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Automation in Health Care
Published in Edward Y. Uechi, Business Automation and Its Effect on the Labor Force, 2023
Two international standards were established to ensure that health-related data can be read and interpreted by diverse organizations and systems. The World Health Organization (WHO) oversees development and adoption of the International Statistical Classification of Diseases and Related Health Problems (ICD) to provide systematic recording of mortality, morbidity, diseases, and other health-related data. This standard ensures interoperability and reusability of health data. As of 1 January 2022, the 11th revision (ICD-11) replaces the 10th revision (ICD-10). Health Level Seven International (HL7), a non-profit organization, established a framework and standards for the language, structure, and data types of health-related data to ensure that electronic health records can be integrated in different health information systems.
Informatics as a Pathway for Integrating Radiation Oncology into Modern Medicine
Published in Siyong Kim, John Wong, Advanced and Emerging Technologies in Radiation Oncology Physics, 2018
Mark H. Phillips, Wade P. Smith, Kristi R. G. Hendrickson, Alan M. Kalet
Health level seven (HL7) is a standards-developing organization “dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of electronic health information.” The standards have evolved since their beginning in 1987; version 2 is the most widely implemented and version 3 is the latest. The differences between the two versions reflect two different approaches to defining standards: namely, “bottom up” versus “top down.” V2.x series standards have been widely implemented because low-level data elements and concepts are well-defined. This approach is very flexible, but it runs into problems when trying to communicate higher-level constructs. Detailed negotiations are necessary between the two communicating partners, and the result is unlikely to be understood outside that relationship. This also makes it difficult to support reliable conformance testing. V3 uses a reference information model (RIM) as its top-level model, from which all other aspects of the standard flow. The RIM model consists of four primary subject areas (“Entity,” “Role,” “Participation,” “Acts”) and 35 classes (http://www.hl7.org/implement/standards/product_brief.cfm?product_id=186, accessed April 20, 2017). For a given healthcare domain, an HL7 version 3 specification is based on the RIM—a common and underlying modeling framework—and includes artifacts such as: Use Case Models, Information Models, Interaction Models, Message Models, and Implementable Message Specifications (https://msdn.microsoft.com/en-us/library/ms954603.aspx, accessed April 20, 2017).
Telemedicine Technology
Published in Rajarshi Gupta, Dwaipayan Biswas, Health Monitoring Systems, 2019
Health Level Seven International (HL7), one of several ANSI-certified standards operating in the healthcare arena, aims at providing standards for the exchange, management, and integration of data related to healthcare services. It aims at facilitating clinical patient care and the management, delivery, and evaluation of healthcare services. HL7 focusses on the interface requirements of the entire healthcare organization. It tries to model different events that take place in healthcare services. Consider an event of a patient’s admission to a hospital. The Patient Administration System (PAS) logs the details about demographics of the patient, and the admission, such as the name of admitting doctor, ward of admission, financial transactions, etc. Several other systems in the hospital, such as pathology laboratory information system or pharmacy system, will require these details at certain stages of care and services. Hence, this event in PAS may trigger forwarding of a message to each of the interested systems about the patient. Otherwise, those systems may wait until the patient needs their service. In any case, the PAS requires to communicate information about a patient to these systems. Before the introduction of HL7, developers of various information systems that needed to communicate had to discuss among themselves and work out a mutually acceptable common format for information exchange for developing interfaces. This is not only an expensive process, but it is also very time consuming. HL7 provides a common language for all health/medical information systems for exchanging and sharing of information. Developers need to make their systems HL7 compliant to connect to other systems through requests and responses to queries.
Distributed electronic health record based on semantic interoperability using fuzzy ontology: a survey
Published in International Journal of Computers and Applications, 2018
Ebtsam Adel, Shaker El-Sappagh, Sherif Barakat, Mohammed Elmogy
HL7 is an American National Standards Institute ‘ANSI’ accredited standards protocol for exchanging the electronic data in the environments of healthcare. It and its group members are considered the most commonly used in the world. These standards focus on the seventh level in Open System Interconnection ‘OSI’ model ‘Application layer.’ HL7 can improve care delivery, reduce ambiguity, optimize workflow, and perfect transferring of the knowledge between all of the stakeholders [26]. HL7 CDA (Clinical Document Architecture) is one of the HL7 members. It’s used for transferring rich, detailed, and unambiguous clinical documents over the barriers of different software applications and islands. It can include text, sounds, images, and many other multimedia contents [20].
