Development Of Common Data Elements Research Articles

Application of the Delphi method to the development of common data elements for social drivers of health: A systematic scoping review.

Collaborative data science requires standardized, harmonized, interoperable, and ethically sourced data. Developing an agreed-upon set of elements requires capturing different perspectives on the importance and feasibility of the data elements through a consensus development approach. This study reports on the systematic scoping review of literature that examined the inclusion of diverse stakeholder groups and sources of social drivers of health variables in consensus-based common data element (CDE) sets. This systematic scoping review included sources from PubMed, Embase, CINAHL, WoS MEDLINE, and PsycINFO databases. Extracted data included the stakeholder groups engaged in the Delphi process, sources of CDE sets, and inclusion of social drivers data across 11 individual and 6 social domains. Of the 384 studies matching the search string, 22 were included in the final review. All studies involved experts with healthcare expertise directly relevant to the developed CDE set, and only six (27%) studies engaged health consumers. Literature reviews and expert input were the most frequent sources of CDE sets. Seven studies (32%) did not report the inclusion of any demographic variables in the CDE sets, and each demographic SDoH domain was included in at least one study with age and sex assigned at birth included in all studies, and social driver domains included only in four studies (18%). The Delphi technique engages diverse expert groups around the development of SDoH data elements. Future studies can benefit by involving health consumers as experts.

Exploring the similarities and differences of burn registers globally: Results from a data dictionary comparison study

IntroductionPooling and comparing data from the existing global network of burn registers represents a powerful, yet untapped, opportunity to improve burn prevention and care. There have been no studies investigating whether registers are sufficiently similar to allow data comparisons. It is also not known what differences exist that could bias analyses. Understanding this information is essential prior to any future data sharing. The aim of this project was to compare the variables collected in countrywide and intercountry burn registers to understand their similarities and differences. MethodsRegister custodians were invited to participate and share their data dictionaries. Inclusion and exclusion criteria were compared to understand each register population. Descriptive statistics were calculated for the number of unique variables. Variables were classified into themes. Definition, method, timing of measurement, and response options were compared for a sample of register concepts. Results13 burn registries participated in the study. Inclusion criteria varied between registers. Median number of variables per register was 94 (range 28 - 890), of which 24% (range 4.8 – 100%) were required to be collected. Six themes (patient information, admission details, injury, inpatient, outpatient, other) and 41 subthemes were identified. Register concepts of age and timing of injury show similarities in data collection. Intent, mechanism, inhalational injury, infection, and patient death show greater variation in measurement. ConclusionsWe found some commonalities between registers and some differences. Commonalities would assist in any future efforts to pool and compare data between registers. Differences between registers could introduce selection and measurement bias, which needs to be addressed in any strategy aiming to facilitate burn register data sharing. We recommend the development of common data elements used in an international minimum data set for burn injuries, including standard definitions and methods of measurement, as the next step in achieving burn register data sharing.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Hospital Course, Confounders, and Medications.

The convergence of an interdisciplinary team of neurocritical care specialists to organize the Curing Coma Campaign is the first effort of its kind to coordinate national and international research efforts aimed at a deeper understanding of disorders of consciousness (DoC). This process of understanding includes translational research from bench to bedside, descriptions of systems of care delivery, diagnosis, treatment, rehabilitation, and ethical frameworks. The description and measurement of varying confounding factors related to hospital care was thought to be critical in furthering meaningful research in patients with DoC. Interdisciplinary hospital care is inherently varied across geographical areas as well as community and academic medical centers. Access to monitoring technologies, specialist consultation (medical, nursing, pharmacy, respiratory, and rehabilitation), staffing resources, specialty intensive and acute care units, specialty medications and specific surgical, diagnostic and interventional procedures, and imaging is variable, and the impact on patient outcome in terms of DoC is largely unknown. The heterogeneity of causes in DoC is the source of some expected variability in care and treatment of patients, which necessitated the development of a common nomenclature and set of data elements for meaningful measurement across studies. Guideline adherence in hemorrhagic stroke and severe traumatic brain injury may also be variable due to moderate or low levels of evidence for many recommendations. This article outlines the process of the development of common data elements for hospital course, confounders, and medications to streamline definitions and variables to collect for clinical studies of DoC.

