Clinical Data Standards Research Articles

2024 ACC/AHA Key Data Elements and Definitions for Social Determinants of Health in Cardiology: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Data Standards.

2024 ACC/AHA Key Data Elements and Definitions for Social Determinants of Health in Cardiology: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Data Standards.

Accelerating pediatric Hodgkin lymphoma research: the Hodgkin Lymphoma Data Collaboration (NODAL).

Data commons have proven to be an indispensable avenue for advancing pediatric cancer research by serving as unified information technology platforms that, when coupled with data standards, facilitate data sharing. The Pediatric Cancer Data Commons, the flagship project of Data for the Common Good (D4CG), collaborates with disease-based consortia to facilitate development of clinical data standards, harmonization and pooling of clinical data from disparate sources, establishment of governance structure, and sharing of clinical data. In the interest of international collaboration, researchers developed the Hodgkin Lymphoma Data Collaboration and forged a relationship with the Pediatric Cancer Data Commons to establish a data commons for pediatric Hodgkin lymphoma. Herein, we describe the progress made in the formation of Hodgkin Lymphoma Data Collaboration and foundational goals to advance pediatric Hodgkin lymphoma research.

Cohort profile: Data standards for cardiac rehabilitation structure and processes for the SWEDEHEART cardiac rehabilitation (SWEDEHEART-CR) registry.

Data standards for quality registries should be evidence-based and follow guideline recommendations. To optimally monitor quality of care, not only patient-level variables, but also centre-level variables need to be included. Here we describe the development of variables to audit the structure and processes in cardiac rehabilitation for patients after myocardial infarction, and the resulting data standards to be implemented in the Swedish quality registry for cardiac disease, SWEDEHEART. The methodology used for the development of international clinical data standards for the European Unified Registries for Heart Care Evaluation and Randomised Trials (EuroHeart) was followed. Based on national guidelines for secondary prevention, candidate variables were prepared, after which a multiprofessional expert group on cardiac rehabilitation selected key variables and assured face validity. An external reference group had the role of peer reviewing, ascertaining content validity and test-retest reliability. The process has resulted in 30 data standards to be introduced into the SWEDEHEART cardiac rehabilitation registry and administered on centre-level biannually. The data standards include measures of human resources, centre requirements and process-based metrics. Including registry variables which audit centre-level structure and processes is essential to improve benchmarking and standardize monitoring of quality of care, covering both services provided and patient outcomes.

Implementing evidence-based clinical and business data standards in Australian private practice clinics is feasible.

To assess the feasibility of implementing data standards in Australian primary care dietetics practices. A mixed-methods pragmatic study of dietitians working in primary care. Using a four-point Likert scale, participants were surveyed on their baseline use of the 45 business and 33 clinical evidenced-based data standards. The content validity index and kappa statistic for each standard were calculated with a kappa statistic of 0.60-0.74 considered 'Good' and > 0.74 'Excellent'. After 4 weeks of assessment, dietitians were surveyed on the feasibility of implementing each standard and standards in total. Qualitative feedback on enablers and barriers to implementing standards was gathered and triangulated with interviews with select participants. Forty-five dietitians from every Australian state and territory completed both surveys (response rate: 100%). At baseline, 24% of business and 79% of clinical standards were rated 'Good' or 'Excellent' for current usage. The feasibility of implementing standards was rated 'Good' or 'Excellent for 86% of the business and 97% of the clinical standards. Software, training and time limitations are enablers and barriers to implementing standards. Embedding data standards within dietetics practices are feasible and have broad applicability for assessing outcomes of care.

2022 ACC/AHA Key Data Elements and Definitions for Chest Pain and Acute Myocardial Infarction: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Data Standards.

2022 ACC/AHA Key Data Elements and Definitions for Chest Pain and Acute Myocardial Infarction: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Data Standards.

Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study.

BackgroundA clinical decision support system (CDSS) is recognized as a technology that enhances clinical efficacy and safety. However, its full potential has not been realized, mainly due to clinical data standards and noninteroperable platforms.ObjectiveIn this paper, we introduce the common data model–based intelligent algorithm network environment (CANE) platform that supports the implementation and deployment of a CDSS.MethodsCDSS reasoning engines, usually represented as R or Python objects, are deployed into the CANE platform and converted into C# objects. When a clinician requests CANE-based decision support in the electronic health record (EHR) system, patients’ information is transformed into Health Level 7 Fast Healthcare Interoperability Resources (FHIR) format and transmitted to the CANE server inside the hospital firewall. Upon receiving the necessary data, the CANE system’s modules perform the following tasks: (1) the preprocessing module converts the FHIRs into the input data required by the specific reasoning engine, (2) the reasoning engine module operates the target algorithms, (3) the integration module communicates with the other institutions’ CANE systems to request and transmit a summary report to aid in decision support, and (4) creates a user interface by integrating the summary report and the results calculated by the reasoning engine.ResultsWe developed a CANE system such that any algorithm implemented in the system can be directly called through the RESTful application programming interface when it is integrated with an EHR system. Eight algorithms were developed and deployed in the CANE system. Using a knowledge-based algorithm, physicians can screen patients who are prone to sepsis and obtain treatment guides for patients with sepsis with the CANE system. Further, using a nonknowledge-based algorithm, the CANE system supports emergency physicians’ clinical decisions about optimum resource allocation by predicting a patient’s acuity and prognosis during triage.ConclusionsWe successfully developed a common data model–based platform that adheres to medical informatics standards and could aid artificial intelligence model deployment using R or Python.

