Semantic interoperability is achieved by using
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Semantic interoperability, or the "ability to use electronic health information across diverse medical records systems that use different words to say the same thing", makes healthcare data analytics possible. Show If we look across different health computer systems that are used by HIE-participating healthcare providers, we will see different ways of saying the same thing (Each doctor has his/her own way when it comes to documenting observations using free text or using local codes in the health system s/he is using). Take radiology procedures for example. The local system codes (e.g. XRSC3V, 123456) and names (e.g. XR SC Joints 3V, Sternoclavicular Joints 3 Views) are different for the same exam across sites. Another example, a health professional would easily understand that “Tylenol” and “Acetaminophen” are generally used interchangeably. However, two computer systems exchanging those phrases may treat the terms entirely differently. If two systems do not agree the terms are synonyms, then data passing through them will not be equally interpreted, and therefore this will affect the possibility of aggregation of integrated data while aggregating data from multiple systems across independent healthcare organizations is crucial for research, which can lead to improved clinical guidelines and practices. The way to overcome this variation in order to 1) ensure the medical system's ability to exchange electronic health information with and use electronic health information from other systems without special effort on the part of the user and to 2) achieve the possibility of aggregation of integrated data is to bind the EMR/EHR system local terminologies (local codes or free text medical description) to a standardized vocabulary or terminology. Data standards are the principal informatics component necessary for information flow through the national health information infrastructure. Data standards term encompasses methods, protocols, terminologies, and specifications for the collection, exchange, storage, and retrieval of information associated with health care applications, including medical records, medications, radiological images, payment and reimbursement, medical devices and monitoring systems, and administrative processes. Standardizing health care data involves the following: - Definition of data elements: Determination of the data content to be collected and exchanged. (Example of data elements: patient name, gender, ethnicity, diagnosis, primary care provider, laboratory results, date of each encounter, etc.) - Data exchange formats: Standard formats for electronically encoding/structuring the data elements as they are exchanged (Example of messaging format standards: HL7, DICOM, etc.) - Terminologies: Medical terms (Medical Codes List) used to code and describe the data elements and expression (data elements and expression should be mapped/translated to standard codes. Distinct expressions that mean the same thing will be mapped to one standard code) (Example of terminology standards: SNOMED-CT, LOINC, RxNorm, ICD, CPT, etc. At its simplest, a SNOMED, for example, is a coded vocabulary of medical concepts and expressions used in healthcare. It is designed to provide the terminology needed to code the entire medical record.) - Knowledge Representation: Databases holding medical knowledge to support decisions (Example of knowledge bases: disease registries, drug-body interactions bases, etc.) Terminology standards will provide an unambiguous, machine-readable meaning of specific terms and messaging standards permitting the electronic exchange of information in a consistent manner. Together, they will allow the interoperable use and exchange of healthcare information. Natural language is huge and very rich in details but at the same time is ambiguous; it has great dependence on context and uses jargon and acronyms. Healthcare Information Systems should capture clinical data in a structured and preferably coded format. This is crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions, etc. In order to address this point, numerous terminological/coding systems for the systematic recording of clinical data have been developed. These systems interrelate concepts of a particular domain and provide reference to related terms and possible definitions and codes. The purpose of terminology services consists of representing facts that happen in the real world through database management (use of dictionaries of medical terms, definitions and codes + structuring data elements). This process is named Semantic Interoperability. It implies that different systems understand the information they are processing through the use of codes of clinical terminologies. Standard terminologies allow controlling medical vocabulary. Several vocabulary and terminology standards have been developed. These include but are not limited to: - Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) for problems or conditions; - RxNorm for medications and medication allergies; - Logical Observation Identifiers Names and Codes (LOINC) for laboratory tests, vital signs and cancer case reporting; and - CVX for immunizations. An important barrier to electronic healthcare information exchanges (HIE) is the lack of interoperability between information systems especially on the semantic level. For this reason, data standards and protocols should be established/implemented by government/industry and the heterogeneous EHRs participating in HIE should collaborate by capturing data in a structured and coded format (mapping medical terms to standard codes system (SNOMED or ICD or etc.)/i.e EHRs should be compatible with standards) to make the data passing through different systems equally interpreted without additional effort. To represent the medical data using a certain codes system (SNOMED or LOINC), the need to a standard codification system (SCS) arise. (SCS is a system software (encoder) that helps human assign codes to the medical data but usually these systems are slow and not complete and this process will require human verification) Another approach to codify medical data is the use of semantic interoperability platform at the level of HIE infrastructure. In this way the use of local medical expressions/terminologies by end users in their EHRs/EMRs will be preserved (less common than the first approach mentioned in the preceding paragraph) ** ** ** ** ** ** ** ** ** ** ** Some relevant sayings... - A treasure trove of information sits in hospitals all over the country; it’s value lies in its use. - Perfect decisions can only be made with perfect information. - Healthcare software systems have traditionally «spoken» different languages, making difficult (and in many cases impossible) to communicate and interact between them. In order to make these systems to exchange information as fluidly as possible, it is necessary to adopt standards. - Semantic interoperability is the “ability to automatically interpret the information exchanged meaningfully and accurately in order to produce useful results as defined by the end users of both systems.” - Interoperability is necessary for health system in which health information flows seamlessly and is available to the right people, at the right place, at the right time. - The need for standardized terminologies and data standards in healthcare has long been recognized. The growing urgency to share electronic health records and the establishment of health information exchanges will continue to escalate the need. If the data standards can be determined and enforced, interoperability will become a reality much quicker. - If patients are to receive the most efficient and effective care possible, HIE must become the way of doing business in health care settings. And if HIE is to be possible in the digital age of medicine, EHR systems must be defined by their interoperability. - Codified Data is EHR data with each finding assigned a standard code assures uniformity of the medical records and facilitates communication between multiple systems. - Operating a health information exchange has many challenges, but one of the most under-appreciated is the difficulty of managing ever-changing source system vocabularies and their mappings to standards. ** ** ** ** ** ** ** ** ** ** ** References: https://www.intechopen.com/books/ehealth-making-health-care-smarter/terminology-services-standard-terminologies-to-control-medical-vocabulary-words-are-not-what-they-sa https://danielvreeman.com/best-practices-managing-terminologies-health-information-exchange/ https://www.adsc.com/blog/what-is-interoperability-and-why-is-it-important https://www.nap.edu/read/10863/chapter/7#128 https://www.sciencedirect.com/science/article/abs/pii/S195903181500024X What is an example of semantic interoperability?Examples of semantic interoperability are Health Information Exchanges and data collection methods for population health.
What is meant by semantic interoperability?Semantic interoperability is a specialization of the general definition that is related to the understanding and interpretation of data that is exchanged for different actors of a system. Semantic interoperability provides a common understanding of the data, by using common nomenclatures and data formats.
What is interoperability and how is IT achieved?Interoperability is the ability of two or more systems to exchange health information and use the information once it is received. It will take time for all types of health IT to be fully interoperable.
How can we achieve software interoperability?Approaches to improving or achieving interoperability include conducting compatibility tests, engineering products with a common standard and using the same technology, coding language or syntax across multiple systems when appropriate.
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