Design and Rationale for Common Data Elements for Clinical Research in Pediatric Critical Care Medicine.

Common data elements are a combination of a precisely defined question paired with a specified set of responses. Common data elements contribute to the National Institutes of Health-supported principle of Findable, Accessible, Interoperable, and Reusableness of research data. Routine use of Common data elements and standardized definitions within pediatric critical care research are likely to promote collaboration, improve quality, and consistency of data collection, improve overall efficiency of study or trial setup, and facilitate cross-study comparisons, meta-analysis, and merging of study cohorts. The purpose of this Pediatric Critical Care Medicine Perspective is to establish a road map for the development of multinational, multidisciplinary consensus-based common data elements that could be adapted for use within any pediatric critical care subject area. We describe a multistep process for the creation of "core domains" of research (e.g. patient outcomes, health-related conditions, or aspects of health) and the development of common data elements within each core domain. We define a tiered approach to data collection based on relevance of each common data element to future studies and clinical practice within the field of interest. Additionally, we describe the use of the Delphi methods to achieve consensus of these common data element documents using an international, multidisciplinary panel of experts.

Building a Research Data Repository for Chronic Condition Self-Management Using Harmonized Data.

Building nursing research data repositories with the goal of comparing and synthesizing results across numerous studies and public sharing of data is still in early stages of development. We describe the process of using common data elements (CDEs) to build a data repository for research addressing self-management of chronic conditions. Issues in the development of CDEs, lessons learned in the creation of a combined data set across seven studies of different chronic condition populations, and recommendations for creating and sharing harmonized nursing research data sets are provided. In 2014, at initiation of a National Institutes of Health-funded Centers of Excellence in Self-Management Research, our center investigators defined a set of CDEs for use in future center-funded pilot studies consisting of populations having different chronic conditions with the intent to combine the study data sets. Over the next 4 years, center investigators were provided with standardized codebooks and data collection protocols for applying the CDEs and data storage. Data from seven pilot studies were subsequently combined. Although each pilot study was small-with sample sizes ranging from 18 to 31 participants-our combined data set of 179 participants provides us with a sample size sufficient to conduct analyses that could not be done with the individual small samples alone. The research data repository addressing self-management of chronic conditions will soon be available for public sharing. Our experience demonstrates that, with careful, upfront planning and ongoing vigilant oversight, CDEs can be applied across studies consisting of different chronic condition populations to combine data sets to create research data repositories for public sharing.

Development of Common Data Elements for Use in Chiari Malformation Type I Clinical Research: An NIH/NINDS Project.

The management of Chiari I malformation (CMI) is controversial because treatment methods vary and treatment decisions rest on incomplete understanding of its complex symptom patterns, etiologies, and natural history. Validity of studies that attempt to compare treatment of CMI has been limited because of variable terminology and methods used to describe study subjects. The goal of this project was to standardize terminology and methods by developing a comprehensive set of Common Data Elements (CDEs), data definitions, case report forms (CRFs), and outcome measure recommendations for use in CMI clinical research, as part of the CDE project at the National Institute of Neurological Disorders and Stroke (NINDS) of the US National Institutes of Health. A working group, comprising over 30 experts, developed and identified CDEs, template CRFs, data dictionaries, and guidelines to aid investigators starting and conducting CMI clinical research studies. The recommendations were compiled, internally reviewed, and posted online for external public comment. In October 2016, version 1.0 of the CMI CDE recommendations became available on the NINDS CDE website. The recommendations span these domains: Core Demographics/Epidemiology; Presentation/Symptoms; Co-Morbidities/Genetics; Imaging; Treatment; and Outcome. Widespread use of CDEs could facilitate CMI clinical research trial design, data sharing, retrospective analyses, and consistent data sharing between CMI investigators around the world. Updating of CDEs will be necessary to keep them relevant and applicable to evolving research goals for understanding CMI and its treatment.

The Extremity Trauma Toolbox: Development of Common Data Elements for Research and Practice

Amputation has been one of the most costly and significant injuries among military service members, yet Military Treatment Facilities have not standardized their approaches nor developed a registry of data across sites. There isn't a common standard for evaluation for this population. This project sought to develop a comprehensive Toolbox of assessments to capture and track outcomes and establish Common Data Elements for use in research and practice with individuals with major extremity trauma. Selection of measures was based upon systematic review of measurement instruments used in the literature guided by two consensus meetings.

