Variability in the prevalence of inappropriate medication use among older adults: A review highlighting the importance of screening methods and database types.

AIMS: The global older population is growing rapidly, and the rise in polypharmacy has increased potentially inappropriate medication (PIM) encounters. PIMs pose health risks, but detecting them automatically in large medical databases is complex. This review aimed to uncover PIM prevalence in individuals aged 65 years or older using health databases and emphasized the risk of underestimating PIM prevalence due to underutilization of detection tools. METHODS: This study conducted a broad search on the Medline database to identify articles about the prevalence of PIMs in older adults using various databases. Articles published between January 2010 and June 2023 were included, and specific criteria were applied for study selection. Two literature reviews conducted before our study period were integrated to obtain a perspective from the 1990s to the present day. The selected papers were analysed for variables including database type, screening method, adaptations and PIM prevalence. The study categorized databases and original screening tools for clarity, examined adaptations and assessed concordance among different screening methods. RESULTS: This study encompassed 48 manuscripts, covering 58 sample evaluations. The mean prevalence of PIMs within the general population aged over 65 years was 27.8%. Relevant heterogeneity emerged in both the utilized databases and the detection methods. Adaptation of original screening tools was observed in 86.2% (50/58) of cases. Half of the original screening tools used for assessing PIMs belonged to the simple category. About a third of the studies employed less than half of the original criteria after adaptation. Only three studies used over 75% of the original criteria and more than 50 criteria. CONCLUSIONS: This extensive review highlights PIM prevalence among the older adults, emphasizing method intricacies and the potential for underestimation due to data limitations and algorithm adjustments. The findings call for enhanced methodologies, transparent algorithms and a deeper understanding of intricate rules' impact on public health implications.

Potential efficacy of T and B lymphocyte-targeted therapies on articular involvement of patients with rheumatoid arthritis and systemic sclerosis overlap syndrome. Results from a 2-centre series of 19 cases.

OBJECTIVES: To analyse in routine practice the efficacy of targeted therapies on joint involvement of patients with rheumatoid arthritis/systemic sclerosis (RA/SSc) overlap syndrome. METHODS: This was a retrospective analysis of medical records of two academic centres over a 10-year period. Joint response to targeted therapies was measured according to EULAR criteria based on Disease Activity Score (DAS)-28. In addition, changes in CRP level and glucocorticoid consumption were recorded. RESULTS: Nineteen patients were included. Methotrexate (n=11) and hydroxychloroquine (n=4) were the most used first-line treatments. Targeted therapies were frequently used (n=14). Tocilizumab was the most selected therapy (n=8), then rituximab (n=5), abatacept and anti-tumour necrosis factor (n=4). Twenty-one treatment sequences were assessed, including 18 with EULAR response criteria. Responses were "good" or "moderate" in 100% (4/4) of patients treated with abatacept, 80% (4/5) with rituximab, 40% (2/5) with tocilizumab, and 25% (1/4) with anti-TNF. T and B lymphocyte-targeted therapies (abatacept, rituximab) resulted more frequently in a "good" or "moderate" response compared to cytokine inhibitors (tocilizumab, etanercept, infliximab) with a significant decrease in DAS-28 at 6 months (-1.75; p=0.016) and a trend to a lower consumption of glucocorticoids. CONCLUSIONS: In patients with RA/SSc overlap syndrome refractory to conventional synthetic-DMARDs, T and B lymphocyte-targeted therapies seem to be a promising therapeutic option to control joint activity.

Evaluation of the nocebo effect after switching from etanercept or adalimumab originator to a biosimilar: a retrospective study of patients with inflammatory rheumatism.

