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Exploring a common data element for International Research in Long-Term Care Homes: A Measure for Evaluating Nursing Supervisor Effectiveness

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GERONTOLOGY AND GERIATRIC MEDICINE 2020年 6卷 2333721420979812页

作者： McGilton, Katherine S. Backman, Annica Boscart, Veronqiue Chu, Charlene Gea Sanchez, Montserrat Irwin, Constance Meyer, Julienne Spilsbury, Karen Zheng, Nancy Zuniga, Franziska KITE Toronto Rehabil Inst UHN 550 Univ Ave Toronto ON Canada Univ Toronto Toronto ON Canada Umea Univ Umea Sweden Conestoga Coll Kitchener ON Canada Univ Lleida Lleida Spain Univ London London England Univ Leeds Leeds W Yorkshire England Univ Basel Basel Switzerland

The aim of this study is to recommend a common data element (CDE) to measure supervisory effectiveness of staff working in LTC homes that can be used in international research. Supervisory effectiveness can serve as a CDE in an effort to establish an international, person-centered LTC research infrastructure in accordance with the aims of the WE-THRIVE group (Worldwide elements to Harmonize Research in Long Term Care Living Environments). A literature review was completed and then a panel of experts independently reviewed and prioritized appropriateness of the measures with mindfulness of their potential applications to international LTC settings. The selection of a recommended CDE measure was guided by the WE-THRIVE group's focus on capacity rather than deficits, the expected availability of internationally comparable data and the goal to provide a short, ecologically viable measurement, specifically for low- and middle-income countries. Two measures were considered as the CDE for supervisory effectiveness, Benjamin Rose Relationship Scale and the Supervisory Support Scale;however, given that the latter measure has been translated in Spanish and Chinese and has been tested with nursing assistants in both of these countries with good psychometric properties, our group recommends it as the CDE going forward.

关键词： long term care nursing supervisor effectiveness common data element international research

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common data elements and data management: Remedy to cure underpowered preclinical studies

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EPILEPSY RESEARCH 2017年 129卷 87-90页

作者： Lapinlampi, Niina Melin, Esbjorn Aronica, Eleonora Bankstahl, Jens P. Becker, Albert Bernard, Cristophe Gorter, Jan A. Grohn, Olli Lipsanen, Anu Lukasiuk, Katarzyna Loescher, Wolfgang Paananen, Jussi Ravizza, Teresa Roncon, Paolo Simonato, Michele Vezzani, Annamaria Kokaia, Merab Pitkanen, Asla Univ Eastern Finland Dept Neurobiol AI Virtanen Inst Mol Sci POB 1627 FI-70211 Kuopio Finland Lund Univ Epilepsy Ctr Wallenberg Neurosci Ctr Lund Sweden Univ Amsterdam Dept Neuro Pathol Acad Med Ctr Amsterdam Netherlands Univ Amsterdam Ctr Neurosci Swammerdam Inst Life Sci Amsterdam Netherlands Stichting Epilepsie Instellingen Nederland Heemstede Netherlands Hannover Med Sch Dept Nucl Med Hannover Germany Univ Bonn Translat Epilepsy Res Sect Med Ctr Bonn Germany Univ Aix Marseille Marseille France Polish Acad Sci Nencki Inst Expt Biol Lab Epileptogenesis Warsaw Poland Univ Vet Med Dept Pharmacol Toxicol & Pharm Hannover Germany Univ Eastern Finland Inst Biomed Kuopio Finland Mario Negri Inst Pharmacol Res Dept Neurosci Expt Neurol Milan Italy Univ Ferrara Milan Italy Univ Vita Salute San Raffaele Milan Italy

