scholarly journals Development, Evaluation, and Implementation of a Pan-African Cancer Research Network: Men of African Descent and Carcinoma of the Prostate

2018 ◽  
pp. 1-14
Author(s):  
Caroline Andrews ◽  
Brian Fortier ◽  
Amy Hayward ◽  
Ruth Lederman ◽  
Lindsay Petersen ◽  
...  
Keyword(s):  
African Descent ◽  
Genomic Data ◽  
Buffy Coat ◽  
Sub Saharan Africa ◽  
Research Network ◽  
Inherited Disease ◽  
Multicenter Studies ◽  
Common Data Elements ◽  
Carcinoma Of The Prostate ◽  
Data Elements

Purpose Cancer of the prostate (CaP) is the leading cancer among men in sub-Saharan Africa (SSA). A substantial proportion of these men with CaP are diagnosed at late (usually incurable) stages, yet little is known about the etiology of CaP in SSA. Methods We established the Men of African Descent and Carcinoma of the Prostate Network, which includes seven SSA centers partnering with five US centers to study the genetics and epidemiology of CaP in SSA. We developed common data elements and instruments, regulatory infrastructure, and biosample collection, processing, and shipping protocols. We tested this infrastructure by collecting epidemiologic, medical record, and genomic data from a total of 311 patients with CaP and 218 matched controls recruited at the seven SSA centers. We extracted genomic DNA from whole blood, buffy coat, or buccal swabs from 265 participants and shipped it to the Center for Inherited Disease Research (Baltimore, MD) and the Centre for Proteomics and Genomics Research (Cape Town, South Africa), where genotypes were generated using the UK Biobank Axiom Array. Results We used common instruments for data collection and entered data into the shared database. Double-entered data from pilot participants showed a 95% to 98% concordance rate, suggesting that data can be collected, entered, and stored with a high degree of accuracy. Genotypes were obtained from 95% of tested DNA samples (100% from blood-derived DNA samples) with high concordance across laboratories. Conclusion We provide approaches that can produce high-quality epidemiologic and genomic data in multicenter studies of cancer in SSA.

scholarly journals Standard work tools for dynamic stereoelectroencephalography using ROSA: naming convention and perioperative planning

2021 ◽  
pp. 1-9
Author(s):  
Salma M. Bakr ◽  
Ajay Patel ◽  
Mohamed A. Zaazoue ◽  
Kathryn Wagner ◽  
Sandi K. Lam ◽  
...  
Keyword(s):  
Phase I ◽  
The United States ◽  
Multicenter Studies ◽  
Common Data Elements ◽  
Standard Work ◽  
Naming Convention ◽  
Depth Electrodes ◽  
Nursing Guidelines ◽  
Data Elements ◽  
Perioperative Planning

OBJECTIVEThe grid-based orthogonal placement of depth electrodes (DEs), initially defined by Jean Talairach and Jean Bancaud, is known as stereo-electroencephalography (sEEG). Although acceptance in the United States was initially slow, advances in imaging and technology have spawned a proliferation of North American epilepsy centers offering sEEG. Despite publications highlighting minimal access techniques and varied indications, standard work for phase I targeted DE has not been defined. In this article, the authors propose the term “dynamic sEEG” and define standard work tools and related common data elements to promote uniformity in the field.METHODSA multidisciplinary approach from July to August 2016 resulted in the production of 4 standard work tools for dynamic sEEG using ROSA: 1) a 34-page illustrated manual depicting a detailed workflow; 2) a planning form to collocate all the phase I data; 3) a naming convention for DEs that encodes the data defining it; and 4) a reusable portable perioperative planning and documentation board. A retrospective review of sEEG case efficiency was performed comparing those using standard work tools (between July 2016 and April 2017) with historical controls (between March 2015 and June 2016). The standard work tools were then instituted at another epilepsy surgery center, and the results were recorded.RESULTSThe process for dynamic sEEG was formally reviewed, including anesthesia, positioning, perioperative nursing guidelines, surgical steps, and postoperative care for the workflow using cranial fixation and ROSA-guided placement. There was a 40% improvement in time per electrode, from 44.7 ± 9.0 minutes to 26.9 ± 6.5 minutes (p = 0.0007) following the development and use of the manual, the naming convention, and the reusable portable perioperative planning and documentation board. This standardized protocol was implemented at another institution and yielded a time per electrode of 22.3 ± 4.4 minutes.CONCLUSIONSThe authors propose the term dynamic sEEG for stereotactic depth electrodes placed according to phase I workup data with the intention of converting to ablation. This workflow efficiency can be optimized using the standard work tools presented. The authors also propose a novel naming convention that encodes critical data and allows portability among providers. Use of a planning form for common data elements optimizes research, and global adoption could facilitate multicenter studies correlating phase I modality and seizure onset zone identification.

scholarly journals MOVING TOWARDS COMMON DATA ELEMENTS AND CORE OUTCOME MEASURES IN FRAILTY RESEARCH

2019 ◽  
pp. 1-9
Author(s):  
J. Muscedere ◽  
J. Afilalo ◽  
I. Araujo de Carvalho ◽  
M. Cesari ◽  
A. Clegg ◽  
...  
Keyword(s):  
Outcome Measures ◽  
Social Systems ◽  
Assessment Tools ◽  
Research Network ◽  
Core Outcome ◽  
Common Data Elements ◽  
For Profit ◽  
Aging Populations ◽  
Core Outcome Measures ◽  
Data Elements