Aided innovative design of bathroom products based on artificial intelligence technology
Published in Journal of Control and Decision, 2023
In the framework of AI-aided product design, the needs of design users are defined and decomposed in the semantic database. The mapping mechanism in the design ontology corresponds to the design elements. Ontology Mapping is the technique of articulating commonalities between ideas from different origin Ontologies. By connectivity and interaction, ontological mappings allow information analysis. Connecting ontologies together broadens accessibility over huge areas including illness. Decaying an impact of concern into its development orientation and examining how all those stages interplay with the environment is referred to as mechanism mapping, a policy research approach. The translation method enables the standard HL-7 mappings to be changed to a specialised area. The methodology also enables us to perform translations within the same section and also across sections. The smallest number of iterations is used when mapping occurs in repeated variables. Health Level Seven, abbreviated as HL7, is a collection of ensuring conformity for the exchange of medical and management information across computer programmes utilised by health professionals and patients. These specifications are concerned with the server-side, which would be designated as ‘layer 7’ at the OSI level. The system extracts the corresponding design elements from the database and integrates them according to the innovation principle and the calculation results of relevant large data, output the preliminary design scheme, then adjusts the design scheme through an expert consultation system, continuously optimise and iterate, and finally output one or more schemes, as shown in Figure 3 (Bianchi et al., 2019; Gao & Bhagi, 2021; Gayathri et al., 2020; Kobayashi & Takeda, 2020; Somjai et al., 2020; Wang et al., 2020; Wang & Arora, 2021; Yang, 2020). Initially, the customer’s demand has to be known for designing the smart bathroom as a prototype model. Then element database has been designed with the help of an expert consultation system. Further, develop the innovation method for obtaining the outcome.
A cloud-based platform for the non-invasive management of coronary artery disease
Published in Enterprise Information Systems, 2020
Antonis Sakellarios, Joao Correia, Savvas Kyriakidis, Elena Georga, Nikolaos Tachos, Panagiotis Siogkas, Francisco Sans, Paolo Stofella, Valiani Massimiliano, Alberto Clemente, Silvia Rocchiccioli, Gualtiero Pelosi, Nenad Filipovic, Dimitrios I. Fotiadis
The design and the development of the platform were based on European and International standards to guarantee the privacy of any sensitive data handling, in particular the EU General Data Protection Regulation (GDPR).2 In order to acquire data from diverse data sources, the system provides a specific HL7 compliant integration layer using clinical data semantics. The HL7 integration layer is developed using HAPI (HL7 application programming interface). The IHE Cross-Enterprise Document Sharing (XDS) Integration Profile was adopted to facilitate the registration, distribution and access across health enterprises of patient electronic health data. In any single Hospital, the HIS (Hospital Information System) provides the enterprise specific patient ID as well as the historical demographic data. Clinical data are shared between different CISs (clinical information system) using the HL7 communication standard and following the IHE communication patterns to avoid errors and the manual data entry. For the Patient, Medical Records the CDA Release 2 HL7 Standard (Clinical Reports) was used following the IHE Cardiology Technical Framework (Volume 1 (CARD TF-1): Integration Profiles and Volume 2 (CARD TF-2)). For the genomics data exchange, we adhere to HL7 IG CG_GENO, R1 Version 3 Genotype, Release1 – January 2009, HL7 IG LOINCGENVA, R1 Version 2 Implementation Guide: Clinical Genomics; Fully LOINC-Qualified Genetic Variation Model, Release 1. On the side of IHE integration frameworks, SMARTool adheres to the following IHE frameworks for the documents workflow: IHE Cross-Enterprise Document Workflow (XDW) Rev. 2.2–31 August 2012; IHE IT Infrastructure Technical Framework Volume 1 (ITI TF-1) Integration Profiles Revision 9.0-Final Text - A–gust 31, 2012; Cross-Enterprise Document Media Interchange (XDM), Cross-Enterprise Document Reliable Interchange (XDR), Cross-Enterprise Document Sharing (XDS.b), Cross-Enterprise Sharing of Scanned Documents (XDS-SD); IHE Anatomic Pathology Technical Framework Supplement-Anatomic Pathology Structured Reports (APSR)-Trial Implementation- 31 March 2011; IHE Laboratory (LAB) Technical Framework Volume 1 (LAB TF-1)-Integration Profiles - Revision 4.0-Final Text 2 October 2012. For the medical images, the DICOM standard is followed. For the refined models, the standard ML format is used and specifically the Markup Language (ML) format for the multiscale and multilevel model and the Personalised Print Markup Language (PMML) format for the data mining and statistical stratification models. The abovementioned standards ensure the interoperability and the required security in information exchange.