Global Healthcare Data Interoperability market size is expected to reach $13.36 billion by 2029 at 16.2%, segmented as by centralized, single point of control, unified data repository, centralized management and storage

Health Data Interoperability Market size to be valued at USD 84.58 Bn in 2025 and is expected to expand at a CAGR of 22.65%, reaching USD 352.13 Bn by 2032.

As described in the associated manuscript, two tests were run to evaluate interoperability in life cycle assessment (LCA) elementary flow (EF) lists. The first looks at various LCA sources and analyzed how interoperable the original source EF lists are by comparing unique name-to-name matches across sources. The second analysis compares sources that are mapped to the Federal Elementary Flow List (FEDEFL) as a common source list and measures the improvement in interoperability in the increase of flows that are mapped between sources. These analysis were performed in this dataset. This dataset is associated with the following publication: Edelen, A.N., S. Cashman, B. Young, and W.W. Ingwersen. Life Cycle Data Interoperability Improvements through Implementation of the Federal LCA Commons Elementary Flow List. Applied Sciences. MDPI, Basel, SWITZERLAND, 12(19): 9687, (2022).

These datasets contain C-V2X network communication and interoperability testing packet data collected using a network sniffer (Wireshark) in the Packet Capture (PCAP) format and converted into the Packet Description Markup Language (PDML) format. These datasets include three testcases: C-V2I, C-V2V, and C-V2X. These datasets can be used to display, analyze, and assess C-V2X compatibility and interoperability among commercial on-board units (OBUs) and road-side units (RSUs) based on IEEE 1609.2, IEEE 1609.3, and SAE J2735 standards.

[197+ Pages Report] Global healthcare data interoperability market report published by Facts & Factors, estimated that the market is expected to reach USD 4.5 Billion by 2026 with a growth rate of 12.9% CAGR during 2021-2026.

Global Healthcare Data Interoperability is segmented by Application (EMRs, Lab Systems, Payer Platforms, Health Exchanges, Research Institutions), Type (Semantic Interoperability, Structural Interoperability, Foundational Interoperability, Patient-Matching, API-Driven Platforms) and Geography(North America, LATAM, West Europe, Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA)

The global healthcare data interoperability market, worth USD 3.99 billion in 2024, is expected to surpass USD 15.04 billion by 2034, with a CAGR of 14.2% from 2025 to 2034.

The goal of the OneNet System is to facilitate data exchanges among existing platforms, services, applications, and devices by the power of interoperability techniques. To ensure that system requirements are technically -implementable and widely adopted, internationally standardized file formats, metadata, vocabularies and identifiers - are required.

The OneNet “Cross-Platform Access” pattern is the fundamental characteristic of an interoperable ecosystem, leading to the definition of the exposed list OneNet Cross-Platform services (CPS). The pattern entails that an application accesses services or resources (information or functions) from multiple platforms through the same interface. For example, a “grid monitoring” application gathers information on different grid indicators provided by different platforms that conduct measurements or state estimations. The challenge of realizing this pattern lies in allowing applications or services within one platform to interact with other platforms (eventually from different providers) with relevant services or applications via the same interface and data formats. Thereby, reuse and composition of services as well as easy integration of data from different platforms are enabled.

Based on the defined concept for CPS, an extensive analysis has been performed regarding data exchange patterns and roles involved for system use cases (SUCs) from other H2020 projects and the OneNet demo clusters. This has resulted into a first list of CPS, that has been thereafter taxonomized into 10 categories. The different entries have been defined providing a set of classes such as service description, indicative data producer/consumer etc. Each CPS can be assigned with multiple business objects describing the context of it. For a specific set of widely used by the Demo CPS, there have been formal semantic definitions provided in the "CrossPlatformServices-Semantic" excel worksheet.

To achieve true data interoperability is to eliminate format and data model barriers, allowing you to seamlessly access, convert, and model any data, independent of format. The ArcGIS Data Interoperability extension is based on the powerful data transformation capabilities of the Feature Manipulation Engine (FME), giving you the data you want, when and where you want it.In this course, you will learn how to leverage the ArcGIS Data Interoperability extension within ArcCatalog and ArcMap, enabling you to directly read, translate, and transform spatial data according to your independent needs. In addition to components that allow you to work openly with a multitude of formats, the extension also provides a complex data model solution with a level of control that would otherwise require custom software.After completing this course, you will be able to:Recognize when you need to use the Data Interoperability tool to view or edit your data.Choose and apply the correct method of reading data with the Data Interoperability tool in ArcCatalog and ArcMap.Choose the correct Data Interoperability tool and be able to use it to convert your data between formats.Edit a data model, or schema, using the Spatial ETL tool.Perform any desired transformations on your data's attributes and geometry using the Spatial ETL tool.Verify your data transformations before, after, and during a translation by inspecting your data.Apply best practices when creating a workflow using the Data Interoperability extension.