With aging populations around the world, frailty is becoming more prevalent increasing the need for health systems and social systems to deliver optimal evidence based care. However, in spite of the growing number of frailty publications, high-quality evidence for decision making is often lacking. Inadequate descriptions of the populations enrolled including frailty severity and frailty conceptualization, lack of use of validated frailty assessment tools, utilization of different frailty instruments between studies, and variation in reported outcomes impairs the ability to interpret, generalize and implement the research findings. The utilization of common data elements (CDEs) and core outcome measures (COMs) in clinical trials is increasingly being adopted to address such concerns. To catalyze the development and use of CDEs and COMs for future frailty studies, the Canadian Frailty Network (www.cfn-nce.ca; CFN), a not-for-profit pan-Canadian nationally-funded research network, convened an international group of experts to examine the issue and plan the path forward. The meeting was structured to allow for an examination of current frailty evidence, ability to learn from other COMs and CDEs initiatives, discussions about specific considerations for frailty COMs and CDEs and finally the identification of the necessary steps for a COMs and CDEs consensus initiative going forward. It was agreed at the onset of the meeting that a statement based on the meeting would be published and herein we report the statement.

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

2003 ◽  
Vol 70 (1) ◽  
pp. 41-48 ◽  
Author(s):  
Marcy D. Winget ◽  
John A. Baron ◽  
Margaret R. Spitz ◽  
Dean E. Brenner ◽  
Denise Warzel ◽  
...  
Keyword(s):  
Early Detection ◽  
Research Network ◽  
Common Data Elements ◽  
Data Elements

scholarly journals TBI surveillance using the common data elements for traumatic brain injury: a population study

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Latha Ganti Stead ◽  
◽  
Aakash N Bodhit ◽  
Pratik Shashikant Patel ◽  
Yasamin Daneshvar ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Population Study ◽  
Common Data Elements ◽  
The Common ◽  
Data Elements

Abstract TP374: Data Linkage is Effective for Improving the Available Data for Stroke: An Example from the Australian Stroke Clinical Registry.

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Monique F Kilkenny ◽  
Helen M Dewey ◽  
Natasha A Lannin ◽  
Vijaya Sundararajan ◽  
Joyce Lim ◽  
...  
Keyword(s):  
Hospital Discharge ◽  
Hospital Discharge Data ◽  
Hospital Data ◽  
High Quality ◽  
Clinical Registry ◽  
Large Hospital ◽  
Common Data Elements ◽  
Discharge Data ◽  
Data Elements ◽  
Data Collections

Introduction: Multiple data collections can be a burden for clinicians. In 2009, the Australian Stroke Clinical Registry (AuSCR) was established by non-government and research organizations to provide quality of care data unavailable for acute stroke admissions. We show here the reliability of linking complimentary registry data with routinely collected hospital discharge data submitted to governmental bodies. Hypothesis: A high quality linkage with a > 90% rate is possible, but requires multiple personal identifiers common to each dataset. Methods: AuSCR identifying variables included date of birth (DoB), Medicare number, first name, surname, postcode, gender, hospital record number, hospital name and admission date. The Victorian Department of Health emergency department (ED) and hospital discharge linked dataset has most of these, with first name truncated to the first 3 digits, but no surname. Common data elements of AuSCR patients registered at a large hospital in Melbourne, Victoria (Australia) between 15 June 2009 and 31 December 2010 were submitted to undergo stepwise deterministic linkage. Results: The Victorian AuSCR sample had 818 records from 788 individuals. Three steps with 1) Medicare number, postcode, gender and DoB (80% matched); 2) hospital number/admit date; and 3) ED number/visit date were required to link AuSCR data with the ED and hospital discharge data. These led to an overall high quality linkage of >99% (782/788) of AuSCR patients, including 731/788 for ED records and 736/788 for hospital records. Conclusion: Multiple personal identifiers from registries are required to achieve reliable linkage to routinely collected hospital data. Benefits of these linked data include the ability to investigate a broader range of research questions than with a single dataset. Characters with spaces= 1941 (limit is 1950)

scholarly journals Preclinical common data elements (CDEs) for epilepsy: A joint ILAE/AES and NINDS translational initiative

2018 ◽  
Vol 3 ◽  
pp. 9-12 ◽  
Author(s):  
Helen E. Scharfman ◽  
Aristea S. Galanopoulou ◽  
Jacqueline A. French ◽  
Asla Pitkänen ◽  
Vicky Whittemore ◽  
...  
Keyword(s):  
Common Data Elements ◽  
Data Elements

scholarly journals Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
A. Anil Sinaci ◽  
Gokce B. Laleci Erturkmen ◽  
Suat Gonul ◽  
Mustafa Yuksel ◽  
Paolo Invernizzi ◽  
...  
Keyword(s):  
Clinical Research ◽  
Real Life ◽  
Critical Factor ◽  
Drug Surveillance ◽  
Safety Study ◽  
Data Interoperability ◽  
Common Data Elements ◽  
Lombardy Region ◽  
Research Activities ◽  
Data Elements

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

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