OBJECTIVES: Despite significant savings with biosimilars, their negative perception can lead to the occurrence of a nocebo effect (NE), therefore we aimed to quantify the NE in inflammatory rheumatism after switching from adalimumab or etanercept originators to biosimilars. METHODS: This retrospective study was conducted in 4 hospitals in Normandy, France between January 2018 and July 2022. The study included patients with rheumatoid arthritis or spondyloarthritis in remission under adalimumab or etanercept originators before switching to biosimilars. The occurrence of a NE was considered in patients who did not maintain biosimilars at 12 months and who presented a subjective adverse event (AE). A comparative analysis of the quantitative data collected before and after switching was performed. The AE that led to biosimilar discontinuation was identified. Additional analyses were performed to identify potential risk factors for the occurrence of a NE. RESULTS: Among 183 patients included,13.1% presented a NE. Objective AEs were observed, including rheumatism reactivation (15.3%), intolerance (8.2%), infection (1.6%) and allergic reactions (0.5%). Morning stiffness duration was significantly different before and after the switch in the spondyloarthritis group (p=0.01). No risk factors were associated with the occurrence of a NE within the limits of the studied parameters. CONCLUSIONS: The occurrence of a NE after switching to a biosimilar remains acceptable. It appears less frequent when the switch is supervised by the practitioner rather than being systematic (up to 33% in some countries). A shared medical decision seems to be essential in a subset of patients, which remains to be defined.

Integrating a new knowledge organisation system for monoclonal antibodies for therapeutic use authorised in Europe into HeTOP terminology-ontology server.

Monoclonal antibodies (MAs) are increasingly used in the therapeutic arsenal. Clinical Data Warehouses (CDWs) offer unprecedented opportunities for research on real-word data. The objective of this work is to develop a knowledge organization system on MAs for therapeutic use (MATUs) applicable in Europe to query CDWs from a multi-terminology server (HeTOP). After expert consensus, three main health thesauri were selected: the MeSH thesaurus, the National Cancer Institute thesaurus (NCIt) and the SNOMED CT. These thesauri contain 1,723 MAs concepts, but only 99 (5.7 %) are identified as MATUs. The knowledge organisation system proposed in this article is a six-level hierarchical system according to their main therapeutic target. It includes 193 different concepts organised in a cross lingual terminology server, which will allow the inclusion of semantic extensions. Ninety nine (51.3 %) MATUs concepts and 94 (48.7 %) hierarchical concepts composed the knowledge organisation system. Two separates groups (an expert group and a validation group) carried out the selection, creation and validation processes. Queries identify, for unstructured data, 83 out of 99 (83.8 %) MATUs corresponding to 45,262 patients, 347,035 hospital stays and 427,544 health documents, and for structured data, 61 out of 99 (61.6 %) MATUs corresponding to 9,218 patients, 59,643 hospital stays and 104,737 hospital prescriptions. The volume of data in the CDW demonstrated the potential for using these data in clinical research, although not all MATUs are present in the CDW (16 missing for unstructured data and 38 for structured data). The knowledge organisation system proposed here improves the understanding of MATUs, the quality of queries and helps clinical researchers retrieve relevant medical information. The use of this model in CDW allows for the rapid identification of a large number of patients and health documents, either directly by a MATU of interest (e.g. Rituximab) but also by searching for parent concepts (e.g. Anti-CD20 Monoclonal Antibody).

Evaluation of Doc'EDS: a French semantic search tool to query health documents from a clinical data warehouse.

BACKGROUND: Unstructured data from electronic health records represent a wealth of information. Doc'EDS is a pre-screening tool based on textual and semantic analysis. The Doc'EDS system provides a graphic user interface to search documents in French. The aim of this study was to present the Doc'EDS tool and to provide a formal evaluation of its semantic features. METHODS: Doc'EDS is a search tool built on top of the clinical data warehouse developed at Rouen University Hospital. This tool is a multilevel search engine combining structured and unstructured data. It also provides basic analytical features and semantic utilities. A formal evaluation was conducted to measure the impact of Natural Language Processing algorithms. RESULTS: Approximately 18.1 million narrative documents are stored in Doc'EDS. The formal evaluation was conducted in 5000 clinical concepts that were manually collected. The F-measures of negative concepts and hypothetical concepts were respectively 0.89 and 0.57. CONCLUSION: In this formal evaluation, we have shown that Doc'EDS is able to deal with language subtleties to enhance an advanced full text search in French health documents. The Doc'EDS tool is currently used on a daily basis to help researchers to identify patient cohorts thanks to unstructured data.

Performance evaluation of three semantic expansions to query PubMed.

