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Atlas - a data warehouse for integrative bioinformatics

BMC BIOINFORMATICS 2005年第1期6卷 34-34页

作者： Shah, SP Huang, Y Xu, T Yuen, MMS Ling, J Ouellette, BFF Univ British Columbia UBC Bioinformat Ctr Vancouver BC V5Z 1M9 Canada

Background: We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description: The Atlas system is based on relational data models that we developed for each of the source data types. data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference database (HPRD), Biomolecular Interaction Network database (BIND), database of Interacting Proteins ( DIP), Molecular Interactions database (MINT), IntAct, NCBI Taxonomy,Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion: The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data o

关键词： Structure Query Language Human Protein Reference database NCBI Taxonomy common data model Relational data model

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A security scheme for distributing analysis codes supporting CDM-based research in a multi-center environment

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022年 226卷 107159-107159页

作者： Jeon, Seungho Shin, Chobyeol Ko, Eunnarae Moon, Jongsub Korea Univ Grad Sch Informat Secur 145 Anrm Ro Seoul 02841 South Korea

Background: Although the common data model (CDM) has achieved a standardization of medical data and a de-identification of personal patient information, hospitals still store CDM data in an on-premises environment, making it difficult for researchers to access medical data. Objective: In this study, for easy access to CDM data in a multi-institutional participatory CDM research environment and to encourage data-driven research, researchers outside hospital networks securely access and analyze CDM data in the target medical center, analyze it, and respond to the results through a public network. We propose an automated security framework that operates on a public network, such as the Internet. Method: The proposed scheme allows authenticated researchers to securely deliver CDM data analysis codes to a medical institution distributed on the network. The institutional servers automatically execute authenticated codes and return the results to the researcher safely. For this purpose, we designed a scheme based on cryptography. The scheme operates on a group of servers consisting of an authentication process, a signing process, a ticket-granting process, a relaying process, and a data analysis process located at the hospital providing medical CDM data. The scheme consists of four phases for a secure medical data analysis in a distributed environment: authentication, code signing, ticket issuing, and distribution and return. Results: Although the CDM has de-identified patient privacy, the issue still needs to be carefully addressed. Therefore, we established four security objectives to verify that the proposed scheme can be operated safely and formally proved them using BAN logic. Conclusion: As a result of the proof using BAN logic, the proposed scheme was verified to achieve the proposed security goal. Although this scheme was designed solely for CDM, it can be applied to systems with similar environments and functional goals. (C) 2022 Elsevier B.V. All rights reserved.

关键词： common data model Multi-centered medical research Secure distribution-protocol Kerberos

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A scoping review of semantic integration of health data and information

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2022年第0期165卷 104834-104834页

作者： Zhang, Hansi Lyu, Tianchen Yin, Pengfei Bost, Sarah He, Xing Guo, Yi Prosperi, Mattia Hogan, Willian R. Bian, Jiang Univ Florida Coll Med Hlth Outcomes & Biomed Informat Gainesville FL USA Univ Florida Coll Med Dept Epidemiol Gainesville FL USA 2197 Mowry Rd 122 Gainesville FL 32610 USA

Objective: We summarized a decade of new research focusing on semantic data integration (SDI) since 2009, and we aim to: (1) summarize the state-of-art approaches on integrating health data and information;and (2) identify the main gaps and challenges of integrating health data and information from multiple levels and *** and Methods: We used PubMed as our focus is applications of SDI in biomedical domains and followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) to search and report for relevant studies published between January 1, 2009 and December 31, 2021. We used Covidence-a systematic review management system-to carry out this scoping ***: The initial search from PubMed resulted in 5,326 articles using the two sets of keywords. We then removed 44 duplicates and 5,282 articles were retained for abstract screening. After abstract screening, we included 246 articles for full-text screening, among which 87 articles were deemed eligible for full-text extraction. We summarized the 87 articles from four aspects: (1) methods for the global schema;(2) data integration strategies (i.e., federated system vs. data warehousing);(3) the sources of the data;and (4) downstream ***: SDI approach can effectively resolve the semantic heterogeneities across different data sources. We identified two key gaps and challenges in existing SDI studies that (1) many of the existing SDI studies used data from only single-level data sources (e.g., integrating individual-level patient records from different hospital systems), and (2) documentation of the data integration processes is sparse, threatening the reproducibility of SDI studies.

