scholarly journals Development Semantically Interoperable PH Emergency Preparedness Data Exchange

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Nikolay Lipskiy ◽  
James Tyson ◽  
Jaqueline Burkholder
Keyword(s):  
Emergency Management ◽  
Emergency Preparedness ◽  
Information Exchange ◽  
Data Exchange ◽  
Situational Awareness ◽  
Content Standards ◽  
Data Interoperability ◽  
Data Set ◽  
Emergency Operations ◽  
Data Elements

Objective:The purpose of this project is to demonstrate progress in developing functional data models and semantic definitions (content standards) for data elements and value sets comprising information categories supporting PH Emergency Preparedness and Response. (EPR) The objective is to explain the concepts and methods used to define core PH Emergency Management and Preparedness and Response functions, Information Exchange Requirements (IERs), data elements, and value sets to create a PH Emergency Operations Center (EOC) Minimum Data Set Specification. The primary focus of this presentation is to describe the value of semantic data interoperability and provide operational examples of the value and return-on-investment gained through building semantically interoperable data exchange through content standardization. Introduction:Effective prevention, detection, and rapid response to PH emergencies rely on sufficient and timely delivered information. PH EOC data flows are based on critical information requirements, addressing needs of EOC staff for timely delivered analytical products that provide situational awareness, event-specific data, event investigation tools, resource management etc1. The ability of PH EOC systems to automatically and accurately interpret meaning of the exchanged data depends on a level of semantic data interoperability and utilization of a common information exchange reference model (CIERF) that conforms to established data standards. PH EOC data interoperability requires mutual development and close collaboration with partners to develop a PH EPR CIERF, common terminology and standardized vocabulary.Methods: The CDC’s Situational Awareness Branch (SAB) facilitates national activities on development PH EOC informatics through participation in the WHO EOC Network (EOC-NET) 2, and collaboration with national organizations and CDC partners on content standardization. The following sources were used for this analysis: 1) 26 content standards developed by national and international standard development organization, 2) WHO’s Framework for a Public Health Emergency Operations Centre2, and 3) PH EOC data requirements3 that were published by CDC’s SAB . These data requirements were included into the CDC Vocabulary and Access Distribution System (VADS) 4, which serves as the primary vocabulary content browser for PH EPR informatics.Results: In analyzing the PH EPR content standards, the CDC’s SAB arrived at the following results. The CDC EOC’s process of development and implementation content standards is based on the PH EOC critical information requirements. These requirement became business rules for the PH EPR CIERF.The current, version 2, of the PH EPR CIERF consists of 12 information modules including PH EOC minimum data set (MDS), patient clinical observations, emergency medical systems (EMS), data elements for emergency departments (DEEDS), WHO MDS for Health Workforce Registry, Resource Utilization Message Component (vocabulary for hospital resources), vocabulary for the national trauma standard. These PH EPR CIERF modules are interoperable and built on existing data standards. These modules were codified by VADS and ready for utilization by international and national PH EOC partners. At the stage of this analysis the PH EPR CIERF codification schema was prepared for adding it into the Logical Observation Identifiers Names and Codes (LOINC) content standard.The current PH EOC MDS version was released in September 2017. The common terminology and vocabulary that were included into this version are conformant with existing national and international content standards and specifications. Comparatively to the previous version 1, the current PH EOC MDS contains more than 60% new and updated terminology and value sets.Added to the PH EOC MDS version 2 new features are the Situational Analysis concept model, that also incorporates a nomenclature and structure for the Public Health EOC Situational Report (SITREP). Also, the Managing and Commanding conceptual model was updated by adding concepts and vocabulary for the agency internal communication, including standardized knowledge repository for managing standard operating procedures (SOP) and reports for leadership.The CDC’s SAB directly supports the CDC Surveillance Data Platform (SDP) and national organizations on development of electronic forms and form builders. These efforts will provide additional capabilities for collecting and electronically sharing standardized SA information utilizing web-enabled Services and mobile capabilities.Conclusions: CDC’s EOC and Division of Emergency Operations Staff is improving the application of emergency management and PH practice in preparing and responding to emergencies through partnerships and coordinated work with Standard Development Organizations (SDOs) to add critical EPR vocabularies to national and international standards. This work supports National Emergency Management Organizations and is a reference source for the WHO EOC-NET guiding documents supporting international efforts to strengthen Global Health Security.

scholarly journals Progress in the Development of the Standardized Public Health Emergency Preparedness Terminology