BACKGROUND: PubMed is one of the most important basic tools to access medical literature. Semantic query expansion using synonyms can improve retrieval efficacy. OBJECTIVE: The objective was to evaluate the performance of three semantic query expansion strategies. METHODS: Queries were built for forty MeSH descriptors using three semantic expansion strategies (MeSH synonyms, UMLS mappings, and mappings created by the CISMeF team), then sent to PubMed. To evaluate expansion performances for each query, the first twenty citations were selected, and their relevance were judged by three independent evaluators based on the title and abstract. RESULTS: Queries built with the UMLS expansion provided new citations with a slightly higher mean precision (74.19%) than with the CISMeF expansion (70.28%), although the difference was not significant. Inter-rater agreement was 0.28. Results varied greatly depending on the descriptor selected. DISCUSSION: The number of citations retrieved by the three strategies and their precision varied greatly according to the descriptor. This heterogeneity could be explained by the quality of the synonyms. Optimal use of these different expansions would be through various combinations of UMLS and CISMeF intersections or unions. CONCLUSION: Information retrieval tools should propose different semantic expansions depending on the descriptor and the search objectives.

Lost in translation? A multilingual Query Builder improves the quality of PubMed queries: a randomised controlled trial.

BACKGROUND: MEDLINE is the most widely used medical bibliographic database in the world. Most of its citations are in English and this can be an obstacle for some researchers to access the information the database contains. We created a multilingual query builder to facilitate access to the PubMed subset using a language other than English. The aim of our study was to assess the impact of this multilingual query builder on the quality of PubMed queries for non-native English speaking physicians and medical researchers. METHODS: A randomised controlled study was conducted among French speaking general practice residents. We designed a multi-lingual query builder to facilitate information retrieval, based on available MeSH translations and providing users with both an interface and a controlled vocabulary in their own language. Participating residents were randomly allocated either the French or the English version of the query builder. They were asked to translate 12 short medical questions into MeSH queries. The main outcome was the quality of the query. Two librarians blind to the arm independently evaluated each query, using a modified published classification that differentiated eight types of errors. RESULTS: Twenty residents used the French version of the query builder and 22 used the English version. 492 queries were analysed. There were significantly more perfect queries in the French group vs. the English group (respectively 37.9% vs. 17.9%; p < 0.01). It took significantly more time for the members of the English group than the members of the French group to build each query, respectively 194 sec vs. 128 sec; p < 0.01. CONCLUSIONS: This multi-lingual query builder is an effective tool to improve the quality of PubMed queries in particular for researchers whose first language is not English.

A search engine to access PubMed monolingual subsets: proof of concept and evaluation in French.

BACKGROUND: PubMed contains numerous articles in languages other than English. However, existing solutions to access these articles in the language in which they were written remain unconvincing. OBJECTIVE: The aim of this study was to propose a practical search engine, called Multilingual PubMed, which will permit access to a PubMed subset in 1 language and to evaluate the precision and coverage for the French version (Multilingual PubMed-French). METHODS: To create this tool, translations of MeSH were enriched (eg, adding synonyms and translations in French) and integrated into a terminology portal. PubMed subsets in several European languages were also added to our database using a dedicated parser. The response time for the generic semantic search engine was evaluated for simple queries. BabelMeSH, Multilingual PubMed-French, and 3 different PubMed strategies were compared by searching for literature in French. Precision and coverage were measured for 20 randomly selected queries. The results were evaluated as relevant to title and abstract, the evaluator being blind to search strategy. RESULTS: More than 650,000 PubMed citations in French were integrated into the Multilingual PubMed-French information system. The response times were all below the threshold defined for usability (2 seconds). Two search strategies (Multilingual PubMed-French and 1 PubMed strategy) showed high precision (0.93 and 0.97, respectively), but coverage was 4 times higher for Multilingual PubMed-French. CONCLUSIONS: It is now possible to freely access biomedical literature using a practical search tool in French. This tool will be of particular interest for health professionals and other end users who do not read or query sufficiently in English. The information system is theoretically well suited to expand the approach to other European languages, such as German, Spanish, Norwegian, and Portuguese.

Evaluating alignment quality between iconic language and reference terminologies using similarity metrics.