Lack of translation of data obtained in preclinical trials to clinic has kindled researchers to develop new methodologies to increase the power and reproducibility of preclinical studies. One approach relates to harmonization of data collection and analysis, and has been used for a long time in clinical studies testing anti-seizure drugs. EPITARGET is a European Union FP7-funded research consortium composed of 18 partners from 9 countries. Its main research objective is to identify biomarkers and develop treatments for epileptogenesis. As the first step of harmonization of procedures between laboratories, EPITARGET established working groups for designing project-tailored common data elements (CDEs) and case report forms (CRFs) to be used in data collection and analysis. Eight major modules of CRFs were developed, presenting >1000 data points for each animal. EPITARGET presents the first single-project effort for harmonization of preclinical data collection and analysis in epilepsy research. EPITARGET is also anticipating the future challenges and requirements in a larger-scale preclinical harmonization of epilepsy studies, including training, data management expertise, cost, location, data safety and continuity of data repositories during and after funding period, and incentives motivating for the use of CDEs. (C) 2016 Elsevier B.V. All rights reserved.

关键词： common data element database data management Epileptogenesis Epilepsy

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Development of common data elements: the experience of and recommendations from the early detection research network

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2003年第1期70卷 41-48页

作者： Winget, MD Baron, JA Spitz, MR Brenner, DE Warzel, D Kincaid, H Thornquist, M Feng, ZD Fred Hutchinson Canc Res Ctr Canc Prevent Res Program Seattle WA 98109 USA Dartmouth Coll Hitchcock Med Ctr Dartmouth Med Sch Dept Community & Family Med Hanover NH 03756 USA Univ Texas MD Anderson Canc Ctr Dept Epidemiol Houston TX 77030 USA Univ Michigan Sch Med Dept Internal Med Ann Arbor MI USA NCI Ctr Bioinformat Bethesda MD 20892 USA

There have been an increasing number of large research consortia in recent years funded by the National Cancer Institute (NCI) to facilitate multi-disciplinary, multi-institutional cancer research. Some of these consortia have central data collection plans similar to a multi-center clinical trial whereas others plan to store data Locally and pool or share the data at a later date. Regardless of the goal of the consortium, there is a need to standardize the way certain data are collected and stored, transferred, or reported across the institutions involved. This communication is a report of the process and current status of the development of common data elements (CDEs) by the Early Detection Research Network (EDRN). The development of the CDEs involved several stages with each stage requiring input from multidisciplinary experts in oncology, epidemiology, biostatistics, pathology, informatics, and study coordination. An effort was made to be consistent with other consortia developing similar CDEs and to follow data standards when available. Initial focus was on identifying the minimum data that would be necessary to collect on all EDRN study participants and EDRN specimens. There are currently CDEs in the development or pilot phase for eight different organ sites and 13 different types of specimen procurements and plans to develop CDEs for 12 or more additional types of specimens. (C) 2003 Elsevier Science Ireland Ltd. All rights reserved.

关键词： early detection research network common data element cancer

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data Collection Variability Across Neonatal Hypoxic-Ischemic Encephalopathy Registries

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JOURNAL OF PEDIATRICS 2025年 279卷 114476-114476页

作者： Peeples, Eric S. Mietzsch, Ulrike Molloy, Eleanor Deveber, Gabrielle Mohammad, Khorshid Soul, Janet S. Guez-Barber, Danielle Pilon, Betsy Chau, Vann Bonifacio, Sonia Afifi, Jehier Craig, Alexa Wintermark, Pia Univ Nebraska Med Ctr Dept Pediat Omaha NE USA Childrens Nebraska Div Neonatol Omaha NE USA Child Hlth Res Inst Omaha NE USA Univ Washington Sch Med Dept Pediat Seattle WA USA Seattle Childrens Hosp Div Neonatol Seattle WA USA Trinity Coll Dublin Dept Pediat Dublin Ireland Childrens Hosp Ireland Crumlin & Tallaght Dublin Ireland Hosp Sick Children Toronto ON Canada Univ Toronto Dept Pediat Toronto ON Canada Univ Calgary Dept Pediat Calgary AB Canada Boston Childrens Hosp Div Pediat Neurol Boston MA USA Harvard Med Sch Dept Pediat Cambridge MA USA Childrens Hosp Colorado Aurora CO USA Univ Colorado Dept Pediat Aurora CO USA Hope HIE West Bloomfield MI USA Lucile Packard Childrens Hosp Palo Alto CA USA Stanford Univ Sch Med Dept Pediat Stanford CA USA Dalhousie Univ Dept Pediat Halifax NS Canada Barbara Bush Childrens Hosp Maine Med Ctr Portland ME USA Tufts Univ Sch Med Dept Pediat Boston MA USA McGill Univ Dept Pediat Montreal PQ Canada Montreal Childrens Hosp Montreal PQ Canada