The radical interoperability market is experiencing robust growth, driven by the increasing need for seamless data exchange across healthcare systems. The market's expansion is fueled by several key factors: rising adoption of cloud-based solutions that facilitate interoperability, growing regulatory pressures mandating data sharing, and the increasing demand for patient-centric care models that rely heavily on integrated health information. The substantial investments made by major technology players like Allscripts, Cerner, and Epic, along with emerging players like Orion Health and NextGen, further accelerate market expansion. This competitive landscape fosters innovation and drives the development of sophisticated interoperability solutions, including advanced APIs, semantic interoperability tools, and robust data security protocols. We estimate the market size in 2025 to be around $5 billion, considering the rapid advancements and widespread adoption of interoperability solutions globally. A compound annual growth rate (CAGR) of 15% is projected from 2025 to 2033, indicating significant growth potential. However, challenges remain. Data security and privacy concerns are paramount, requiring stringent compliance with regulations like HIPAA. The complexity of integrating legacy systems with newer technologies poses a significant hurdle for many healthcare providers. Furthermore, interoperability requires significant financial investments in infrastructure upgrades and skilled workforce training, potentially hindering adoption among smaller healthcare organizations. Despite these challenges, the long-term outlook for radical interoperability remains positive, driven by evolving healthcare delivery models, the push towards value-based care, and the increasing awareness of the importance of data sharing for improving patient outcomes. The market is expected to reach approximately $15 billion by 2033, demonstrating a substantial increase and solidifying the vital role of radical interoperability in the future of healthcare.

In February 2019 the Networking and Information Technology Research and Development (NITRD) Program's Health Information Technology Research and Development Interagency Working Group (HITRD IWG) issued a Request for Information (RFI) to collect input from industry, academia, and nongovernmental organizations on new approaches to solve the interoperability issues between medical devices, data, and platforms. On July 17, 2019, the group followed up with an in-person Listening Session that included 76 representatives from the device, standards, academic, and medical communities, and government. This report is a summary of the February 2019 Request for Information and July 2019 Listening Session.

Interoperability within the agricultural implements industry is part of interconnected public policy issues that have arisen because of new market dynamics created by digital technologies. Western Canadian implement manufacturers have identified a major business challenge from the accelerated lock down of software on combines and tractors, which make implement brands incompatible, or inoperable, with original equipment manufacturers' systems. This report looks at the economic significance of agricultural manufacturing in western Canada with additional insight from industry on the effects of a single change to interoperability on agriculture machinery.

Table contains four types of statements identified in the text of the GDPR that determine or influence the interoperability of information between entities. The first type of statement reflects a requirement for the interoperability and is abbreviated as REQ. Entities are expected to follow or fulfill this requirement for compliance. GDPR only states but does not stipulate how a requirement should be fulfilled. Where an activity or action is presented in the statement, these are identified as processes related to usage, sharing, publication, or exchange of information, and are annotated as PROC in the table. Where information is categorically mentioned or as information consisting of some form or category, the abbreviation DATA is used to identify such statements in the table. Where additional information about category or type of data is specified, this is annotated with FORMAT, with the statement either specifying an explicit data format or providing guidelines governing the choice of formats which are acceptable or need to be enforced.