BACKGROUND: Visualization of Concepts in Medicine (VCM) is a compositional iconic language that aims to ease information retrieval in Electronic Health Records (EHR), clinical guidelines or other medical documents. Using VCM language in medical applications requires alignment with medical reference terminologies. Alignment from Medical Subject Headings (MeSH) thesaurus and International Classification of Diseases - tenth revision (ICD10) to VCM are presented here. This study aim was to evaluate alignment quality between VCM and other terminologies using different measures of inter-alignment agreement before integration in EHR. METHODS: For medical literature retrieval purposes and EHR browsing, the MeSH thesaurus and the ICD10, both organized hierarchically, were aligned to VCM language. Some MeSH to VCM alignments were performed automatically but others were performed manually and validated. ICD10 to VCM alignment was entirely manually performed. Inter-alignment agreement was assessed on ICD10 codes and MeSH descriptors, sharing the same Concept Unique Identifiers in the Unified Medical Language System (UMLS). Three metrics were used to compare two VCM icons: binary comparison, crude Dice Similarity Coefficient (DSCcrude), and semantic Dice Similarity Coefficient (DSCsemantic), based on Lin similarity. An analysis of discrepancies was performed. RESULTS: MeSH to VCM alignment resulted in 10,783 relations: 1,830 of which were manually performed and 8,953 were automatically inherited. ICD10 to VCM alignment led to 19,852 relations. UMLS gathered 1,887 alignments between ICD10 and MeSH. Only 1,606 of them were used for this study. Inter-alignment agreement using only validated MeSH to VCM alignment was 74.2% [70.5-78.0]CI95%, DSCcrude was 0.93 [0.91-0.94]CI95%, and DSCsemantic was 0.96 [0.95-0.96]CI95%. Discrepancy analysis revealed that even if two thirds of errors came from the reviewers, UMLS was nevertheless responsible for one third. CONCLUSIONS: This study has shown strong overall inter-alignment agreement between MeSH to VCM and ICD10 to VCM manual alignments. VCM icons have now been integrated into a guideline search engine (http://www.cismef.org) and a health terminologies portal (http://www.hetop.eu).

Digital Health Education for the Future: The SaNuRN (Santé Numérique Rouen-Nice) Consortium's Journey.

SaNuRN is a five-year project by the University of Rouen Normandy (URN) and the Côte d'Azur University (CAU) consortium to optimize digital health education for medical and paramedical students, professionals, and administrators. The project includes a skills framework, training modules, and teaching resources. In 2027, SaNuRN is expected to train a significant portion of the 400,000 health and paramedical professions students at the French national level. Our purpose is to give a synopsis of the SaNuRN initiative, emphasizing its novel educational methods and how they will enhance the delivery of digital health education. Our goals include showcasing SaNuRN as a comprehensive program consisting of a proficiency framework, instructional modules, and educational materials and explaining how SaNuRN is implemented in the participating academic institutions. SaNuRN is a project aimed at educating and training health-related and paramedics students in digital health. The project results from a cooperative effort between URN and CAU, covering four French departments. The project is based on the French National Referential on Digital Health (FNRDH), which defines the skills and competencies to be acquired and validated by every student in the health, paramedical, and social professions curricula. The SaNuRN team is currently adapting the existing URN and CAU syllabi to FNRDH and developing short-duration video capsules of 20 to 30 minutes to teach all the relevant material. The project aims to ensure that the largest student population earns the necessary skills, and it has developed a two-tier system involving facilitators who will enable the efficient expansion of the project's educational outreach and support the students in learning the needed material efficiently. With a focus on real-world scenarios and innovative teaching activities integrating telemedicine devices and virtual professionals, SaNuRN is committed to enabling continuous learning for healthcare professionals in clinical practice. The SaNuRN team introduced new ways of evaluating healthcare professionals by shifting from a knowledge-based to a competencies-based evaluation, aligning with the Miller teaching pyramid and using the Objective Structured Clinical Examination and Script Concordance Test in digital health education. Drawing on the expertise of URN, CAU, and their public health and digital research laboratories and partners, the SaNuRN project represents a platform for continuous innovation, including telemedicine training and living labs with virtual and interactive professional activities. The SaNuRN project provides a comprehensive, personalized 30-hour training package for health and paramedical students, addressing all 70 FNRDH competencies. The program is enhanced using AI and NLP to create virtual patients and professionals for digital healthcare simulation. SaNuRN teaching materials are open-access. The project collaborates with academic institutions worldwide to develop educational material in digital health in English and multilingual formats. SaNuRN offers a practical and persuasive training approach to meet the current digital health education requirements.

Paediatric antibiotic prescribing in a nationwide direct-to-consumer telemedicine platform in France, 2018-2021.

