technology Overview

Traditional availability and replication solutions often require substantial capital investments in infrastructure, deployment, configuration, software licensing, and planning. Caché Database Mirroring (Mirroring) is designed to provide an economical solution for rapid, reliable, robust, automatic failover between two Caché systems, making mirroring the ideal automatic failover high-availability solution for the enterprise.

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Providing a reliable infrastructure for rapid, unattended, automated failover

Technology Overview

Traditional availability and replication solutions often require substantial capital investments in infrastructure, deployment, configuration, software licensing, and planning. Caché Database Mirroring (Mirroring) is designed to provide an economical solution for rapid, reliable, robust, automatic failover between two Caché systems, making mirroring the ideal automatic failover high-availability solution for the enterprise.

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Executive Overview

In most organizations, events drive action. In financial services, for example, a stock dipping below a threshold price may trigger a sell order. In manufacturing, production may start when an order is received. In healthcare, an unusual increase in the number of patients registering in an emergency room could signal the start of a disease outbreak, calling for action on the part of medical staff and public health officials.

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Introduction

To overcome the performance limitations of traditional relational databases, applications - ranging from those running on a single machine to large, interconnected grids - often use in-memory databases to accelerate data access. While in-memory databases and caching products increase throughput, they suffer from a number of limitations including lack of support for large data sets, excessive hardware requirements, and limits on scalability.

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Abstract

In a recent benchmark test of an application based on InterSystems Caché, a sustainable rate of 8.9million database accesses/second, with peaks of 16.9 million database accesses/second, was achieved. These results were from a test performed on a connected system of eight applications servers, using Intel Xeon 5570 processors, and running Linux as the operating system. This benchmark shows that:

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The Business Case for InterSystems Ensemble

This document presents a business case for replacement of older interface engine software with our next-generation rapid integration product, Ensemble. To illustrate the business case, our primary example will be an InterSystems customer (Metro Health Corporation) that replaced its SeeBeyond eGate (now Sun SeeBeyond) interface engine with Ensemble. Other organizations also will comment on reasons for switching to Ensemble.

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Abstract

The European Space Agency (ESA) has chosen InterSystems Caché as the database technology for the AGIS astrometric solution that will be used to analyze the celestial data captured by the Gaia satellite.

The Gaia mission is to create an accurate phase-map of about a billion celestial objects. During the mission, the AGIS solution will iteratively refine the accuracy of Gaia's spatial observations, ultimately achieving accuracies that are on the order of 20 microarcseconds.

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