关键词： Semantic data integration common data model common data element Ontology Systematic review and meta -analyses (PRISMA) framework

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Toward new generation railway Traffic Management Systems: the contribution of the OPTIMA project

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Transportation Research Procedia 2023年 72卷 3166-3173页

作者： Gabriele Cecchetti Anna Lina Ruscelli Cristian Ulianov Paul Hyde Jin Liu Airy Magnien Marek Tavač Michal Ďuračík Luca Oneto Jose Bertolin Scuola Superiore Sant'Anna Via G. Moruzzi 1 56124 Pisa Italy University of Newcasle Newcastle upon Tyne NE1 7RU UK University of Zˇilina Univerzitna 8215/1 010 26 Zilina Slovakia University of Genoa Via Opera Pia 11a 16145 Genova Italy UNIFE Av. Louise 221 1050 Bruxelles Belgium

Legacy Traffic Management Systems (TMS) lack interoperable data structures and standardized communication interfaces. The H2020 Shift2Rail OPTIMA project is developing a demonstrator of a communication platform for a new generation of TMS with advanced functionalities for improving the efficiency, effectiveness, and resilience of railway operations, as well as improved interoperability, modularity, and scalability. In this paper, this platform is described, along with its main components that provide seamless access to persistent and real-time data from heterogeneous data sources. A common data model supports the automated data exchange process by means of a fully standardized structure for representing the data. Furthermore, the testing and validation of the OPTIMA platform and of connected TMS services when it is set up as a testing environment are illustrated.

关键词： Railway Traffic Management Systems Integration Layer common data model Technological Demonstrator Integration of networks and services

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ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2023年第1期177卷 105144-105144页

作者： Oniani, David Parmanto, Bambang Saptono, Andi Bove, Allyn Freburger, Janet Visweswaran, Shyam Cappella, Nickie McLay, Brian Silverstein, Jonathan C. Becich, Michael J. Delitto, Anthony Skidmore, Elizabeth Wang, Yanshan Univ Pittsburgh Dept Hlth Informat Management Pittsburgh PA 15213 USA Univ Pittsburgh Dept Occupat Therapy Pittsburgh PA USA Univ Pittsburgh Dept Phys Therapy Pittsburgh PA USA Univ Pittsburgh Sch Med Dept Biomed Informat Pittsburgh PA 15206 USA Univ Pittsburgh Intelligent Syst Program Pittsburgh PA 15260 USA Univ Pittsburgh Clin & Translat Sci Inst Pittsburgh PA 15213 USA

Rehabilitation research focuses on determining the components of a treatment intervention, the mechanism of how these components lead to recovery and rehabilitation, and ultimately the optimal intervention strategies to maximize patients' physical, psychologic, and social functioning. Traditional randomized clinical trials that study and establish new interventions face challenges, such as high cost and time commitment. Observational studies that use existing clinical data to observe the effect of an intervention have shown several advantages over RCTs. Electronic Health Records (EHRs) have become an increasingly important resource for conducting observational studies. To support these studies, we developed a clinical research datamart, called ReDWINE (Rehabilitation datamart With Informatics iNfrastructure for rEsearch), that transforms the rehabilitation-related EHR data collected from the UPMC health care system to the Observational Health data Sciences and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to facilitate rehabilitation research. The standardized EHR data stored in ReDWINE will further reduce the time and effort required by investigators to pool, harmonize, clean, and analyze data from multiple sources, leading to more robust and comprehensive research findings. ReDWINE also includes deployment of data visualization and data analytics tools to facilitate cohort definition and clinical data analysis. These include among others the Open Health Natural Language Processing (OHNLP) toolkit, a high-throughput NLP pipeline, to provide text analytical capabilities at scale in ReDWINE. Using this comprehensive representation of patient data in ReDWINE for rehabilitation research will facilitate real-world evidence for health interventions and outcomes.

关键词： Electronic health records Rehabilitation Clinical research informatics Informatics infrastructure Natural language processing common data model

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Development and Validation of a Prognostic Classification model Predicting Postoperative Adverse Outcomes in Older Surgical Patients Using a Machine Learning Algorithm: Retrospective Observational Network Study

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JOURNAL OF MEDICAL INTERNET RESEARCH 2023年第1期25卷 e42259页