Background: Recent regulatory and reimbursement changes facilitated the development of teleconsultation within primary care. French guidance advises against antibiotic prescribing in children in teleconsultation. We assessed paediatric antibiotic prescribing on a French teleconsultation platform. Methods: This cross-sectional observational study analysed paediatric (0-14 years) visits on a national direct-to-consumer teleconsultation platform between January 2018 and December 2021. Teleconsultations with complete information regarding diagnosis (ICD-10 coding) and prescriptions were included. We assessed antibiotic prescription rates per 100 visits across diagnoses and used logistic regression to identify factors associated with antibiotic prescribing. Results: In the 37 587 included paediatric teleconsultations (median age 3 years) performed by 713 general practitioners (GPs) and 89 paediatricians, antibiotics were prescribed for 12.1%. Respiratory tract infections (RTIs) accounted for 49.5% of antibiotic prescriptions. Antibiotic prescription rates per 100 visits were: sinusitis, 69.5%; urinary tract infections, 62.2%; pharyngitis, 59.0%; pneumonia, 45.5%; otitis, 46.6%; bronchitis, 19.6%; rhinitis, 11.6%; bronchiolitis 6.6%. Antibiotic prescription rates were higher in GPs than paediatricians [OR 2.21 (IC95% 2.07-2.35)], among physicians aged 45-54 and over 65 [OR 1.66 (1.48-1.85) and 1.48 (1.32-1.66), respectively], in female practitioners [OR 1.13 (1.05-1.21)], in children 3-6 years old [OR 1.41 (1.28-1.56)] and over 6 [OR 1.50 (1.35-1.66)], during winter [OR 1.28 (1.21-1.37)] and for RTIs [OR 1.99 (1.87-2.10)]. Antibiotic prescription rates were lower in doctors with extensive experience in teleconsultation [OR 0.92 (0.86-0.98)]. Conclusions: Despite current recommendations, paediatric patients were frequently prescribed antibiotics during acute care teleconsultations. Specific antibiotic stewardship campaigns should target paediatric teleconsultations.

Standardized Reasons for Consultations on a French Telemedicine Platform.

Thirteen standardized reasons for e-visits were implemented in March 2024 on a French telemedicine platform to improve the analysis of needs in telemedicine, educate patients on what is possible in e-visit and adapt the offer. Patients could select 1 to 3 reasons for consultations among a list of 13 reasons. Our aim was to evaluate their impact on use of e-visits. The main reasons for consultations in teleconsultations were more linked to acute care, specifically involving a large majority of upper respiratory tract infections, back pain, and urinary tract infections. They were mostly concordant with the physician's conclusion and they may have simplified the preparation of the e-visits.

Empowering healthcare education: A multilingual ontology for medical informatics and digital health (MIMO) integrated to artificial intelligence powered training in smart hospitals.

Objective: A comprehensive understanding of professional and technical terms is essential to achieving practical results in multidisciplinary projects dealing with health informatics and digital health. The medical informatics multilingual ontology (MIMO) initiative has been created through international cooperation. MIMO is continuously updated and comprises over 3700 concepts in 37 languages on the Health Terminology/Ontology Portal (HeTOP). Methods: We conducted case studies to assess the feasibility and impact of integrating MIMO into real-world healthcare projects. In HosmartAI, MIMO is used to index technological tools in a dedicated marketplace and improve partners' communication. Then, in SaNuRN, MIMO supports the development of a "Catalog and Index of Digital Health Teaching Resources" (CIDHR) backing digital health resources retrieval for health and allied health students. Results: In HosmartAI, MIMO facilitates the indexation of technological tools and smooths partners' interactions. In SaNuRN within CIDHR, MIMO ensures that students and practitioners access up-to-date, multilingual, and high-quality resources to enhance their learning endeavors. Conclusion: Integrating MIMO into training in smart hospital projects allows healthcare students and experts worldwide with different mother tongues and knowledge to tackle challenges facing the health informatics and digital health landscape to find innovative solutions improving initial and continuous education.

Initiating a One Digital Health Unified Terminology (ODH-UT) to Facilitate Community Expansion.

One Digital Health (ODH) merges the Digital Health and One Health approaches to create a comprehensive framework for future health ecosystems. In this rapidly evolving field, a standardized vocabulary is not just a convenience, but a necessity to ensure efficient communication. This research proposes the development of a "One Digital Health-Unified Terminology" (ODH-UT) to facilitate communication among researchers and practitioners in Digital Health and One Health, addressing this crucial need.

