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Optimizing Medication Use through Health Information Technology
Published in Salvatore Volpe, Health Informatics, 2022
Troy Trygstad, Mary Ann Kliethermes, Anne L. Burns, Mary Roth McClurg, Marie Smith, John Easter
The Unified Medical Language System (UMLS) is sponsored by the National Library of Medicine (NLM) and has focused its efforts of late on enabling interoperability between often disparate proprietary and non-proprietary classification systems embedded within electronic medical and other health records systems. In addition to classifying diseases and procedures, relationships are defined between terms to create ontological structures. The Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), maintained by the International Health Terminology Standards Development Organization (IHTSDO), and RxNorm, produced by the (NLM) itself, are probably the most well-known and widely used ontologies in the US healthcare system, with the latter being used to classify pharmaceuticals to aid interoperable functions such as electronic prescribing and computerized physician order entry systems.
Canadian Health Outcomes for Better Information and Care: Making the Value of Nursing Visible through the Use of Standardized Data
Published in Connie White Delaney, Charlotte A. Weaver, Joyce Sensmeier, Lisiane Pruinelli, Patrick Weber, Nursing and Informatics for the 21st Century – Embracing a Digital World, 3rd Edition, Book 3, 2022
Peggy White, Lynn M. Nagle, Kathryn J. Hannah
The International Classification for Nursing Practice® (ICNP) is the standardized clinical terminology endorsed by the CNA for documenting professional nursing practice in Canada (CNA, 2003, 2016). When C-HOBIC became a national initiative, there was a need to map the C-HOBIC concepts to ICNP®. The result was the C-HOBIC/ICNP® Catalogue published by the International Council of Nurses (ICN), entitled ICNP Catalogue—Nursing Outcome Indicators (ICN, 2011). In 2006, Canada Health Infoway (Infoway) approved and adopted Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT) as the clinical standard to support the EHR and facilitate the building of a pan-Canadian EHR network. Subsequently, the C-HOBIC/ICNP® Catalogue was mapped to SNOMED CT and published by the International Health Terminology Standards Development Organisation (IHTSDO), as the Technical Report Canadian Health Outcomes for Better Information and Care (C-HOBIC) & SNOMED CT (IHTSDO, 2013). Thus, nursing data could be included in Canadian EHRs. The approach and methodology for mapping in both cases were similar and are well documented elsewhere (IHTSDO, 2013).
Using big data to improve safety and quality in radiation oncology
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
Eric Ford, Alan Kalet, Mark Phillips
There is currently an unmet need for data standardization in oncology and this is directly related to quality and safety. Many efforts are underway, examples include the development of a standard radiation prescription nomenclature by ASTRO19 and the development of standards for structure names and dose–volume histogram data by AAPM Task Group 263.20 In the United States, some of the interest will be driven by the need for Centers for Medicare and Medicaid Services (CMS)-approved Qualified Clinical Data Registries needed to qualify for the new reimbursement models.21 Such standards can be expected to have a huge impact as they have in other areas of health care, for example, the widely-used Systematized Nomenclature of Medicine (SNOMED) system, which is the categorization schema for medical terminology.
Innovation and immunization program management: traceability and quality in Latin America and the Caribbean, laying the groundwork for a regional action plan
Published in Expert Review of Vaccines, 2022
Pablo Tregnaghi, Sebastián Ospina-Henao, Cédin Maldonado Oliva, Clara Lucía Bocanegra, Christian Toledo, Cristina Aldaz, Graciela Pérez, José Luis Díaz Ortega, Juan Manuel Castelli, Lourdes Aguilar, Luis Oliva, Mabel Jiménez Quinteros, Max Enriquez Navas, Roberto Arroba
The SLIPE’s Computerized Medicine Committee has been working on the Vaxeen system, a digital and intelligent assistant in immunization. It allows for management and making inferences during the whole process of traceability of the immunization program(s); this system has gone through several development platforms. At first, it was a Registry platform; at a second moment, it incorporated artificial intelligence and became a management platform, and finally, with the incorporation of BlockChain accompanied by the Internet of Things (IoT), it became a traceability platform. Among the system’s advantages is that it has not only a web version but also a mobile application; it is multi-language, interoperable (with a Health Level Seven International (HL7) and Fast Healthcare Interoperability Resources (FHIR) information layer) with the Systematized Nomenclature of Medicine – Clinical Terms (Snomed-CT), in addition, it encrypts sensitive data making it a secure platform and has double validation systems to ensure data quality.
Ensuring equitable, inclusive and meaningful gender identity- and sexual orientation-related data collection in the healthcare sector: insights from a critical, pragmatic systematic review of the literature
Published in International Review of Psychiatry, 2022
Nicola Luigi Bragazzi, Rola Khamisy-Farah, Manlio Converti
Finally, Lynch et al. (2019) relied on an ‘expanded vocabulary’ (concept lexicon expansion and evaluation) using enriched samples of patients and documents with sexual orientation. Authors were able to find seven additional words and 21 misspellings beyond their initial set of five seed words. With this respect, great progress has been achieved with the development and implementation of the ‘Gender, Sex, and Sexual Orientation’ (GSSO) ontology, which is an integrated and curated vocabulary of approximately 200 slang terms, 190 pronouns with linked example usages, and more than 200 non-binary and culturally specific gender identities. At its second edition, it has been extensively mapped to already existing, consolidated, and reliable thesauri, such as the DSM (the Diagnostic and Statistical Manual of Mental Disorders), the SNOMED (the Systematized Nomenclature of Medicine), the MeSH (the Medical Subject Headings), and the NCIT (the National Cancer Institute Thesaurus). GSSO ontology, a readable hierarchy system, with more than 10,000 entries with definitions, and more than 14,000 database mappings, 70% of which are unique, is a formidable ontology tool for managing issues related to the LGBTI community.
Characteristics of patients with major depressive disorder switching SSRI/SNRI therapy compared with those augmenting with an atypical antipsychotic in a real-world setting
Published in Current Medical Research and Opinion, 2021
David M. Kern, M. Soledad Cepeda, Ruby C. Castilla-Puentes, Adam Savitz, Mila Etropolski
Patient demographics (age and gender) were captured on the index date. Comorbid conditions, psychiatric symptoms and the Charlson Comorbid Index15 were captured during the one-year pre-index period, which included the index date. One diagnosis code for the comorbidity of interest was required during this time frame. Comorbidities were defined according to the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) classification system, which maps various diagnostic languages, including ICD-9-CM and ICD-10-CM, to a single standardized set of concepts. Medication use in the one-year pre-index period, not including the index date, was captured according to the RxNorm ingredient and for specific treatment classes of interest (anxiolytics, hypnotics/sedatives, anticonvulsants, stimulants, lithium). Additionally, the type of SSRI/SNRI filled during the 90 days prior to the index treatment change was captured and compared between cohorts.