scholarly journals Gastrointestinal and Nongastrointestinal Complications of Esophagogastroduodenoscopy and Colonoscopy in the Real World: A Nationwide Standard Cohort Using the Common Data Model Database

Gut and Liver ◽  
2021 ◽  
Author(s):  
Ha Il Kim ◽  
Jin Young Yoon ◽  
Min Seob Kwak ◽  
Jae Myung Cha
Keyword(s):  
Real World ◽  
Data Model ◽  
Common Data Model ◽  
The Real ◽  
The Common ◽  
Model Database

scholarly journals Honeur (Heamatology Outcomes Network in Europe): A Federated Model to Support Real World Data Research in Hematology

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4839-4839
Author(s):  
Kristina Bardenheuer ◽  
Alun Passey ◽  
Maria d'Errico ◽  
Barbara Millier ◽  
Carine Guinard-Azadian ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Real World ◽  
Data Model ◽  
Quality Analysis ◽  
Common Data Model ◽  
Real World Data ◽  
World Data ◽  
New Concepts ◽  
The Common

Abstract Introduction: The Haematology Outcomes Network in EURope (HONEUR) is an interdisciplinary initiative aimed at improving patient outcomes by analyzing real world data across hematological centers in Europe. Its overarching goal is to create a secure network which facilitates the development of a collaborative research community and allows access to big data tools for analysis of the data. The central paradigm in the HONEUR network is a federated model whereby the data stays at the respective sites and the analysis is executed at the local data sources. To allow for a uniform data analysis, the common data model 'OMOP' (Observational Medical Outcomes Partnership) was selected and extended to accommodate specific hematology data elements. Objective: To demonstrate feasibility of the OMOP common data model for the HONEUR network. Methods: In order to validate the architecture of the HONEUR network and the applicability of the OMOP common data model, data from the EMMOS registry (NCT01241396) have been used. This registry is a prospective, non-interventional study that was designed to capture real world data regarding treatments and outcomes for multiple myeloma at different stages of the disease. Data was collected between Oct 2010 and Nov 2014 on more than 2,400 patients across 266 sites in 22 countries. Data was mapped to the OMOP common data model version 5.3. Additional new concepts to the standard OMOP were provided to preserve the semantic mapping quality and reduce the potential loss of granularity. Following the mapping process, a quality analysis was performed to assess the completeness and accuracy of the mapping to the common data model. Specific critical concepts in multiple myeloma needed to be represented in OMOP. This applies in particular for concepts like treatment lines, cytogenetic observations, disease progression, risk scales (in particular ISS and R-ISS). To accommodate these concepts, existing OMOP structures were used with the definition of new concepts and concept-relationships. Results: Several elements of mapping data from the EMMOS registry to the OMOP common data model (CDM) were evaluated via integrity checks. Core entities from the OMOP CDM were reconciled against the source data. This was applied for the following entities: person (profile of year of birth and gender), drug exposure (profile of number of drug exposures per drug, at ATC code level), conditions (profile of number of occurrences of conditions per condition code, converted to SNOMED), measurement (profile of number of measurements and value distribution per (lab) measurement, converted to LOINC) and observation (profile of number of observations per observation concept). Figure 1 shows the histogram of year of birth distribution between the EMMOS registry and the OMOP CDM. No discernible differences exist, except for subjects which have not been included in the mapping to the OMOP CDM due to lacking confirmation of a diagnosis of multiple myeloma. As additional part of the architecture validation, the occurrence of the top 20 medications in the EMMOS registry and the OMOP CDM were compared, with a 100% concordance for the drug codes, which is shown in Figure 2. In addition to the reconciliation against the different OMOP entities, a comparison was also made against 'derived' data, in particular 'time to event' analysis. Overall survival was plotted from calculated variables in the analysis level data from the EMMOS registry and derived variables in the OMOP CDM. Probability of overall survival over time was virtually identical with only one day difference in median survival and 95% confidence intervals identically overlapping over the period of measurement (Figure 3). Conclusions: The concordance of year of birth, drug code mapping and overall survival between the EMMOS registry and the OMOP common data model indicates the reliability of mapping potential in HONEUR, especially where auxiliary methods have been developed to handle outcomes and treatment data in a way that can be harmonized across platform datasets. Disclosures No relevant conflicts of interest to declare.