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Nikolay Lipskiy ◽  
James Tyson ◽  
Shauna Mettee Zarecki ◽  
Jacqueline Burkholder
Keyword(s):  
Public Health ◽  
Emergency Management ◽  
Emergency Preparedness ◽  
Data Exchange ◽  
Semantic Interoperability ◽  
Incident Management ◽  
Data Set ◽  
Emergency Operations ◽  
Support Organizations ◽  
Emergency Preparedness And Response

ObjectiveThe purpose of this project is to demonstrate the progress in development of a standardized public health (PH) emergency preparedness and response data ontology (terminology) through collaboration between the Centers for Disease Control and Prevention (CDC), Division of Emergency Operations (DEO), and the Logical Observation Identifiers Names and Codes (LOINC) system.IntroductionThe U.S. Department of Homeland Security National Incident Management System (NIMS) establishes a common framework and common terminology that allows diverse incident management and support organizations to work together across a wide variety of functions and hazard scenarios1. Using common terminology helps avoid confusion and enhances interoperability, particularly in fast-moving public health (PH) emergency responses. In addition, common terminology allows diverse incident management and support organizations to work together across a wide variety of functions and scenarios1. LOINC is one of a suite of designated standards for the electronic exchange of public health and clinical information. Implementation of LOINC facilitates improvement of semantic interoperability, including unified terminology2. More than 68,100 registered users from 172 countries use LOINC to move interoperable data seamlessly between systems3. The CDC Division of Emergency Operations (DEO) leads development of standardized PH emergency preparedness and response terminology to improve effective and interoperable communications between national and international partners. Realizing the scale of LOINC support and implementation across the global public health arena, CDC DEO collaborates with LOINC to further enhance and harmonize the current PH emergency response terminology and to attain critical PH emergency management and preparedness and response requirements.MethodsDEO analyzed 87,863 LOINC terms that were included in LOINC version 2.64, released on 06/15/20183. Access to this LOINC version was obtained through the Regenstrief LOINC Mapping Assistant (RELMA). RELMA is a Windows-based LOINC utility developed by the Regenstrief Institute (Indiapolis, USA) for searching the LOINC database and mapping local codes to LOINC codes4. The relevance of LOINC terminology to PH emergency preparedness and response was assessed through evaluating existing LOINC terminology against terminology specified by the World Health Organization PH Emergency Operation Centers (EOC). The following functions were evaluated: 1) Managing and Commanding; 2) Operating; 3) Planning/Intelligence; 4) Logistics and 5) Finance/Administration5. LOINC terminology was also evaluated against the CDC PH EOC Minimum Data Set (MDS)6 that contains 315 standardized terms. Analysis of fully specified LOINC terms was conducted through assessment of such LOINC term parts (attributes) as the code, name (component), system, method and class. Recommendations of gaps and enhancements were coordinated with LOINC management for inclusion of the new terminology in the release of version 2.65 .ResultsA new LOINC method, “CDC.EOC”, is under development. Currently, the “emergency management incident” terminology presented by LOINC is limited by such characteristics as event type, event location and event name and requires amplification regarding to PH operations (i.e., communication, logistics etc.).As a result of this investigation, emergency management terms are now being classified according to the type of incident or event (i.e., hurricane, outbreak, etc.) under LOINC code 80394-0. Similarly laboratory and clinical terms are being classified under a provisional LOINC code (89724-9). Two panels were created: 1) The emergency medical systems from the National Emergency Medical Services Information System (NEMSIS) was added under the NEMSIS.Panel (n= 177 terms) and 2) the Data Elements for Emergency Departments Systems (DEEDS) panel (n = 152 terms) was added with two subpanels: Attach.ED and Panel.ED.Assessing existing LOINC taxonomy and codification, DEO is working with the LOINC management team on evaluating additional options for reconciliation the PH emergency preparedness and response common information exchange reference model and LOINC standard. This process aims to further improve semantic interoperability of PH emergency preparedness and response information.ConclusionsThe LOINC terminology standardization is essential for improving PH preparedness and response data exchange and semantic interoperability. Collaboration with the Regenstrief Institute (LOINC) allows CDC to meet the terminology needs of PH emergency management and defines new opportunities for reconciliation data exchange between NIMS partners. This collaborative effort incorporates critically needed PH emergency and preparedness terminology and hierarchical structure in the LOINC standard.References1.FEMA National Incident Management System. Third Edition, October 2017. At: https://www.fema.gov/media-library-data/1508151197225-ced8c60378c3936adb92c1a3ee6f6564/FINAL_NIMS_2017.pdf2. US National Library of Medicine. Logical Observation Identifiers Names and Codes (LOINC). At: https://www.nlm.nih.gov/research/umls/loinc_main.html3. LOINC. The international standard for identifying health measurements, observations, and documents. At: https://loinc.org/4. RELMA-the Reginstrief Institute LOINC Mapping Assistant. At: https://loinc.org/relma/5.WHO. Framework for a Public Health Emergency Operations Centre. Interim document. November, 2015. At: http://www.who.int/ihr/publications/9789241565134_eng/en/6. CDC. Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). Minimum Data Set for PH Emergency Operations Center. At: https://phinvads.cdc.gov/vads/SearchVocab.action 