Functional Outcomes Following Burn Injury.

Major advances in functional recovery following burn injury over the last ten years include the development of conceptual framework for disability assessment and its application burn recovery, the description of the long-term outcomes in the burn population, and progress in basic science research leading to new treatments that improve long-term functional outcomes. Future tasks and challenges include the development of common data elements and standards for burn recovery in order to measure and optimize the path toward functional recovery. The development of patient-reported outcome measures with benchmarks for recovery over time has the potential to improve patient-provider communication and quality of patient-centered care. The study of burn recovery should include an examination of resiliency along with the study of disabilities following burn injury. Better understanding of the mechanisms, impact and modulation of hypermetabolism and inflammation following burn injury is essential to improve functional recovery. Continued basic science and clinical research must focus on scar modulation and skin replacements and address recalcitriant problems such as heterotopic ossification. Health tracking technologies should be leveraged to understand and optimize physical therapy interventions.

Commentary: A Gene-Based Association Method for Mapping Traits Using Reference Transcriptome Data.

Commentary: A Gene-Based Association Method for Mapping Traits Using Reference Transcriptome Data.

The Development of Common Data Elements for Spinal Stenosis

The Development of Common Data Elements for Spinal Stenosis

Toward Rigorous Data Harmonization in Cancer Epidemiology Research: One Approach.

Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.

Development of Common Data Elements to Provide Tele self-Care Management.

Background:Self-care management could empower patients to management of their health. Tele-health is the remote exchange of data between a patient and medical staff to improve healthcare quality.The aim:The aim of this research was developing common data elements to provide Tele self-care management and improve quality of care.Materials and methods:This was a cross-sectional study based on Delphi approach was done in 2011. Data was extracted by three sessions’ of conversation with 20 faculty members. Data had more than 75% agreement was inserted in minimum data element list, data with lower than 50% agreement was considered as failed data and whom was agreed between 50%-75% of participants were reconsidered for conversation until three sessions and after re-voting it was failed or accepted.Results:Results showed that self-care divides in three main categories and also some sub-categories including:1-Immunity and Safety with two subcategories (A: Prevention of Disease and B: Awareness and Knowledge about Disease); 2-Health Security and Maintains in six subcategories (A: Labratoary Test Results; B: Vital Data Monitoring; C: Rehabilitation; D: Drug Information; E: Follow up and F: Dental Health), 3- Well-Being Education in four subcategories (A: Nutrition; B: Health Promotion; C: Life Style Improvement and D: Patient Activity).Discussion:Consideration of all aspects of self management including information about prevention of disease, knowledge about disease, laboratory test result, vital signs monitoring, rehabilitation, drug information, follow up, dental health, nutrition, health promotion, life style improvement and patient activities is necessary.

Design and utilization of the colorectal and pancreatic neoplasm virtual biorepository: An early detection research network initiative

Background: The Early Detection Research Network (EDRN) colorectal and pancreatic neoplasm virtual biorepository is a bioinformatics-driven system that provides high-quality clinicopathology-rich information for clinical biospecimens. This NCI-sponsored EDRN resource supports translational cancer research. The information model of this biorepository is based on three components: (a) development of common data elements (CDE), (b) a robust data entry tool and (c) comprehensive data query tools. Methods: The aim of the EDRN initiative is to develop and sustain a virtual biorepository for support of translational research. High-quality biospecimens were accrued and annotated with pertinent clinical, epidemiologic, molecular and genomic information. A user-friendly annotation tool and query tool was developed for this purpose. The various components of this annotation tool include: CDEs are developed from the College of American Pathologists (CAP) Cancer Checklists and North American Association of Central Cancer Registries (NAACR) standards. The CDEs provides semantic and syntactic interoperability of the data sets by describing them in the form of metadata or data descriptor. The data entry tool is a portable and flexible Oracle-based data entry application, which is an easily mastered, web-based tool. The data query tool facilitates investigators to search deidentified information within the warehouse through a "point and click" interface thus enabling only the selected data elements to be essentially copied into a data mart using a dimensional-modeled structure from the warehouse′s relational structure. Results: The EDRN Colorectal and Pancreatic Neoplasm Virtual Biorepository database contains multimodal datasets that are available to investigators via a web-based query tool. At present, the database holds 2,405 cases and 2,068 tumor accessions. The data disclosure is strictly regulated by user′s authorization. The high-quality and well-characterized biospecimens have been used in different translational science research projects as well as to further various epidemiologic and genomics studies. Conclusions: The EDRN Colorectal and Pancreatic Neoplasm Virtual Biorepository with a tangible translational biomedical informatics infrastructure facilitates translational research. The data query tool acts as a central source and provides a mechanism for researchers to efficiently query clinically annotated datasets and biospecimens that are pertinent to their research areas. The tool ensures patient health information protection by disclosing only deidentified data with Institutional Review Board and Health Insurance Portability and Accountability Act protocols.

