The development and deployment of Common Data Elements for tissue banks for translational research in cancer – An emerging standard based approach for the Mesothelioma Virtual Tissue Bank

Mohanty, Sambit K.; Mistry, Amita T; Amin, Waqas; Parwani, Anil V.; Pople, Andrew K; Schmandt, Linda; Winters, Sharon; Milliken, Erin L.; Kim, Paula; Whelan, Nancy; Farhat, Ghada N.; Melamed, Jonathan; Taioli, Emanuela; Dhir, Rajiv; Pass, Harvey I.; Becich, Michael J.

doi:10.1186/1471-2407-8-91

Cited by 45 publications

(41 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, Office of Management and Budget (OMB) and de facto standards for patient characteristics (e.g., race, ethnicity, and demographics) will be applied, with the goal of limiting unnecessary variations of questions that have relevance across all rare disease registries. New and forthcoming pilot projects sponsored by HL7, caBIG, and CDISC that demonstrate the use of common data elements and shared conceptual domain models for specific therapeutic areas (e.g., cardiovascular, tuberculosis, and diabetes) will also be monitored and explored as a source of standardized questions that could be incorporated into the library and re-used for rare disease registry data collection (Gao, Zhang, Xie, Zhang, & Hu, 2006; Mohanty, et al, 2008; Winget, et al, 2003). Standardized health data from CDC’s PHIN Shared Vocabulary will be searched for value sets standardized for a variety of use cases.…”

Section: Relevant Standardsmentioning

confidence: 99%

[RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases

Richesson

Shereff

Andrews

2010

Journal of Library Metadata

View full text Add to dashboard Cite

Patient registries are important for understanding the causes and origins of rare diseases and estimating their impact; and they may prove critical developing new diagnostics and therapeutics. This paper introduces the [RD] PRISM resource , an NIH-funded project to develop a library of standardized question and answer sets to support rare disease research. The paper presents a project case-driven plan for creating a new registry using questions from an existing related registry, revising and expanding an existing registry, and showing interoperability of data collected from different registries and data sources. Each of the use cases involves the retrieval of indexed questions for re-use. Successful retrieval of questions can facilitate their re-use in registries, meaning new registries can be implemented more quickly, and the use of "standard" questions can be facilitated. The paper further discusses issues involved in encoding the sets with relevant data standards for interoperability and indexing encoded sets with metadata for optimal retrievability.

show abstract

Section: Relevant Standardsmentioning

confidence: 99%

[RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases

Richesson

Shereff

Andrews

2010

Journal of Library Metadata

View full text Add to dashboard Cite

show abstract

“…Three papers focus on the need to standardize data collection by applying common data elements. [88][89][90] Seven papers 27,40,49,[91][92][93][94] highlight the challenges associated with collecting and analyzing data from multiple sites and informatics platforms, such as the differences in the data collected for clinical use versus research use, 27 variances between the functionality of different EHRs, 91 lack of standardization in how data are reported among multiple data sources, 40,49,92,93 and difficulty in implementing standardization efforts after systems are operational. 94…”

Section: Emerging Themes the Need For Standardizationmentioning

confidence: 99%

Building the Informatics Infrastructure for Comparative Effectiveness Research (CER)

et al. 2012

View full text Add to dashboard Cite

One hundred thirty-two articles were selected for inclusion in the review. Of these, 88 articles are the focus of the discussion in this paper. Three types of articles were identified, including papers that: (1) provide historical context or frameworks for using clinical informatics for research, (2) describe platforms and projects, and (3) discuss issues, challenges, and applications of natural language processing. In addition, 2 cross-cutting themes emerged: the challenges of conducting research in the absence of standardized ontologies and data collection; and unique data governance concerns related to the transfer, storage, deidentification, and access to electronic clinical data. Finally, the authors identified several current gaps on important topics such as the use of clinical informatics for cohort identification, cloud computing, and single point access to research data.

show abstract

“…There are few resources for methodology of CDE development. [45][46][47] One CDE project that is specifically focused on diabetes at the point of capture (i.e., EHR) is the Diabetes Data Strategy (Diabe-DS) demonstration project. 48,49 The project was formed in early 2009 in the HL7 EHR Working Group (with representatives from academia, professional societies, government, EHR developers, and pharmaceutical industry) to develop a repeatable process that identifies important data elements for clinical care and secondary use.…”

Section: Content Standards: Important "Common" Diabetes Data Elementsmentioning

confidence: 99%

Data Standards in Diabetes Patient Registries

Richesson

2011

J Diabetes Sci Technol

View full text Add to dashboard Cite

Widespread adoption of electronic health records (EHRs) and expansion of patient registries present opportunities to improve patient care and population health and advance translational research. However, optimal integration of patient registries with EHR functions and aggregation of regional registries to support national or global analyses will require the use of standards. Currently, there are no standards for patient registries and no content standards for health care data collection or clinical research, including diabetes research. Data standards can facilitate new registry development by supporting reuse of well-defined data elements and data collection systems, and they can enable data aggregation for future research and discovery. This article introduces standardization topics relevant to diabetes patient registries, addresses issues related to the quality and use of registries and their integration with primary EHR data collection systems, and proposes strategies for implementation of data standards in diabetes research and management.

show abstract

The development and deployment of Common Data Elements for tissue banks for translational research in cancer – An emerging standard based approach for the Mesothelioma Virtual Tissue Bank

Cited by 45 publications

References 10 publications

[RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases

[RD] PRISM Library: Patient Registry Item Specifications and Metadata for Rare Diseases

Building the Informatics Infrastructure for Comparative Effectiveness Research (CER)

Data Standards in Diabetes Patient Registries

Contact Info

Product

Resources

About