scholarly journals From OpenEHR to FHIR and OMOP Data Model for Microbiology Findings

2021 ◽  
Author(s):  
Eugenia Rinaldi ◽  
Sylvia Thun
Keyword(s):  
Infection Control ◽  
Data Model ◽  
Data Exchange ◽  
Control Group ◽  
Common Data Model ◽  
University Hospitals ◽  
Data Set ◽  
Related Data ◽  
National Initiative ◽  
Data Elements

HiGHmed is a German Consortium where eight University Hospitals have agreed to the cross-institutional data exchange through novel medical informatics solutions. The HiGHmed Use Case Infection Control group has modelled a set of infection-related data in the openEHR format. In order to establish interoperability with the other German Consortia belonging to the same national initiative, we mapped the openEHR information to the Fast Healthcare Interoperability Resources (FHIR) format recommended within the initiative. FHIR enables fast exchange of data thanks to the discrete and independent data elements into which information is organized. Furthermore, to explore the possibility of maximizing analysis capabilities for our data set, we subsequently mapped the FHIR elements to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). The OMOP data model is designed to support the conduct of research to identify and evaluate associations between interventions and outcomes caused by these interventions. Mapping across standard allows to exploit their peculiarities while establishing and/or maintaining interoperability. This article provides an overview of our experience in mapping infection control related data across three different standards openEHR, FHIR and OMOP CDM.

hData - A Simple XML Framework for Health Data Exchange

2009 ◽  
Author(s):  
Gerald Beuchelt ◽  
Harry Sleeper ◽  
Andrew Gregorowicz ◽  
Robert Dingwell
Keyword(s):  
Health Information ◽  
Information Exchange ◽  
Data Exchange ◽  
Health Information Exchange ◽  
Health Data ◽  
Care Providers ◽  
Future Health ◽  
Data Interoperability ◽  
History Of ◽  
Electronic Health

Health data interoperability issues limit the expected benefits of Electronic Health Record (EHR) systems. Ideally, the medical history of a patient is recorded in a set of digital continuity of care documents which are securely available to the patient and their care providers on demand. The history of electronic health data standards includes multiple standards organizations, differing goals, and ongoing efforts to reconcile the various specifications. Existing standards define a format that is too complex for exchanging health data effectively. We propose hData, a simple XML-based framework to describe health information. hData addresses the complexities of the current HL7 Clinical Document Architecture (CDA). hData is an XML design that can be completely validated by modern XML editors and is explicitly designed for extensibility to address future health information exchange needs. hData applies established best practices for XML document architectures to the health domain, thereby facilitating interoperability, increasing software developer productivity, and thus reducing the cost for creating and maintaining EHR technologies.

Feature Mapping Automation for CAD Data Exchange

2008 ◽  
Author(s):  
Leen Hanayneh ◽  
Yiwen Wang ◽  
Yan Wang ◽  
Jack C. Wileden ◽  
Khurshid A. Qureshi
Keyword(s):  
Information Integration ◽  
Information Exchange ◽  
Computer Aided Design ◽  
Data Exchange ◽  
Feature Model ◽  
Feature Mapping ◽  
Data Interoperability ◽  
Data Formats ◽  
Engineering Environment ◽  
Implicit And Explicit

Computer-aided design (CAD) data interoperability is one of the most important issues to enable information integration and sharing in a collaborative engineering environment. A significant amount of work has been done on the extension and standardization of neutral data formats in both academy and industry. In this paper, we present a feature mapping mechanism to allow for automatic feature information exchange. A hybrid semantic feature model is used to represent implicit and explicit features. A graph-based feature isomorphism algorithm is developed to support feature mapping between different CAD data formats.