An informatics supported web-based data annotation and query tool to expedite translational research for head and neck malignancies.

BackgroundThe Specialized Program of Research Excellence (SPORE) in Head and Neck Cancer neoplasm virtual biorepository is a bioinformatics-supported system to incorporate data from various clinical, pathological, and molecular systems into a single architecture based on a set of common data elements (CDEs) that provides semantic and syntactic interoperability of data sets.ResultsThe various components of this annotation tool include the Development of Common Data Elements (CDEs) that are derived from College of American Pathologists (CAP) Checklist and North American Association of Central Cancer Registries (NAACR) standards. The Data Entry Tool is a portable and flexible Oracle-based data entry device, which is an easily mastered web-based tool. The Data Query Tool helps investigators and researchers to search de-identified information within the warehouse/resource through a "point and click" interface, thus enabling only the selected data elements to be essentially copied into a data mart using a multi dimensional model from the warehouse's relational structure.The SPORE Head and Neck Neoplasm Database contains multimodal datasets that are accessible to investigators via an easy to use query tool. The database currently holds 6553 cases and 10607 tumor accessions. Among these, there are 965 metastatic, 4227 primary, 1369 recurrent, and 483 new primary cases. The data disclosure is strictly regulated by user's authorization.ConclusionThe SPORE Head and Neck Neoplasm Virtual Biorepository is a robust translational biomedical informatics tool that can facilitate basic science, clinical, and translational research. The Data Query Tool acts as a central source providing a mechanism for researchers to efficiently find clinically annotated datasets and biospecimens that are relevant to their research areas. The tool protects patient privacy by revealing only de-identified data in accordance with regulations and approvals of the IRB and scientific review committee.

The development of common data elements for a multi-institute prostate cancer tissue bank: the Cooperative Prostate Cancer Tissue Resource (CPCTR) experience.

BackgroundThe Cooperative Prostate Cancer Tissue Resource (CPCTR) is a consortium of four geographically dispersed institutions that are funded by the U.S. National Cancer Institute (NCI) to provide clinically annotated prostate cancer tissue samples to researchers. To facilitate this effort, it was critical to arrive at agreed upon common data elements (CDEs) that could be used to collect demographic, pathologic, treatment and clinical outcome data.MethodsThe CPCTR investigators convened a CDE curation subcommittee to develop and implement CDEs for the annotation of collected prostate tissues. The draft CDEs were refined and progressively annotated to make them ISO 11179 compliant. The CDEs were implemented in the CPCTR database and tested using software query tools developed by the investigators.ResultsBy collaborative consensus the CPCTR CDE subcommittee developed 145 data elements to annotate the tissue samples collected. These included for each case: 1) demographic data, 2) clinical history, 3) pathology specimen level elements to describe the staging, grading and other characteristics of individual surgical pathology cases, 4) tissue block level annotation critical to managing a virtual inventory of cases and facilitating case selection, and 5) clinical outcome data including treatment, recurrence and vital status. These elements have been used successfully to respond to over 60 requests by end-users for tissue, including paraffin blocks from cases with 5 to 10 years of follow up, tissue microarrays (TMAs), as well as frozen tissue collected prospectively for genomic profiling and genetic studies. The CPCTR CDEs have been fully implemented in two major tissue banks and have been shared with dozens of other tissue banking efforts.ConclusionThe freely available CDEs developed by the CPCTR are robust, based on "best practices" for tissue resources, and are ISO 11179 compliant. The process for CDE development described in this manuscript provides a framework model for other organ sites and has been used as a model for breast and melanoma tissue banking efforts.

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

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 multi-disciplinary 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.