作者： Choi, Jung-Yeon Yoo, Sooyoung Song, Wongeun Kim, Seok Baek, Hyunyoung Lee, Jun Suh Yoon, Yoo-Seok Yoon, Seonghae Lee, Hae-Young Kim, Kwang-il Seoul Natl Univ Dept Internal Med Bundang Hosp Seongnam Si South Korea Seoul Natl Univ Off Ehlth Res & Business Bundang Hosp Seongnam Si South Korea Seoul Natl Univ Grad Sch Convergence Sci & Technol Dept Hlth Sci & Technol Seongnam Si South Korea G Sam Hosp Dept Surg Gunpo South Korea Seoul Natl Univ Dept Surg Bundang Hosp Seongnam Si South Korea Seoul Natl Univ Dept Surg Coll Med Seoul South Korea Seoul Natl Univ Dept Clin Pharmacol & Therapeut Bundang Hosp Seongnam Si South Korea Seoul Natl Univ Hosp Dept Internal Med Seoul South Korea Seoul Natl Univ Dept Internal Med Coll Med Seoul South Korea Seoul Natl Univ Bundang Hosp Dept Internal Med 82 Gumi Ro173 Beon Gil Seongnam Si 13620 South Korea

Background: Older adults are at an increased risk of postoperative morbidity. Numerous risk stratification tools exist, but effort and manpower are required. Objective: This study aimed to develop a predictive model of postoperative adverse outcomes in older patients following general surgery with an open-source, patient-level prediction from the Observational Health data Sciences and Informatics for internal and external validation. Methods: We used the Observational Medical Outcomes Partnership common data model and machine learning algorithms. The primary outcome was a composite of 90-day postoperative all-cause mortality and emergency department visits. Secondary outcomes were postoperative delirium, prolonged postoperative stay (>= 75th percentile), and prolonged hospital stay (>= 21 days). An 80% versus 20% split of the data from the Seoul National University Bundang Hospital (SNUBH) and Seoul National University Hospital (SNUH) common data model was used for model training and testing versus external validation. model performance was evaluated using the area under the receiver operating characteristic curve (AUC) with a 95% CI. Results: data from 27,197 (SNUBH) and 32,857 (SNUH) patients were analyzed. Compared to the random forest, Adaboost, and decision tree models, the least absolute shrinkage and selection operator logistic regression model showed good internal discriminative accuracy (internal AUC 0.723, 95% CI 0.701-0.744) and transportability (external AUC 0.703, 95% CI 0.692-0.714) for the primary outcome. The model also possessed good internal and external AUCs for postoperative delirium (internal AUC 0.754, 95% CI 0.713-0.794;external AUC 0.750, 95% CI 0.727-0.772), prolonged postoperative stay (internal AUC 0.813, 95% CI 0.800-0.825;external AUC 0.747, 95% CI 0.741-0.753), and prolonged hospital stay (internal AUC 0.770, 95% CI 0.749-0.792;external AUC 0.707, 95% CI 0.696-0.718). Compared with age or the Charlson comorbidity index, the model showed

关键词： CDM common data model patient-level prediction OHDSI Observational Health data Sciences and Informatics postoperative outcome postoperative surgery elderly elder predict adverse event adverse outcome geriatric older adult ageing model algorithm

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Empirical assessment of alternative methods for identifying seasonality in observational healthcare data

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BMC MEDICAL RESEARCH METHODOLOGY 2022年第1期22卷 182-182页

作者： Molinaro, Anthony DeFalco, Frank Janssen Res & Dev 1125 Trenton Harbourton Rd Titusville NJ 08560 USA

Background Seasonality classification is a well-known and important part of time series analysis. Understanding the seasonality of a biological event can contribute to an improved understanding of its causes and help guide appropriate responses. Observational data, however, are not comprised of biological events, but timestamped diagnosis codes the combination of which (along with additional requirements) are used as proxies for biological events. As there exist different methods for determining the seasonality of a time series, it is necessary to know if these methods exhibit concordance. In this study we seek to determine the concordance of these methods by applying them to time series derived from diagnosis codes in observational data residing in databases that vary in size, type, and provenance. Methods We compared 8 methods for determining the seasonality of a time series at three levels of significance (0.01, 0.05, and 0.1), against 10 observational health databases. We evaluated 61,467 time series at each level of significance, totaling 184,401 evaluations. Results Across all databases and levels of significance, concordance ranged from 20.2 to 40.2%. Across all databases and levels of significance, the proportion of time series classified seasonal ranged from 4.9 to 88.3%. For each database and level of significance, we computed the difference between the maximum and minimum proportion of time series classified seasonal by all methods. The median within-database difference was 54.8, 34.7, and 39.8%, for p < 0.01, 0.05, and 0.1, respectively. Conclusion Methods of binary seasonality classification when applied to time series derived from diagnosis codes in observational health data produce inconsistent results. The methods exhibit considerable discord within all databases, implying that the discord is a result of the difference between the methods themselves and not due to the choice of database. The results indicate that researchers relying on automated meth