Objective To assess variability among data elements collected among existing neonatal hypoxic-ischemic encephalopathy (HIE) data registries worldwide and to determine the need for future harmonization of standard common data elements. Study design This was a cross-sectional study of data elements collected from current or recently employed HIE registry data forms. Registries were identified by literature search and email inquiries to investigators worldwide. data elements were categorized by group consensus. Results A total of 1281 data elements were abstracted from 22 registries based in 14 countries, including 3 middle-income countries. Registries had a median of 106.5 distinct data elements per registry (range 59-458). The most commonly collected data were related to pregnancy, therapeutic hypothermia, and short-term hospital outcomes. The least consistently collected data were laboratory values other than acid/base status values. Only 4 variables were consistently collected in every registry. Five registries included neurodevelopmental follow-up fields and 5 others linked their data to a separate follow-up registry. Conclusion Many HIE registries are collecting patient data around the world, but there is considerable variability in the number, type, and format of data collected. Future attempts to develop standard common data elements to harmonize data collection globally will be crucial to facilitate worldwide collaboration and to optimize management and outcome of neonatal HIE. (J Pediatr2025;279:114476).

关键词： common data elements harmonization perinatal asphyxia therapeutic hypothermia CDE common data element ECMO Extracorporeal membrane oxygenation HIC High-income country HIE Hypoxic-ischemic encephalopathy LMIC Low- and middle-income countries NE Neonatal encephalopathy PA Perinatal asphyxia TH Therapeutic hypothermia

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Scoping review to develop common data elements for lumbar spinal stenosis

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SPINE JOURNAL 2017年第7期17卷 1045-1057页

作者： Heinemann, Allen Raad, Jason Akuthota, Venu Segal, Neil Nitsch, Kristian P. Rho, Monica Chan, Leighton Casey, Ellen Press, Joel Sowa, Gwendolyn Moore, Jennifer Northwestern Univ Feinberg Sch Med 303 E Chicago Ave Chicago IL 60611 USA Rehabil Inst Chicago 345 E Super St Chicago IL 60611 USA Edward Hines Jr VA Hosp 5000 S 5th Ave Hines IL 60141 USA Univ Colorado 1800 Grant StSuite 800 Denver CO 80203 USA Univ Kansas 1450 Jayhawk Blvd Lawrence KS 66045 USA IIT 3300 South Fed St Chicago IL 60616 USA NIH Clin Ctr 10 Ctr Dr Bethesda MD 20814 USA Drexel Univ Coll Med 2900 W Queen Lane Philadelphia PA 19129 USA Univ Pittsburgh Med Ctr 200 Lothrop St Pittsburgh PA 15213 USA