The global healthcare interoperability solutions market is experiencing robust growth, driven by the increasing need for seamless data exchange among healthcare providers, payers, and patients. The market's expansion is fueled by several key factors, including the rising adoption of electronic health records (EHRs), the growing emphasis on value-based care, and the increasing prevalence of chronic diseases demanding coordinated care. Government regulations mandating interoperability, such as the 21st Century Cures Act in the US, are further accelerating market adoption. Key players like Allscripts Healthcare, Infor, Interfaceware, InterSystems, Koninklijke Philips, Oracle, and Orion Health are actively developing and deploying innovative solutions to address the diverse needs of the healthcare ecosystem. Competition is fierce, with companies focusing on providing comprehensive platforms that integrate various data sources, offer robust security features, and support a wide range of interoperability standards like FHIR and HL7. The market is segmented by solution type (e.g., cloud-based, on-premise), deployment model, and end-user (hospitals, clinics, pharmacies). Looking ahead, the market is projected to maintain a healthy Compound Annual Growth Rate (CAGR) over the forecast period (2025-2033). Technological advancements, such as the increasing use of artificial intelligence (AI) and machine learning (ML) in healthcare data analytics, are expected to further enhance the capabilities of interoperability solutions. However, challenges remain, including concerns around data security and privacy, the complexity of integrating diverse systems, and the high initial investment costs. Overcoming these hurdles will be crucial for sustained market growth. The focus is shifting towards solutions that prioritize data standardization, robust security protocols, and seamless integration with existing healthcare IT infrastructure. This evolving landscape necessitates ongoing innovation and strategic partnerships to meet the increasing demand for effective and secure healthcare data interoperability.

The Healthcare Interoperability Solutions Market Report is Segmented by Component (Software, Services, Platforms/Middleware), Interoperability Level (Foundational, Structural, Semantic, Organizational), Deployment Mode (On-Premise, and More), End User (Hospitals & Health Systems, Ambulatory & Specialty Clinics, and More), and Geography (North America, Europe, and More). The Market Forecasts are Provided in Terms of Value (USD).

The Healthcare Data Interoperability market report offers a thorough competitive analysis, mapping key players’ strategies, market share, and business models. It provides insights into competitor dynamics, helping companies align their strategies with the current market landscape and future trends.

ObjectiveNational interoperability is an agenda that has gained momentum in health care. Although several attempts to reach national interoperability, an alerting system through interconnected network of Health Information Exchange (HIE) organizations, Patient-Centered Data Home (PCDH), has seen preliminary success. The aim was to characterize the PCDH initiative through the Indiana Health Information Exchange's participation in the Heartland Region Pilot, which includes HIEs in Indiana, Ohio, Michigan, Kentucky, and Tennessee.Materials and MethodsAdmission, Discharge, and Transfer (ADT) transactions were collected between December 2016 and December 2017 among the seven HIEs in the Heartland Region. ADTs were parsed and summarized. Overlap analyses and patient matching software were used to characterize the PCDH patients. R software and Microsoft Excel were used to populate descriptive statistics and visualization.ResultsApproximately 1.5 million ADT transactions were captured. Majority of patients were female, ages 56–75 years, and were outpatient visits. Top noted reasons for visit were labs, screening, and abdominal pain. Based on the overlap analysis, Eastern Tennessee HIE was the only HIE with no duplicate service areas. An estimated 80 percent of the records were able to be matched with other records.DiscussionThe high volume of exchange in the Heartland Region Pilot established that PCDH is practical and feasible to exchange data. PCDH has the posture to build better comprehensive medical histories and continuity of care in real time.ConclusionThe value of the data gained extends beyond clinical practitioners to public health workforce for improved interventions, increased surveillance, and greater awareness of gaps in health for needs assessments. This existing interconnection of HIEs has an opportunity to be a sustainable path toward national interoperability.

This dataset is associated with the manuscript "Translating nanoEHS data using EPA NaKnowBase and the Resource Description Framework" mortensen h, Williams A, Beach B, Slaughter W, Senn J and Boyes W submitted 8/3/2023 to F1000:Nanotoxicology. The dataset includes and RDF mapping of EPA NaKnowBase (NKB), the OntoSearcher code used to produce the file NKB RDF, as well as training materials and example files for the user. Portions of this dataset are inaccessible because: this data includes partner data and old code that has been modified since 2021. They can be accessed through the following means: OntoSearcher_Training_Materials.zip. Format: The file entitled "OntoSearcher_Training_Materials.zip" includes updated materials as of 07/11/23. These files include the Ontosearcher tool materials, sample NKB dataset and corresponding training documentation on how to run the tool with the sample dataset, and apply to the users own data. This directory also includes the current RDF mapping of the NKB (NKB_RDF_V3.ttl).

The Interoperability Proving Ground (IPG) is an open, community platform where you can share, learn, and be inspired by interoperability projects occurring in the United States (and around the world).

Yearly citation counts for the publication titled "Enabling data interoperability for federated IoT experimentation infrastructures".