关键词： ACHILLES ARIMA CASTOR Classification common data model Cyclical Observational data OHDSI OMOP CDM R Seasonality Time series

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Patient-Centered Economic Burden of Exudative Age-Related Macular Degeneration: Retrospective Cohort Study

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JMIR PUBLIC HEALTH AND SURVEILLANCE 2023年第1期9卷 e49852页

作者： Choi, Kyungseon Park, Sang Jun Han, Sola Mun, Yongseok Lee, Da Yun Chang, Dong-Jin Kim, Seok Yoo, Sooyoung Woo, Se Joon Park, Kyu Hyung Suh, Hae Sun Kyung Hee Univ Grad Sch Dept Regulatory Sci Seoul South Korea Kyung Hee Univ Inst Regulatory Innovat Sci Seoul South Korea Seoul Natl Univ Bundang Hosp Coll Med Dept Ophthalmol Seongnam South Korea Univ Texas Austin Coll Pharm Hlth Outcomes Div Austin TX USA Hallym Univ Coll Med Kangnam Sacred Heart Hosp Dept Ophthalmol Seoul South Korea Catholic Univ Korea Yeouido St Marys Hosp Coll Med Dept Ophthalmol & Visual Sci Seoul South Korea Seoul Natl Univ Bundang Hosp Off eHlth Res & Businesses Healthcare ICT Res Ctr Seongnam South Korea Seoul Natl Univ Coll Med Seoul Natl Univ Hosp Dept Ophthalmol Seoul South Korea Kyung Hee Univ Coll Pharm Seoul South Korea Kyung Hee Univ Coll Pharm 26 Kyunghee Daero Seoul 02447 South Korea

Background: Exudative age-related macular degeneration (AMD), one of the leading causes of blindness, requires expensive drugs such as anti-vascular endothelial growth factor (VEGF) agents. The long-term regular use of effective but expensive drugs causes an economic burden for patients with exudative AMD. However, there are no studies on the long-term patient-centered economic burden of exudative AMD after reimbursement of ***: This study aimed to evaluate the patient-centered economic burden of exudative AMD for 2 years, including nonreimbursement and out-of-pocket costs, compared with nonexudative AMD using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM).Methods: This retrospective cohort study was conducted using the OMOP CDM, which included 2,006,478 patients who visited Seoul National University Bundang Hospital from June 2003 to July 2019. We defined the exudative AMD group as patients aged >50 years with a diagnosis of exudative AMD and a prescription for anti-VEGFs or verteporfin. The control group was defined as patients aged >50 years without a diagnosis of exudative AMD or a prescription for anti-VEGFs or verteporfin. To adjust for selection bias, controls were matched by propensity scores using regularized logistic regression with a Laplace prior. We measured any medical cost occurring in the hospital as the economic burden of exudative AMD during a 2-year follow-up period using 4 categories: total medical cost, reimbursement cost, nonreimbursement cost, and out-of-pocket cost. To estimate the average cost by adjusting the confounding variable and overcoming the positive skewness of costs, we used an exponential conditional model with a generalized linear model. Results: We identified 931 patients with exudative AMD and matched 783 (84.1%) with 2918 patients with nonexudative AMD. In the exponential conditional model, the total medical, reimbursement, nonreimbursement, and out-of-pocket incremental costswer

关键词： blindness age-related macular degeneration economic burden cost of illness retrospective cohort study common data model

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A Framework (SOCRATex) for Hierarchical Annotation of Unstructured Electronic Health Records and Integration Into a Standardized Medical database: Development and Usability Study

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JMIR MEDICAL INFORMATICS 2021年第3期9卷 e23983页