BACKGROUND CONTEXT: common data elements (CDE) represent an important tool for understanding and classifying health outcomes across settings. Although CDEs have been developed for a number of disorders, to date CDEs for lumbar spinal stenosis (LSS) have not been fully developed. To facilitate the identification of CDEs and measures to assess them, this technical study leverages the International Classification of Functioning, Disability and Health (ICF), peer-reviewed research, and a panel of experts to identify CDEs specific to LSS. PURPOSE: The study aimed to define CDEs for disease characteristics and outcomes of LSS using the World Health Organization's ICF taxonomy, and to facilitate the selection of assessment instruments for research and clinical care. DESIGN: This is a scoping review using a modified Delphi approach with a technical expert panel composed of clinicians and scientists representing the academia, policy and advocacy stakeholders, and professional associations with expertise in LSS. METHODS: This is a scoping review to identify measures that assess LSS symptoms. Thirty-one subject matter experts (SMEs) prioritized ICF codes and evaluated instruments measuring specific domains. We used a modified Delphi technique to evaluate item-level content and achieve consensus. RESULTS: SMEs prioritized 53 ICF codes;3 received 100% endorsement, 27 received >= 90% endorsement, whereas the remaining 23 received >= 80% endorsement. Prioritized ICF codes represent diverse domains, including pain, activities and participation, and emotional well-being. The review yielded 58 instruments;we retained 24 for content analysis. CONCLUSIONS: The retained instruments adequately represent the ICFs activities and participation, and body function domains. Body structure and environmental factors were assessed infrequently. Adoption of these CDEs may guide clinical decision making and facilitate comparative effectiveness trials for interventions focused on LSS. (C) 2017 Elsev

关键词： Clinical assessment common data element International Classification of Functioning, Disability and Health Lower back pain Lumbar spinal stenosis Outcome measure

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Toward common data elements for International Research in Long-term Care Homes: Advancing Person-Centered Care

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JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION 2019年第5期20卷 598-603页

作者： Corazzini, Kirsten N. Anderson, Ruth A. Bowers, Barbara J. Chu, Charlene H. Edvardsson, David Fagertun, Anette Gordon, Adam L. Leung, Angela Y. M. McGilton, Katherine S. Meyer, Julienne E. Siegel, Elena O. Thompson, Roy Wang, Jing Wei, Sijia Wu, Bei Lepore, Michael J. Duke Univ Durham NC USA Univ N Carolina Chapel Hill NC 27515 USA Univ Wisconsin Madison WI USA Univ Toronto Toronto ON Canada La Trobe Univ Melbourne Vic Australia Umea Univ Umea Sweden Western Norway Univ Appl Sci Bergen Norway Univ Nottingham Nottingham England Hong Kong Polytech Univ Hong Kong Peoples R China Univ Hlth Network Toronto Rehabil Inst Toronto ON Canada City Univ London London England Univ Calif Davis Sacramento CA 95817 USA NYU New York NY USA RTI Int Washington DC USA

To support person-centered, residential long-term care internationally, a consortium of researchers in medicine, nursing, behavioral, and social sciences from 21 geographically and economically diverse countries have launched the WE-THRIVE consortium to develop a common data infrastructure. WE-THRIVE aims to identify measurement domains that are internationally relevant, including in low-, middle-, and high-income countries, prioritize concepts to operationalize domains, and specify a set of data elements to measure concepts that can be used across studies for data sharing and comparisons. This article reports findings from consortium meetings at the 2016 meeting of the Gerontological Society of America and the 2017 meeting of the International Association of Gerontology and Geriatrics, to identify domains and prioritize concepts, following best practices to identify common data elements (CDEs) that were developed through the US National Institutes of Health/National Institute of Nursing Research's CDEs initiative. Four domains were identified, including organizational context, workforce and staffing, person-centered care, and care outcomes. Using a nominal group process, WE-THRIVE prioritized 21 concepts across the 4 domains. Several concepts showed similarity to existing measurement structures, whereas others differed. Conceptual similarity (convergence;eg, concepts in the care outcomes domain of functional level and harm-free care) provides further support of the critical foundational work in LTC measurement endorsed and implemented by regulatory bodies. Different concepts (divergence;eg, concepts in the person-centered care domain of knowing the person and what matters most to the person) highlights current gaps in measurement efforts and is consistent with WE-THRIVE's focus on supporting resilience and thriving for residents, family, and staff. In alignment with the World Health Organization's call for comparative measurement work for health systems change, WE-

关键词： Long-term care nursing homes common data element cross cultural comparison person-centered care

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An exploratory study using an openEHR 2-level modeling approach to represent common data elements

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2016年第5期23卷 956-967页

作者： Lin, Ching-Heng Fann, Yang-Cheng Liou, Der-Ming Natl Yang Ming Univ Inst Biomed Informat Taipei Taiwan NINDS NIH Bldg 36Rm 4D04 Bethesda MD 20892 USA

