Abstract P192: National Institute of Neurological Disorders and Stroke Common Data Elements: Stroke Version 2.0 Recommendations

Introduction: The National Institute of Neurological Disorders and Stroke (NINDS) Common Data Element (CDE) project provides standardized data collection formats for neuroscience clinical research. Goals are to increase harmonization, efficiency, and data quality in studies, and facilitate collaboration through data sharing and analysis. Stroke-specific CDEs were developed in 2010. The Stroke Oversight Committee (OC) reviewed Core CDEs in 2015. Subarachnoid hemorrhage and unruptured cerebral aneurysms (SAH)-specific CDEs were developed in 2017. In 2018, the Stroke OC recommended that Stroke CDEs be updated to Version 2.0. Methods: NINDS in August 2018, convened the Stroke V2.0 Working Group (WG) consisting of over 50 international subject matter experts. Each domain-specific subgroup: Biospecimens, Biomarkers, and Laboratory Tests; Hospital Course and Acute Therapies; Imaging; Long Term Therapies; Medical History and Prior Health Status; Outcomes and Endpoints; Stroke Presentation and Vital Signs; and Stroke Types and Subtypes, reviewed Stroke V1.0 and SAH CDEs relevant to their purview. Subgroups met regularly to discuss updates to existing Stroke CDEs, addition of new instruments and case report forms (CRFs), and harmonization with SAH CDEs. Draft V2.0 recommendations were posted for public review from February 26 to April 8, 2020. The WG considered public feedback before V2.0 was finalized. Results: This comprehensive review led to updates across CDEs and additions to therapies, outcomes, and imaging domains including Imaging Acquisition and SAH Surgical/Procedural Interventions CRFs and Fugl-Meyer Assessment and PROMIS-29 outcome measures. Following review of 39 V1.0 Stroke outcome measures, 11 were reclassified. Stroke V2.0 CDE recommendations include revised and new template CRFs, data dictionaries, instrument informational documents and guidance documents. Stroke V2.0 was posted to the NINDS CDE website in summer 2020. Conclusions: Updates to the NINDS CDEs based on scientific advancements and user feedback ensure they remain a useful resource. The Stroke v2.0 CDEs provide a current tool for clinical investigators across research domains. NINDS encourages CDE use to standardize research data collection across studies.

Strengthening International Research in Long-Term Care: Recommended Common Data Elements to Support Clinical Staff Training

The purpose of this study is to develop candidate common data element (CDE) items related to clinical staff training in long-term care (LTC) homes that can be used to enable international comparative research. This paper is part of the WE-THRIVE ( Worldwide Elements to Harmonize Research in Long-Term Care Li ving Environments) group’s initiative which aims to improve international academic collaboration. We followed best practices to develop CDEs by conducting a literature review of clinical staff (i.e., Regulated Nurses, Health Care Aides) training measures, and convening a subgroup of WE-THRIVE experts to review the literature review results to develop suitable CDEs. The international expert panel discussed and critically reflected on the current knowledge gaps from the literature review results. The panel proposed three candidate CDEs which focused on the presence of and the measurement of training. These three proposed CDEs seek to facilitate international research as well as assist in policy and decision-making regarding LTC homes worldwide. This study is a critical first step to develop candidate CDE items to measure staff training internationally. Further work is required to get feedback from other researchers about the proposed CDEs, and assess the feasibility of these CDEs in high and low resourced settings.

Observations from the Data Integration and Imaging Informatics (DI-Cubed) Project

In this paper we explore extending the concept of common cross-study Common Data Element concepts beyond simple demographics to cover disease-specific concepts relevant to imaging. We test interactively linking the resulting database to the associated images in a federated manner. We examine the use of existing standards, not only for terminology, but for interchange of serialized data in forms familiar to imaging and clinical trials specialists and their dedicated systems. Our intent is to perform preliminary work to inform both the upcoming Imaging Data Commons specifically, as well as more general integration projects beyond imaging.

Abstract WP203: National Institute of Neurological Disorders and Stroke Common Data Elements: Public Review and Updates to the Stroke Recommendations

Objective: The National Institute of Neurological Disorders and Stroke (NINDS) initiated the Common Data Element (CDE) project to provide standardized clinical research data collection formats that increase the efficiency and effectiveness of studies and reduce start-up time, as well as improve data quality and facilitate and accelerate data sharing. In 2010, Stroke-specific CDEs were posted on the NINDS CDE website. The Stroke Oversight Committee (OC) reviewed Core CDEs in 2015; and in 2018, recommended that Stroke CDEs undergo a comprehensive review and update to Version 2.0. Background: In August 2018, a Stroke V2.0 Working Group (WG) consisting of over 50 worldwide subject matter experts was convened by NINDS. The WG was asked to review all current Stroke CDEs and subarachnoid hemorrhage and unruptured cerebral aneurysms (SAH) CDEs (developed in 2017) for harmonization and inclusion within Stroke V2.0. Methods: The Stroke V2.0 WG divided into eight domain-specific subgroups: Biospecimens, Biomarkers, and Laboratory Tests; Hospital Course and Acute Therapies; Imaging; Long Term Therapies; Medical History and Prior Health Status; Outcomes and Endpoints; Stroke Presentation and Vital Signs; and Stroke Types and Subtypes. Subgroups met regularly to review, revise and add to the existing Stroke CDEs based on developments in stroke research. Following an internal WG review, a public review of the draft updates will be held. The WG will consider public feedback before V2.0 is finalized. The Stroke OC plans to review the project status at the 2020 International Stroke Conference. Results: The Stroke V2.0 CDE recommendations will include updated and new template case report forms, data dictionaries, instrument informational documents and guideline documents. The updates will reflect the current state of science, streamline CDE recommendations, and incorporate SAH CDEs. Stroke V2.0 CDEs will be available on the NINDS CDE website in 2020. Conclusions: The NINDS CDEs are periodically revised as research progresses. Through the update of the Stroke CDEs to V2.0, the initiative strives to maintain the utility of CDEs as a valuable clinical research resource. NINDS encourages use of CDEs to standardize research data collection across studies.

Exploring a Common Data Element for International Research in Long-Term Care Homes: A Measure for Evaluating Nursing Supervisor Effectiveness

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.