Establishing the common oncology data model for the national biobank consortium of Taiwan.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19283-e19283
Author(s):  
Yang Yi-Hsin ◽  
Li-Tzong Chen ◽  
Shiu-Feng Huang
Keyword(s):  
National Health ◽  
Real World ◽  
Data Model ◽  
Data Science ◽  
Common Data Model ◽  
Data Interoperability ◽  
Cancer Data ◽  
Common Definition ◽  
The Common ◽  
Data Elements

e19283 Background: Taiwan has 32 biobanks under Government’ governance. The Ministry of Health and Welfare have established a National Biobank Consortium of Taiwan to unify the specimen quality and the medical record database. The total recruited participants exceed 350,000. The National Health Research Institutes in Taiwan hold the responsibility of establish a common data model for aggregating data elements from electronic health records (EHRs) of institutes through direct feeds. The goals are to assemble a set of common oncology data elements and to facilitate cancer data interoperability for patient care and research across institutes of Biobank Consortium. Methods: We first conduct a thorough review of available EHR data elements for patient characteristics, diagnosis/staging, treatments, laboratory results, vital signs and outcomes. The data dictionary was organized based on HL7 FHIR and also included data elements from Taiwan Cancer Registry (TCR) and National Health Insurance (NHI) Program, which the common definition has already been established and implemented for years. Data elements suggested by ASCO CancerLinQ and minimal Common Oncology Data Elements (mCODE) are also referenced during planning. The final common model was then reviewed by a panel of experts consisting oncologists as well as data science specialists. Results: There are finally 9 data tables with 281 data elements, in which 248 of them are from the routinely uploaded data elements to government agencies (TCR & NHI) and 33 elements are collected with partial common definition among institutes. There are 164 data elements which are to be collected one observation per case, while 117 elements will be accumulated periodically. Conclusions: A comprehensive understanding of genetics, phenotypes, disease variation as well as treatment responses is crucial to fulfill the needs of real-world studies, which potentially would lead to personalized treatment and drug development. At the first stage of this project, we aim to accumulate available EHR structured data elements and to maintain sufficient cancer data quality. Consequently, the database can provide real-world evidence to promote evidence-based & data-driven cancer care.

scholarly journals Verification in theory and in the sciences

2020 ◽  
pp. 25
Author(s):  
Konstantinos Papageorgiou ◽  
Demetrios Lekkas
Keyword(s):  
Real World ◽  
Formal Logic ◽  
Logical System ◽  
The Real ◽  
The Road ◽  
The Common ◽  
Per Se ◽  
The Relationship ◽  
Made In

In this work, we undertake the task of laying out some basic considerations towards straightening out the foundations of an abstract logical system. We venture to explain what theory is as well as what is not theory, to discriminate between the roles of truth in theory and in reality, as well as to open the road towards clarifying the relationship between theory and the real world. Etymological, cultural and conceptual analyses of truth are brought forth in order to reveal problems in modern approaches and to set the stage for more consistent solutions. One such problem addressed here is related to negation per se, to its asymmetry towards affirmative statements and to the essential ramifications of this duality with respect to the common perceptual and linguistic aspects of words indicating concepts akin to truth in various languages and to attitudes reflected and perpetuated in them and to their consequent use in attempted informal or formal logic and its understanding. Finally, a case study invoking the causes or “causes” of gravity both clarifies and reinforces the points made in this paper.

OEN: Multi-center, international, real-world evidence studies performed using health records without data pooling—The use of a common data model and shared analytical methods.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13554-e13554
Author(s):  
Bethany Levick ◽  
Sue Cheeseman ◽  
Eun Ji Nam ◽  
Haewon Doh ◽  
Subin Lim ◽  
...  
Keyword(s):  
Real World ◽  
Data Model ◽  
Clinical Care ◽  
Common Data Model ◽  
Local Data ◽  
Large Hospital ◽  
Patient Level Data ◽  
Patient Level ◽  
Real World Evidence ◽  
Level Data