作者： Park, Jimyung You, Seng Chan Jeong, Eugene Weng, Chunhua Park, Dongsu Roh, Jin Lee, Dong Yun Cheong, Jae Youn Choi, Jin Wook Kang, Mira Park, Rae Woong Ajou Univ Dept Biomed Sci Grad Sch Med Suwon South Korea Yonsei Univ Dept Prevent Med & Publ Hlth Coll Med Seoul South Korea Vanderbilt Univ Dept Biomed Informat Sch Med Nashville TN USA Columbia Univ Dept Biomed Informat New York NY USA Ajou Univ Dept Biomed Informat Sch Med 164 World Cup Ro Suwon 16499 South Korea Ajou Univ Hosp Dept Pathol Suwon South Korea Ajou Univ Dept Gastroenterol Sch Med Suwon South Korea Ajou Univ Dept Radiol Sch Med Suwon South Korea Sungkyunkwan Univ Samsung Adv Inst Hlth Sci & Technol Dept Digital Hlth Seoul South Korea

Background: Although electronic health records (EHRs) have been widely used in secondary assessments, clinical documents are relatively less utilized owing to the lack of standardized clinical text frameworks across different institutions. Objective: This study aimed to develop a framework for processing unstructured clinical documents of EHRs and integration with standardized structured data. Methods: We developed a framework known as Staged Optimization of Curation, Regularization, and Annotation of clinical text (SOCRATex). SOCRATex has the following four aspects: (1) extracting clinical notes for the target population and preprocessing the data, (2) defining the annotation schema with a hierarchical structure, (3) performing document-level hierarchical annotation using the annotation schema, and (4) indexing annotations for a search engine system. To test the usability of the proposed framework, proof-of-concept studies were performed on EHRs. We defined three distinctive patient groups and extracted their clinical documents (ie, pathology reports, radiology reports, and admission notes). The documents were annotated and integrated into the Observational Medical Outcomes Partnership (OMOP)-common data model (CDM) database. The annotations were used for creating Cox proportional hazard models with different settings of clinical analyses to measure (1) all-cause mortality, (2) thyroid cancer recurrence, and (3) 30-day hospital readmission. Results: Overall, 1055 clinical documents of 953 patients were extracted and annotated using the defined annotation schemas. The generated annotations were indexed into an unstructured textual data repository. Using the annotations of pathology reports, we identified that node metastasis and lymphovascular tumor invasion were associated with all-cause mortality among colon and rectum cancer patients (both P=.02). The other analyses involving measuring thyroid cancer recurrence using radiology reports and 30-day hospital readmiss

关键词： natural language processing search engine data curation data management common data model

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Relationship between insomnia and rest time between shifts among shift workers: A multicenter cross-sectional study

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JOURNAL OF OCCUPATIONAL HEALTH 2022年第1期64卷 e12336-e12336页

作者： Sim, Juho Yun, Byungyoon Yoon, Jin-Ha Lee, Jiho Oh, Juyeon Cho, Ara Kim, Sung-Kyung Yonsei Univ Grad Sch Dept Publ Hlth Seoul South Korea Yonsei Univ Dept Prevent Med Coll Med Seoul South Korea Yonsei Univ Inst Occupat Hlth Coll Med Seoul South Korea Univ Ulsan Ulsan Univ Hosp Dept Occupat & Environm Med Coll Med Ulsan South Korea Yonsei Univ Grad Sch Publ Hlth Dept Occupat Hlth Seoul South Korea Yonsei Univ Wonju Coll Med Dept Occupat & Environm Med 20 Ilsan Ro Wonju 26426 Gangwon Do South Korea Yonsei Univ Wonju Coll Med Inst Occupat & Environm Med Wonju South Korea

Objectives A rest time of less than 11 h taken by a shift worker between shifts is defined as quick return (QR). QR is shown to decrease sleep time by virtue of decreasing rest time, diminishing sleepiness and exhaustion, and increasing the number of sick days taken by employees. Therefore, in this multicenter retrospective study, the association between QR and the incidence of insomnia was established using the night-shift questionnaire from the Korean Workers Health Examination-common data model. Methods Three hospitals collected the night-shift profiles and baseline demographic data of 33 669 workers between January 2015 and December 2017. The most recent date of examination was used for participants who had been examined multiple times at the same institution. We used multiple logistic regression to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). The pooled ORs were estimated using combined results from the three institutions. Results The proportion of men was higher than that of women in the QR group at each institution. The pooled ORs were computed using combined data from the three institutions. Workers who reported a QR had the highest risk of sleeplessness (OR, 1.21;95% CI, 1.12-1.31) compared to those workers who reported a slow return, after adjusting for possible confounders. Conclusions A substantial correlation was established between QR and insomnia using the CDM approach and data from multiple centers. This study may serve as a foundation for developing guidelines to enhance the health of shift workers and prevent occupational accidents.

关键词： common data model insomnia quick return rest time between time shift workers

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