scholarly journals EXTRACTION AND TRANSFORMATION OF IFC DATA TO CITYGML FORMAT

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 595-601 ◽  
Author(s):  
M. J. Sani ◽  
I. A. Musliman ◽  
A. Abdul Rahman
Keyword(s):  
Information Exchange ◽  
Data Exchange ◽  
Transformation Process ◽  
Information Modeling ◽  
Data Interoperability ◽  
Industry Foundation Classes ◽  
Gis Applications ◽  
Two Systems ◽  
Building Information ◽  
The Difference

Abstract. The integration of Geographic Information System (GIS) and the Building Information Modeling (BIM) referred to as the merging of the two systems for the purpose of data interoperability. The need to share information between the two systems is what motivated the integration process purposely for geospatial analysis. This can be achieved through their data exchange formats such as; City Markup Language (CityGML) and Industry Foundation Classes (IFC). The formats are the two most prominent key schemas of GIS and BIM systems respectively. The integration is a step towards information exchange or sharing (data interoperability) between the two systems. The selection of the two most prominent data exchange formats is as a result of their widespread applications in the GIS and BIM domains. However, the differences in geometric and the semantics information hinders data interoperability (information sharing) between GIS and BIM. Also, coupled with the difference in schema structure and the level of information richness between IFC and CityGML. This paper, propose a geometry transformation process that can be used to extract and transform IFC building objects to that of CityGML building objects to enable 3D model design and constructed using BIM tool to be easily reused in 3D GIS applications which will be able to support the CityGML model format. Where the geometric information will be extracted using the IFC tree-structure (hierarchy) and transformed to destination CityGML.

Social Media in Emergency Management

2021 ◽  
Author(s):  
Clayton Wukich
Keyword(s):  
Social Media ◽  
Emergency Management ◽  
Information Exchange ◽  
Science Communication ◽  
Situational Awareness ◽  
Academic Disciplines ◽  
The Public ◽  
Interactive Nature ◽  
Types Of Information ◽  
Media Applications

Social media applications such as Facebook and Twitter enable the rapid transmission of public warning messages in the event of a disaster. This augments traditional channels such as television and radio and may indeed save lives. The interactive nature of social media enables other types of information exchange beyond the one-way broadcast of warnings and guidance that has long characterized risk communication. Authorities monitor social media data for situational awareness, and they can solicit input from the public and engage in more deliberative conversations. In turn, the public initiates communication by asking questions, providing input, and requesting help. They expand the reach of official messages by sharing with friends and followers. Therefore, from an emergency management perspective, social media applications can disrupt the traditional one-way mode of communication and improve the efficacy of efforts to communicate risk. Research from across academic disciplines (e.g., computer science, communication, information systems, public administration, and sociology) illustrates: (a) the need for social media in emergency management; (b) the related benefits of use; and (c) the best practices used to attain those benefits. This offers a roadmap for authorities to effectively implement social media in their organizations while avoiding potential pitfalls.

scholarly journals OpenPharma Blockchain on FHIR: An Interoperable Solution for Read-Only Health Records Exchange through Blockchain and Biometrics

2020 ◽  
Author(s):  
Gracie Carter ◽  
Ben Chevellereau ◽  
Hossain Shahriar ◽  
Sweta Sneha
Keyword(s):  
Information Exchange ◽  
Data Exchange ◽  
Identity Management ◽  
The United States ◽  
Distributed Applications ◽  
Proof Of Concept ◽  
Data Interoperability ◽  
Health Records ◽  
Blockchain Technology ◽  
Share Data

The healthcare system in the United States is unique. From payor to provider, patients have the freedom of choice. This creates a complicated and profitable paradigm of care. Legislation defines government expectations of data exchange; however, the methods are left to the discretion of the stakeholders. Today, devices and programs are not built to unified standards, thus they do not share data easily. This communication between software is known as interoperability. We address the health data interoperability by leveraging Fast Health Interoperable Resource (FHIR) standard, a viewer of FHIR called OpenPharma, and Blockchain technology. Our proof of concept, called “OpenPharma Blockchain on FHIR” (OBF), is interoperable by design and grants clinicians access to patient records using a combination of data standards, distributed applications, patient-driven identity management, and the Ethereum blockchain. OBF is a trustless, secure, decentralized, and vendor-independent method for information exchange. It is easy to implement and places the control of records with the patients.

scholarly journals Towards a Newborn Screening Common Data Model: The Utah Newborn Screening Data Model