Background and Objective In order to facilitate clinical research across multiple institutions, data harmonization is a critical requirement. common data elements (CDEs) collect data uniformly, allowing data interoperability between research studies. However, structural limitations have hindered the application of CDEs. An advanced modeling structure is needed to rectify such limitations. The openEHR 2-level modeling approach has been widely implemented in the medical informatics domain. The aim of our study is to explore the feasibility of applying an openEHR approach to model the CDE concept. Materials and Methods Using the National Institute of Neurological Disorders and Stroke General CDEs as material, we developed a semiautomatic mapping tool to assist domain experts mapping CDEs to existing openEHR archetypes in order to evaluate their coverage and to allow further analysis. In addition, we modeled a set of CDEs using the openEHR approach to evaluate the ability of archetypes to structurally represent any type of CDE content. Results Among 184 CDEs, 28% (51) of the archetypes could be directly used to represent CDEs, while 53% (98) of the archetypes required further development (extension or specialization). A comprehensive comparison between CDEs and openEHR archetypes was conducted based on the lessons learnt from the practical modeling. Discussion CDEs and archetypes have dissimilar modeling approaches, but the data structure of both models are essentially similar. This study proposes to develop a comprehensive structure to model CDE concepts instead of improving the structure of CED. Conclusion The findings from this research show that the openEHR archetype has structural coverage for the CDEs, namely the openEHR archetype is able to represent the CDEs and meet the functional expectations of the CDEs. This work can be used as a reference when improving CDE structure using an advanced modeling approach.

关键词： common data element openEHR archetype modeling approach

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Incorporation of the International Spinal Cord Injury data Set elements into the National Institute of Neurological Disorders and Stroke common data elements

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SPINAL CORD 2011年第1期49卷 60-64页

作者： Biering-Sorensen, F. Charlifue, S. DeVivo, M. J. Grinnon, S. T. Kleitman, N. Lu, Y. Odenkirchen, J. Rigshosp Ctr Neurosci Clin Spinal Cord Injuries DK-2100 Copenhagen Denmark Univ Copenhagen Copenhagen Denmark Craig Hosp Englewood CO USA Univ Alabama Dept Phys Med & Rehabil Birmingham AL USA KAI Res Inc Rockville MD USA NINDS NIH Bethesda MD 20892 USA

Objectives: To develop consistent variable names and a common database structure for the data elements in the International Spinal Cord Injury (SCI) data Sets. Setting: National Institute of Neurological Disorders and Stroke (NINDS) common data elements (CDE) Project and The Executive Committee of the International SCI Standards and data Sets committees (ECSCI). Methods: The NINDS CDE team creates a variable name for each defined data element in the various International SCI data Sets. Members of the ECSCI review these in an iterative process to make the variable names logical and consistent across the data sets. Following this process, the working group for the particular data set reviews the variable names, and further revisions and adjustments may be made. In addition, a database structure for each data set is developed allowing data to be stored in a uniform way in databases to promote sharing data from different studies. Results: The International SCI data Sets variable names and database specifications will be available through the web sites of the International Spinal Cord Society (http://***), the American Spinal Injury Association (http://***) and the NINDS CDE project web site (http://***). Conclusion: This process will continue as additional International SCI data Sets fulfill the requirements of the development and approval process and are ready for implementation. Spinal Cord (2011) 49, 60-64;doi: 10.1038/sc.2010.90;published online 24 August 2010

关键词： spinal cord injury International data Set variable names database specifications common data element

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IMI-CDE: an interactive interface for collaborative mapping of study variables to common data elements 10

IMI-CDE: an interactive interface for collaborative mapping ...