e13554 Background: The value of real-world evidence derived from the care of patients managed outside the context of clinical trials is well recognised. However, the ability to link data from multiple centres, especially those from different countries, is complicated by complex legal and information governance differences. The Oncology Evidence Network is a collaboration of large hospital centres, with strong clinical informatics capabilities in six countries in Europe and Asia working with the support of an industrial partner to provide high quality, real world data reflecting routine clinical care. We have developed an efficient workflow based on a study-specific common data model (CDM) clinically validated at each site and analysed with a single analysis script, which embeds a set of data quality rules. Local implementation allows each centre to generate analytical outputs aligned across the different sites without the need for any patient level data to leave the participating site. This approach has been designed and tested in Epithelial Ovarian Cancer (EOC) patients. Methods: A CDM was agreed using expert advisors from each centre. Clinical alignment was achieved through iterative assessment of clinical vignettes, to ensure common definitions of clinical assessment, prognosis, and treatment algorithms in EOC patients. A data guide detailing variable level derivations and validation rules, general data coding principles, and conversions/codes from international coding systems was developed. The analysis scripts were implemented as a bespoke package (OpenOvary) in R. The package includes functions to validate the data against the CDM, and generate a standard output including tables, numerical summaries and Kaplan-Meier analysis of progression and overall survival. Results: 2,925 patient records from 6 centres across 6 countries were included in the study with 27 key data items curated by each centre. Treatment data is available detailing relevant surgical procedures and their outcomes, and regimens of SACT throughout patients’ care from diagnosis to death. Data completeness was generally high for key data items, with missing data ranging from 0-16% for FIGO stage at diagnosis and 0-14% for tumour morphology. The CDM and R script will be made publicly available for other centres to adopt and facilitate analysis of their local data. Conclusions: This collaboration has brought together a substantial body of data describing the care and outcomes for EOC patients. A CDM and flexible shared analysis approach enabled unified analysis and reporting whilst avoiding the transfer of patient level data and its pooling into a common database. The process of clinical and data alignment has generated a replicable model for rapid extension to other study centres to join the EOC study, or application to other disease areas.

Analysis of antiseizure drug‐related adverse reactions from the electronic health record using the common data model

Epilepsia ◽  
2020 ◽  
Vol 61 (4) ◽  
pp. 610-616 ◽  
Author(s):  
Sun Ah Choi ◽  
Hunmin Kim ◽  
Seok Kim ◽  
Sooyoung Yoo ◽  
Soyoung Yi ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Data Model ◽  
Adverse Reactions ◽  
Common Data Model ◽  
Health Record ◽  
The Common ◽  
Electronic Health

scholarly journals ”En sværm af skyer, som skal tænkes” – en diskussion af kultur, kunst og æstetik

2015 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Martin Blok Johansen ◽  
Ole Morsing
Keyword(s):  
Real World ◽  
Educational Practice ◽  
Common Denominator ◽  
The Real ◽  
The World ◽  
The Common ◽  
Epistemological Dimension ◽  
Independent Existence

<p>These days there are many different understandings and definitions of the term aesthetics. Sometimes it is regarded as identical to the pleasing or the sensual, other times it has a more workaday meaning, being associated with e.g. a well-stocked lunch table. The common denominator, however, is that aesthetics is understood as something that can be recorded in the real world, having been assigned an independent existence. <br />The concept has thus undergone ‘ontological dumping’, by which we understand that an analytical concept has become a “thing in the world”, i.e. an epistemological state has been transformed into an ontological state. The problem with this is that what can potentially be used to understand has instead turned into something to be understood. In the endeavour not to downgrade the epistemological dimension in favour of the experiential dimension, we attempt in this article to re-establish aesthetics as an analytical concept: Something to be seen with – instead of something that is seen. In addition, we put it into perspective alongside culture and art, which we feel has undergone the same ontological dumping. The article concludes with some reflections on the implications this may have for educational practice. As its theoretical springboard, the article takes the philosopher Jean-François Lyotard, drawing its exemplary material from the Norwegian author Karl Ove Knausgård.</p>

Digitalizing PBL to Transition Learning Into the Real World

2020 ◽  
pp. 279-294
Author(s):  
Pei Lin Tay ◽  
Se Yong Eh Noum
Keyword(s):  
21St Century ◽  
Real World ◽  
Learning Experience ◽  
Problem Based Learning ◽  
Learning Design ◽  
The Real ◽  
The Common

This chapter is on how the concept of teach less, learn more is envisioned in the perspective of the problem-based learning (PBL) approach. It includes a brief introduction of the problem-based learning design and its relevance to learning in the 21st century as well as strategies for implementing the processes and assessments in PBL, not in a manner of merely digitalizing the tradition but to re-establish how PBL can be strategized to transition learning experience into the real world. The chapter also discusses the effects of digitizing the PBL approach, which include highlighting how it can improve students' learning as well as cautioning teachers on the common challenges of digitizing this approach.

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