Sharing Digital Health Educational Resources in a One-Stop Shop Portal: Tutorial on the Catalog and Index of Digital Health Teaching Resources (CIDHR) Semantic Search Engine.

BACKGROUND: Access to reliable and accurate digital health web-based resources is crucial. However, the lack of dedicated search engines for non-English languages, such as French, is a significant obstacle in this field. Thus, we developed and implemented a multilingual, multiterminology semantic search engine called Catalog and Index of Digital Health Teaching Resources (CIDHR). CIDHR is freely accessible to everyone, with a focus on French-speaking resources. CIDHR has been initiated to provide validated, high-quality content tailored to the specific needs of each user profile, be it students or professionals. OBJECTIVE: This study's primary aim in developing and implementing the CIDHR is to improve knowledge sharing and spreading in digital health and health informatics and expand the health-related educational community, primarily French speaking but also in other languages. We intend to support the continuous development of initial (ie, bachelor level), advanced (ie, master and doctoral levels), and continuing training (ie, professionals and postgraduate levels) in digital health for health and social work fields. The main objective is to describe the development and implementation of CIDHR. The hypothesis guiding this research is that controlled vocabularies dedicated to medical informatics and digital health, such as the Medical Informatics Multilingual Ontology (MIMO) and the concepts structuring the French National Referential on Digital Health (FNRDH), to index digital health teaching and learning resources, are effectively increasing the availability and accessibility of these resources to medical students and other health care professionals. METHODS: First, resource identification is processed by medical librarians from websites and scientific sources preselected and validated by domain experts and surveyed every week. Then, based on MIMO and FNRDH, the educational resources are indexed for each related knowledge domain. The same resources are also tagged with relevant academic and professional experience levels. Afterward, the indexed resources are shared with the digital health teaching and learning community. The last step consists of assessing CIDHR by obtaining informal feedback from users. RESULTS: Resource identification and evaluation processes were executed by a dedicated team of medical librarians, aiming to collect and curate an extensive collection of digital health teaching and learning resources. The resources that successfully passed the evaluation process were promptly included in CIDHR. These resources were diligently indexed (with MIMO and FNRDH) and tagged for the study field and degree level. By October 2023, a total of 371 indexed resources were available on a dedicated portal. CONCLUSIONS: CIDHR is a multilingual digital health education semantic search engine and platform that aims to increase the accessibility of educational resources to the broader health care-related community. It focuses on making resources "findable," "accessible," "interoperable," and "reusable" by using a one-stop shop portal approach. CIDHR has and will have an essential role in increasing digital health literacy.

Trends in computerized provider order entry: 20-year bibliometric overview.

Background: Drug-related problems (DRPs) can lead to serious health issues and have significant economic impacts on healthcare systems. One solution to address this issue is the use of computerized physician order entry systems (CPOE), which can help prevent DRPs by reducing the risk of medication errors. Objective: The purpose of this study is to provide an analysis on scientific production of the past 20 years in order to describe trends in academic publishing on CPOE and to identify the major topics as well as the predominant actors (journals, countries) involved in this field. Methods: A PubMed search was carried out to extract articles related to computerized provider order entry during the period January 1st 2003- December 31st 2022 using a specific query. Data were downloaded from PubMed in Extensible Markup Language (XML) and were processed through a dedicated parser. Results: A total of 2,946 articles were retrieved among 623 journals. One third of these articles were published in eight journals. Publications grew strongly from 2002 to 2006, with a dip in 2008 followed by an increase again in 2009. After 2009, there follows a decreasing until 2022.The most producing countries are the USA with 51.39% of the publication over the period by France (3.80%), and Canada (3.77%). About disciplines, the top 3 is: "medical informatics" (21.62% of articles), "pharmacy" (19.04%), and "pediatrics" (6.56%). Discussion: This study provides an overview of publication trends related to CPOE, which exhibited a significant increase in the first decade of the 21st century followed by a decline after 2009. Possible reasons for this decline include the emergence of digital health tools beyond CPOE, as well as healthcare professionals experiencing alert fatigue of the current system. Conclusion: Future research should focus on analyzing publication trends in the field of medical informatics and decision-making tools to identify other areas of interest that may have surpassed the development of CPOE.