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10th IEEE International Conference on Healthcare Informatics (IEEE ICHI)

作者： Tao, Shiqiang Chou, Wei-Chun Li, Jianfu Du, Jingcheng Ram, Pritham Abeysinghe, Rashmie Xu, Hua Jiang, Xiaoqian Rose, Peter W. Ohno-Machado, Lucila Zhang, Guo-Qiang Univ Texas Hlth Sci Ctr Houston Dept Neurol Houston TX 77030 USA Univ Texas Hlth Sci Ctr Houston Sch Biomed Informat Houston TX 77030 USA Univ Calif San Diego San Diego Supercomp Ctr La Jolla CA 92093 USA Univ Calif San Diego Dept Biomed Informat La Jolla CA 92093 USA

ISBN: (数字)9781665468459

ISBN: (纸本)9781665468459

The National Institute of Health (NIH) launches the RADx Radical research collaboratives (RADx-rad) to advance new, non-traditional approaches for COVID-19 testing. RADx-rad projects are required to adopt common data elements (CDEs) to collect data to increase data interoperability. To overcome the challenges in finding appropriate CDEs for a wide range of study variables, we create a web application - IMI-CDE to ease the burden of mapping study variables to CDEs from researchers. IMI-CDE can automatically recommend CDE candidates for a study variable based on its name and description. Together with interactive mapping interfaces, IMI-CDE allows researchers to perform variable-CDE mapping with one mouse click. In addition, the IMI-CDE application supports users with multiple roles to work collaboratively on the mapping tasks. We have piloted the IMI-CDE with RADx-rad projects. 22 researchers from 8 different projects have started to use the IMI-CDE system for variable-CDE mappings. The beta-testing evaluators reported the system is intuitive, effective, and easy to use.

关键词： COVID-19 common data element CDE Mapping data Dictionary Study Variable CDE Recommendation

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common data elements collected among universities for sport-related concussion studies

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Injury Epidemiology 2018年第1期5卷 1页

作者： Yang, Jingzhen Peek-Asa, Corinne Noble, James M. Torner, James Schmidt, Paul Cooper, Martha L. Department of Pediatrics College of Medicine Ohio State University 700 Children’s Drive WB5403 Columbus 43205 OH United States Department of Occupational and Environmental Health College of Public Health University of Iowa IA United States Department of Neurology Taub Institute for Research on Alzheimer’s Disease and the Aging Brain and G.H. Sergievsky Center Columbia University New York NY United States Department of Epidemiology College of Public Health University of Iowa IA United States Department of Athletics University of Illinois Champaign IL United States Big Ten Academic Alliance Champaign IL United States Center for Injury Research and Policy The Research Institute at Nationwide Children’s Hospital Columbus United States

Background: Universities are increasingly implementing programs to effectively respond to and manage sport-related concussions (SRCs). One such effort is to develop common data elements (CDEs) and standardize data collection methods. The objectives of this study were to describe CDEs currently collected by Big Ten and Ivy League universities for SRC studies, and to compare the data collected with the core CDEs recommended by the National Institute of Neurological Disorders and Stroke (NINDS). Methods: We conducted an anonymous cross-sectional online survey among medical staff at the 14 Big Ten and 8 Ivy League universities (one per university) between September and October 2015. The survey instrument, including 9 questions corresponding to the concussion data collected before, during, and after a concussion, was developed and pilot-tested before field use. We analyzed patterns of the concussion CDEs being collected, including when, what, and how the data were collected and stored, and compared them with the NINDS' recommended core CDEs. Results: A total of 19 out of 22 universities were included, with 13 from Big Ten and 6 from Ivy-League universities. All 19 participating universities currently collected concussion data with athletes before, during, and after a concussion. Great similarities in data collection were observed at baseline and acutely post-concussion across participating universities. All 19 universities collected at least one of the ten recommended acute symptoms checklists, and 18 universities collected one of the four recommended core neuropsychological function cognitive measures. However, CDEs in the sub-acute and chronic timeframes were limited, with only 9 (47%) universities collecting post-concussion short to long term outcome data. While over 60% of universities collected and stored concussion data electronically, only 17% to 42% of data collected were readily available for research. Conclusions: Significant inter-institutional similarities in

关键词： College sports common data element Concussion

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