Increase Differentiation and Boost Business Results with InterSystems IRIS for Health

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The healthcare industry is awash in data—electronic patient records, wearable device data, public-health surveillance data, clinical data, research data, and more. Digital health solution providers (SPs) can move up the value chain and gain a competitive edge by transforming this abundance of data into meaningful and actionable insights.

Data-driven applications and services can help clinicians enhance care delivery and improve patient outcomes. They can help researchers streamline investigations and accelerate discoveries. The list of possibilities goes on and on. But system interoperability barriers and data integration challenges can hinder application development efforts, impede innovation, and impair business results.

Most healthcare applications leverage data from a variety of diverse sources. Healthcare data formats and protocols vary from source to source and vendor to vendor. Collecting, managing, and analysing large, divergent datasets is a significant challenge. Development teams must find efficient and cost-effective ways to gather, unify, clean, and analyse vast volumes of distinct data at speed and scale.

InterSystems IRIS for Health is a comprehensive, cloud-first digital health development platform that provides all the building blocks needed to work with almost any healthcare data standard. Digital health SPs can use InterSystems IRIS for Health to bring differentiated applications and services to market, quickly and cost-effectively.

The InterSystems solution makes it easy to connect to disparate healthcare systems and manage diverse healthcare data with built-in support for HL7® FHIR®, HL7 v2, C-CDA, IHE, DICOM, X12, and other national and global standards. The solution provides out-of-the-box connectivity for a wide range of applications, databases, and technologies. It lets you efficiently collect, integrate, and manage dissimilar healthcare data scattered across diverse environments.

InterSystems IRIS for Health includes a multi-model, multi-workload database management engine that supports vertical and horizontal scalability, and advanced vector search functionality for faster, more accurate queries. The ultra high-performance engine ingests, processes, and stores transactional data at high rates while simultaneously processing high-volume analytic workloads involving historical and real-time data.

InterSystems IRIS for Health provides many of the critical capabilities needed to implement a smart data fabric including built-in analytics, machine learning (ML), and generative AI facilities. Smart data fabrics lay a solid foundation for digital health and healthcare AI initiatives by providing a uniform, extensible, secure, and scalable data architecture. They help overcome interoperability barriers, simplify application development and maintenance efforts, reduce implementation cost and complexity, avoid data duplication and movement, and improve data quality and accessibility. They help organisations manage data gravity and contain costs by breaking down data silos and unifying data.¹

Smart data fabrics include real-time data processing and in-memory computing functionality to accelerate data analysis, embedded ML and AI functionality, self-service analytics, reporting tools to streamline discoveries, and data governance to protect confidential information and ensure compliance.

InterSystems IRIS for Health is highly flexible and extensible. Developers, businesses, and users can add new features, functions, or integrations without altering the core system. This adaptability ensures the platform can evolve and scale to meet new requirements, making it future-proof and versatile.

You can reuse and repurpose InterSystems IRIS for Health building blocks to efficiently address common architectural patterns including:

• Interoperability – Connect disparate systems and interwork dissimilar healthcare protocols and data formats. Enable seamless communication between healthcare providers to improve coordination and continuity of care. Standardise data exchange to reduce the risk of errors and ensure patients’ medical histories are accessible across different platforms.
  
• Analytics – Gather and analyse large volumes of diverse healthcare data at speed and scale for advanced analytics solutions and AI and ML applications. Use real-time data insights to improve diagnosis and personalise treatment plans. Leverage predictive modeling to identify health risks early, accelerate interventions, and improve patient outcomes.
  
• IT simplification and optimization – Consolidate systems and harmonise data to eliminate inefficiencies and overhead, reduce latency, and optimise application performance, availability, and economics. Reduce maintenance costs and improve scalability by streamlining IT infrastructure. Accelerate data processing and respond to critical healthcare needs more quickly.

Healthcare integration is hard. InterSystems IRIS for Health is specifically designed to remove integration barriers and streamline development efforts. The platform supports a wide range of healthcare information protocols and standards. And InterSystems continuously updates the solution to keep pace with the evolving standards landscape.

InterSystems IRIS for Health reduces development cost and complexity, helping APs and SPs deliver value-added, data-driven applications and services, quickly and profitably. The versatile platform supports a wide array of uses and architectures, helping software companies and service providers expand markets, accelerate investment returns, and improve competitive differentiation.

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1- Data gravity describes the effect that as data accumulates, additional services and applications are attracted to the data. Ultimately, data becomes concentrated and too expensive to copy or move.