2021 ◽  
Vol 7 (4) ◽  
pp. 70
Author(s):  
David Jones ◽  
Jianyin Shao ◽  
Heidi Wallis ◽  
Cody Johansen ◽  
Kim Hart ◽  
...  
Keyword(s):  
Newborn Screening ◽  
Data Model ◽  
Data Exchange ◽  
Healthcare Providers ◽  
Common Data Model ◽  
Snomed Ct ◽  
Electronic Data ◽  
Data Interoperability ◽  
Screening Programs ◽  
Data Elements

As newborn screening programs transition from paper-based data exchange toward automated, electronic methods, significant data exchange challenges must be overcome. This article outlines a data model that maps newborn screening data elements associated with patient demographic information, birthing facilities, laboratories, result reporting, and follow-up care to the LOINC, SNOMED CT, ICD-10-CM, and HL7 healthcare standards. The described framework lays the foundation for the implementation of standardized electronic data exchange across newborn screening programs, leading to greater data interoperability. The use of this model can accelerate the implementation of electronic data exchange between healthcare providers and newborn screening programs, which would ultimately improve health outcomes for all newborns and standardize data exchange across programs.

Emergency preparedness collaboration on Twitter

2018 ◽  
Vol 16 (3) ◽  
pp. 191 ◽  
Author(s):  
DeeDee Bennett, PhD
Keyword(s):  
Social Media ◽  
Public Education ◽  
Emergency Management ◽  
Emergency Preparedness ◽  
Large Scale ◽  
Emergency Operations ◽  
Governmental Agencies ◽  
Intergovernmental Collaboration ◽  
Social Media Platforms ◽  
Use Of Social Media

Agency collaboration is an important function in the management of disasters and catastrophes. For effective emergency management, the need for intergovernmental collaboration grows as the scale of the disaster increases. Several researchers have examined the use of social media by emergency management (and other governmental agencies) during large-scale disasters; however, few have examined the use of social media for intergovernmental collaboration. This study explores the use of social media platforms as a means to establish and maintain intergovernmental collaboration for emergency management-related agencies. More salient is the focus on social media during the preparedness and planning stages of emergency management. Using qualitative observational and coding analysis, this study identifies the types of connections made by topic, level of governance, and established affiliation in the local emergency operations plan (LEOP). The findings show that more than 50 percent of the connections made were established on Twitter and not present in the current LEOP. Furthermore, the most popular topic to initiate online connections was related to public education information. The findings from this study can assist emergency management practitioners in developing social media strategies, which incorporate methods to connect with other agencies on Twitter.

scholarly journals Rules and validation processes for interoperable BIM data exchange

2020 ◽  
Author(s):  
Yong-Cheol Lee ◽  
Charles M Eastman ◽  
Wawan Solihin
Keyword(s):  
Information Exchange ◽  
Data Exchange ◽  
Detailed Examination ◽  
Facility Management ◽  
Information Modeling ◽  
Data Mapping ◽  
Data Validation ◽  
Data Interoperability ◽  
Building Information ◽  
Challenging Situation

Abstract Diverse industries have recognized the significance of a neutral data standard for seamless building information modeling (BIM) data exchanges and adopted commonly agreed schemes such as the industry foundation classes (IFC) schema for enhancing BIM data interoperability. To selectively employ domain-specific data exchange requirements, the AEC-FM (the Architecture, Engineering, Construction, and Facility Management) industries have developed their own schema with a subset of the IFC schema, named a model view definition (MVD). However, because of latent human errors, inadequate MVD definitions, and error-prone data mapping problems, the adoption of IFC for exchanging and sharing BIM data is frequently limited with severe data integrity issues. This challenging situation requires the detailed examination of the limitations of the heterogeneous IFC translation processes of the current BIM authoring and application tools. To accomplish this objective, the authors thoroughly investigated the two MVDs, the Coordination View Version 2.0 and the Construction Operations Building Information Exchange, broadly used as an international standard for developing the IFC translation processes, and then identified their intrinsic requirements/rules and developed rule-based data validation processes. These new intrinsic knowledge of the two MVD specifications will be fundamental foundations to create coherent BIM data exchange systems that are currently scattered and dispersed in heterogeneous IFC translation processes and structures. Newly revealed rules pertaining to these two MVDs have been executed with IfcDoc, which is the IFC documentation tool. This BIM data validation process is expected to not only accurately evaluate the translation processes between BIM native data and IFC ones but also help industry professionals ensure the integrity and the accuracy of their BIM data according to the BIM data exchange standards using the two MVDs. In addition, the outcomes of this research study are expected to bolster the interoperable BIM adoption and offer the values of greater consistency of BIM data exchange.

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