Digital Emergency Management for a Complex One Health Landscape: the Need for Standardization, Integration, and Interoperability.

OBJECTIVE: Planning reliable long-term planning actions to handle disruptive events requires a timely development of technological infrastructures, as well as the set-up of focused strategies for emergency management. The paper aims to highlight the needs for standardization, integration, and interoperability between Accident & Emergency Informatics (A&EI) and One Digital Health (ODH), as fields capable of dealing with peculiar dynamics for a technology-boosted management of emergencies under an overarching One Health panorama. METHODS: An integrative analysis of the literature was conducted to draw attention to specific foci on the correlation between ODH and A&EI, in particular: (i) the management of disruptive events from private smart spaces to diseases spreading, and (ii) the concepts of (health-related) quality of life and well-being. RESULTS: A digitally-focused management of emergency events that tackles the inextricable interconnectedness between humans, animals, and surrounding environment, demands standardization, integration, and systems interoperability. A consistent and finalized process of adoption and implementation of methods and tools from the International Standard Accident Number (ISAN), via findability, accessibility, interoperability, and reusability (FAIR) data principles, to Medical Informatics and Digital Health Multilingual Ontology (MIMO) - capable of looking at different approaches to encourage the integration between the ODH framework and the A&EI vision, provides a first answer to these needs. CONCLUSIONS: ODH and A&EI look at different scales but with similar goals for converging health and environmental-related data management standards to enable multi-sources, interdisciplinary, and real-time data integration and interoperability. This allows holistic digital health both in routine and emergency events.

Modeling and integrating interactions involving the CYP450 enzyme system in a multi-terminology server: Contribution to information extraction from a clinical data warehouse.

INTRODUCTION: The cytochrome P450 (CYP450) enzyme system is involved in the metabolism of certain drugs and is responsible for most drug interactions. These interactions result in either an enzymatic inhibition or an enzymatic induction mechanism that has an impact on the therapeutic management of patients. Detecting these drug interactions will allow for better predictability in therapeutic response. Therefore, computerized solutions can represent a valuable help for clinicians in their tasks of detection. OBJECTIVE: The objective of this study is to provide a structured data-source of interactions involving the CYP450 enzyme system. These interactions are aimed to be integrated in the cross-lingual multi-terminology server HeTOP (Health Terminologies and Ontologies Portal), to support the query processing of the clinical data warehouse (CDW) EDSaN (Entrepôt de Données de Santé Normand). MATERIAL AND METHODS: A selection and curation of drug components (DCs) that share a relationship with the CYP450 system was performed from several international data sources. The DCs were linked according to the type of relationship which can be substrate, inhibitor, or inducer. These relationships were then integrated into the HeTOP server. To validate the CYP450 relationships, a semantic query was performed on the CDW, whose search engine is founded on HeTOP data (concepts, terms, and relations). RESULTS: A total of 776 DCs are associated by a new interaction relationship, integrated in HeTOP, by 14 enzymes. These are CYP450 1A2, 2A6, 2B6, 2C8, 2C9, 2C18, 2C19, 2D6, 2E1, 3A4, 3A7, 11B1,11B2 mitochondrial and P-glycoprotein, constituting a total of 2,088 relationships. A general modelling of cytochromic interactions was performed. From this model, 233,006 queries were processed in less than two hours, demonstrating the usefulness and performance of our CDW implementation. Moreover, they showed that in our university hospital, the concurrent prescription that could cause a cytochromic interaction is Bisoprolol with Amiodarone by enzymatic inhibition for 2,493 patients. DISCUSSION: The queries submitted to the CDW EDSaN allowed to highlight the most prescribed molecules simultaneously and potentially responsible for cytochromic interactions. In a second step, it would be interesting to evaluate the real clinical impact by looking for possible adverse effects of these interactions in the patients' files. Other computational solutions for cytochromic interactions exist. The impact of CYP450 is particularly important for drugs with narrow therapeutic window (NTW) as they can lead to increased toxicity or therapeutic failure. It is also important to define which drug component is a pro-drug and to considerate the many genetic polymorphisms of patients. CONCLUSION: The HeTOP server contains a non-negligible number of relationships between drug components and CYP450 from multiple reference sources. These data allow us to query our Clinical Data Warehouse to highlight these cytochromic interactions. It would be interesting in the future to assess the actual clinical impact in hospital reports.