Results 31 to 40 of about 2,261 (201)

Migrating longitudinal African mental health data from staging to the OMOP common data model within the INSPIRE network datahub [PDF]

Frontiers in Psychiatry
BackgroundThe standardization and integration of longitudinal mental health data from African cohort studies are critical in advancing research and informing policy.
Tathagata Bhattacharjee, Bylhah Mugotitsa, Bylhah Mugotitsa, Michael Ochola, Reinpeter Momanyi, Pauline Andeso, David Amadi, Dorothy Mailosi, Letisha Najjemba, Jay Greenfield, Kagiso Mabe, Emma Slaymaker, Jim Todd, Jim Todd, Agnes Kiragga, Agnes Kiragga, INSPIRE Network   +16 more
doaj   +2 more sources

Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network.

PLoS ONE, 2020
Background and purposeHemorrhagic transformation (HT) after cerebral infarction is a complex and multifactorial phenomenon in the acute stage of ischemic stroke, and often results in a poor prognosis.
Qiong Wang, Jenna M Reps, Kristin Feeney Kostka, Patrick B Ryan, Yuhui Zou, Erica A Voss, Peter R Rijnbeek, RuiJun Chen, Gowtham A Rao, Henry Morgan Stewart, Andrew E Williams, Ross D Williams, Mui Van Zandt, Thomas Falconer, Margarita Fernandez-Chas, Rohit Vashisht, Stephen R Pfohl, Nigam H Shah, Suranga N Kasthurirathne, Seng Chan You, Qing Jiang, Christian Reich, Yi Zhou   +22 more
doaj   +2 more sources

A dataset for mapping the Japanese drugs to RxNorm standard conceptsMendeley Data [PDF]

Data in Brief
Observational Health Data Sciences and Informatics (OHDSI) is an international research community dedicated to large-scale observational studies using real-world healthcare data.
Eizen Kimura, Yukinobu Kawakami, Shingo Inoue, Ai Okajima   +3 more
doaj   +2 more sources

Streamlining electronic medical record data extraction and validation in digital hospitals: A systematic review to identify optimal approaches and methods [PDF]

Learning Health Systems, Volume 9, Issue 4, October 2025.
Abstract Objective Extracting and curating data from large clinical information systems is challenging, and the optimal methodology is often unclear. This review was to systematically investigate and appraise the research literature to assess existing methods used by healthcare organizations to extract data from the electronic medical record (EMR). The
Han Chang Lim, Howard Wong, Reji Philip, Anton Van Der Vegt, Kim‐Kwang Raymond Choo, Jason D. Pole, Clair Sullivan   +6 more
wiley   +2 more sources

Ferramentas OHDSI e a medicina de precisão: estudos PLE e PLP

, 2020
The SBCAS 2020 Short Course Book contains the texts of the tutorials selected and presented in this edition of the event. The book is organized into four chapters covering themes of software architecture, multisensory environments, tools in precision ...
M. T. Abrahão, P. J. Madril
semanticscholar   +3 more sources

5 ． Taking Advantage of the Global RWD Standard ―OMOP CDM and OHDSI―

Japanese Journal of Pharmacoepidemiology/Yakuzai ekigaku, 2022
T. Hiramatsu
semanticscholar   +2 more sources

Enhancing adverse drug reaction data quality in Canada: A high-precision pipeline for medication name standardization and enrichment. [PDF]

PLoS ONE
BackgroundThe Canada Vigilance Adverse Reaction database is a vital pharmacovigilance tool, but its utility is severely limited by heterogeneity in medication nomenclature.
Niaz Chalabianloo, Sheikh S Abdullah, Mohammad Ali Omrani, Atefeh Jafari, Kamran Sedig, Flory Tsobo Muanda   +5 more
doaj   +2 more sources

352 Dermatology research with the Observational Health Data Sciences and Informatics (OHDSI) network [PDF]

Journal of Investigative Dermatology, 2021
T. Sivesind, T. Runion, M. Branda, L. Schilling, R. Dellavalle   +4 more
semanticscholar   +2 more sources

Building Interoperable FHIR-based Vocabulary Mapping Services: A Case Study of OHDSI Vocabularies and Mappings

Medinfo, 2017
The OHDSI Common Data Model (CDM) is a deep information model, in which its vocabulary component plays a critical role in enabling consistent coding and query of clinical data. The objective of the study is to create methods and tools to expose the OHDSI
Guoqian Jiang, Richard C. Kiefer, E. Prud'hommeaux, H. Solbrig   +3 more
semanticscholar   +4 more sources

Contextualising adverse events of special interest to characterise the baseline incidence rates in 24 million patients with COVID-19 across 26 databases: a multinational retrospective cohort studyResearch in context

EClinicalMedicine, 2023
Summary: Background: Adverse events of special interest (AESIs) were pre-specified to be monitored for the COVID-19 vaccines. Some AESIs are not only associated with the vaccines, but with COVID-19.
Erica A. Voss, Azza Shoaibi, Lana Yin Hui Lai, Clair Blacketer, Thamir Alshammari, Rupa Makadia, Kevin Haynes, Anthony G. Sena, Gowtham Rao, Sebastiaan van Sandijk, Clement Fraboulet, Laurent Boyer, Tanguy Le Carrour, Scott Horban, Daniel R. Morales, Jordi Martínez Roldán, Juan Manuel Ramírez-Anguita, Miguel A. Mayer, Marcel de Wilde, Luis H. John, Talita Duarte-Salles, Elena Roel, Andrea Pistillo, Raivo Kolde, Filip Maljković, Spiros Denaxas, Vaclav Papez, Michael G. Kahn, Karthik Natarajan, Christian Reich, Alex Secora, Evan P. Minty, Nigam H. Shah, Jose D. Posada, Maria Teresa Garcia Morales, Diego Bosca, Honorio Cadenas Juanino, Antonio Diaz Holgado, Miguel Pedrera Jiménez, Pablo Serrano Balazote, Noelia García Barrio, Selçuk Şen, Ali Yağız Üresin, Baris Erdogan, Luc Belmans, Geert Byttebier, Manu L.N.G. Malbrain, Daniel J. Dedman, Zara Cuccu, Rohit Vashisht, Atul J. Butte, Ayan Patel, Lisa Dahm, Cora Han, Fan Bu, Faaizah Arshad, Anna Ostropolets, Fredrik Nyberg, George Hripcsak, Marc A. Suchard, Dani Prieto-Alhambra, Peter R. Rijnbeek, Martijn J. Schuemie, Patrick B. Ryan   +63 more
doaj   +1 more source