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Data standardization and informatics in radiation oncology
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
The terminology of LOINC (https://loinc.org/), created by Dr. Clem McDonald working with the Regenstrief Institute, is an open-access system that can be used in EHRs to identify tests and observations. LOINC entries define 18 elements, including distinct numeric and short letter codes for laboratory values and observations and specific conditions of their measurement. For example, albumin measured in urine in units of mass per unit volume has a numerical code of 1754-1 and a letter code of Albumin Ur-mCnc. Albumin in serum or plasma has numeric and letter codes of 1751-7 and Albumin SerPl-mCnc. With the various distinctions, more than 56 entries list albumin as the sole component and 216 reference albumin as part of the component or measurement.
Patient Report Analysis for Identification and Diagnosis of Disease
Published in Rashmi Agrawal, Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore, Dac-Nhuong Le, Machine Learning for Healthcare, 2020
Muralidharan C., Mohamed Sirajudeen Y., Anitha R.
Logical Observation Identifiers Names and Codes (LOINC) is a universal and database standard developed for identifying the medical laboratory reports. Health Level 7 is an international standard for transferring administrative and clinical data between the application which are used by various medical providers. The Fast Healthcare Interoperability Resources (FHIR), is a drafting standard for elements, data formats, and API for exchanging the medical data.
Telemedicine Technology
Published in Rajarshi Gupta, Dwaipayan Biswas, Health Monitoring Systems, 2019
Medical informatics primarily focusses on representation and computation on medical and health information. These are needed for design and development of a medical information system providing healthcare services and business. Different international standards have been evolved for exchange and management of information related to these areas. These standards are developed so that the systems designed by different organizations and running on different platforms could be made interoperable. Let us consider a few example cases. If a hospital requires to send information and a query regarding a patient to another referral hospital, the systems at both ends should have a protocol for exchange of information. In another situation, for getting payment from an insurance company, the hospital may require to send relevant information of their services and their charges to them. All these different types of information related to healthcare services should be sent in a format following a standard of data representation. For exchanging messages and queries among multiple information systems operating independently, there should be a common language and a common format for representing patients’ data. Two such standards are very widely used in medical business world, namely HL7, which is a messaging protocol specifically developed to exchange health/medical/patient information between information systems, and the other standard, DICOM, which is used for representing medical images, waveforms, etc. and exchange of information in radiological imaging systems such as Picture Archiving and Communication System (PACS). There are also other types of health standards, which focus on requirements of a particular department or domain. For example, International Statistical Classification of Diseases and Related Health Problems (ICD9, and ICD10) are meant for identifying and classifying diseases. The standard Logical Observation Identifiers Names and Codes (LOINC) is used for denoting laboratory observations, health measurements, observations, and documents. Another standard Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) targets at defining multilingual vocabulary of clinical terms.
Quality medical data management within an open AI architecture – cancer patients case
Published in Connection Science, 2023
Mirjana Ivanovic, Serge Autexier, Miltiadis Kokkonidis, Johannes Rust
To process and use for different purposes rich patients’ health records, various health terminologies and ontologies have been used to achieve great level of standardisation and unification of data representations. A health terminology represents a kind of “language” used to code entries in EHRs and other medical and health data and there are a range of them: various International Classification of Diseases, ICD-9, ICD-10, IDC-11, LOINC, CPT, SNOMED CT, and so on (Link 4). Such terminologies are important for obtaining interoperability between systems and for integrating data; exchange of data between systems as codes from different systems have to be compatible; and are standards for obtaining mapping of various vocabularies and smooth “communication” between independent medical and health systems.