2022 AHA/ACC Key Data Elements and Definitions for Cardiovascular and Noncardiovascular Complications of COVID-19: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards.

2022 AHA/ACC Key Data Elements and Definitions for Cardiovascular and Noncardiovascular Complications of COVID-19: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards.

Society for Maternal-Fetal Medicine Special Statement: Best-practice recommendations for ultrasound network connectivity

Prenatal ultrasound is an indispensable tool used by obstetrical care providers to assist in the everyday care of their pregnant patients. Alongside advancements in imaging, the electronic systems that support this technology have become more advanced. However, it is currently difficult for these individual systems to communicate with each other "out of the box." There is also minimal standardization of the type and format of data transmitted within these systems. Clinicians and system vendors must work collaboratively to create clinical and technical standards to serve as the foundation for increased interoperability among the various systems within each institutional network. Therefore, the Society for Maternal-Fetal Medicine Clinical Informatics Committee established an Ultrasound Electronic Health Record Subcommittee to facilitate collaboration between clinicians, including maternal-fetal medicine subspecialists, and ultrasound network component vendors. Based on the work of this subcommittee, the purpose of this document is to provide: (1) a basic understanding of ultrasound network architecture and capabilities, and (2) best-practice recommendations for electronic health record order design, obstetrical clinical data standards, and billing and coding practices.

Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice.

Next-generation sequencing (NGS) is rapidly expanding into routine oncology practice. Genetic variations in both the cancer and inherited genomes are informative for hereditary cancer risk, prognosis, and treatment strategies. Herein, we focus on the clinical perspective of integrating NGS results into patient care to assist with therapeutic decision making. Five key considerations are addressed for operationalization of NGS testing and application of results to patient care as follows: (1) NGS test ordering and workflow design; (2) result reporting, curation, and storage; (3) clinical consultation services that provide test interpretations and identify opportunities for molecularly guided therapy; (4) presentation of genetic information within the electronic health record; and (5) education of providers and patients. Several of these key considerations center on informatics tools that support NGS test ordering and referencing back to the results for therapeutic purposes. Clinical decision support tools embedded within the electronic health record can assist with NGS test utilization and identifying opportunities for targeted therapy including clinical trial eligibility. Challenges for project and change management in operationalizing NGS-supported, evidence-based patient care in the context of current information technology systems with appropriate clinical data standards are discussed, and solutions for overcoming barriers are provided.

P074 Crohn’s disease clinical data standards: Adoption and implementation to promote data sharing and reuse

Abstract Background Creation and adoption of clinical data standards will transform incompatible and disparate data into universal and illuminating information, facilitating discoveries that could have invaluable impact on Crohn’s Disease clinical research. Implementation of CDISC standards deliver on the promise of FAIR data through consistent organization and analysis that allow all researchers to leverage information from studies globally. Methods With support from The Leona M. and Harry B. Helmsley Charitable Trust and following the CDISC consensus-based standards development process, a team of Crohn’s disease and standards development experts was created to develop clinical data standards for Crohn’s disease.The CDISC standards development process consists of five stages: Results Free and publicly available data standards are anticipated to be available in May 2021 in the following areas: - Questionnaires, Ratings and Scales (including standard symptom measures, patient/investigator reported outcomes, and socio-economic measures) - Prior and Baseline, and On-Study Treatments (including response to prior treatment) - Disease Classification (location and phenotypic descriptions of the disease)- Endoscopy Assessments - Cross Section Imaging Assessments (including CT, MRI and Ultrasound) - Histopathology of Biopsy Samples - Biomarkers of Interest for Crohn’s Disease Conclusion Widespread promotion of the standards for researchers to adopt and implement is of highest importance. CDISC provides complementary education courses and implementation information to assist in adoption for academic teams new to CDISC standards. Widespread adoption of the standards will bring clarity to Crohn’s Disease data and will enable the accessibility, interoperability, and reusability of data (FAIR).

2021 ACC/AHA Key Data Elements and Definitions for Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Heart Failure).

2021 ACC/AHA Key Data Elements and Definitions for Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Heart Failure).

COLLABORATIVE DEVELOPMENT OF CROHN’S DISEASE CLINICAL DATA STANDARDS BY STANDARDS DEVELOPMENT AND CROHN’S DISEASE EXPERTS TO FOSTER DATA REVIEW, SHARING, AND REUSE

Abstract Background The ability to access expansive collections of well-curated biological, clinical, and behavioral data will propel scientific progress and enable the discoveries needed to improve treatments for human disease. Development and adoption of standards transform incompatible and disparate data into universal and illuminating information, facilitating discoveries that could have invaluable impact on Crohn’s disease clinical research. When standards are applied, data is collected, organized, and analyzed in a clear and consistent manner, allowing all researchers to leverage information from studies around the world. Required by the United States Food and Drug Administration (FDA) and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) and adopted by the world’s leading research organizations, CDISC standards enable the accessibility, interoperability, and reusability of data. CDISC standards addresses each step of the clinical research process to drive operational efficiencies within the organizations that use them, expedite the regulatory review process and reduce time to market. Methods With support from The Leona M. and Harry B. Helmsley Charitable Trust, CDISC formed a team of standards development and Crohn’s disease experts to follow our consensus-based, clinical data standards process, which consists of six stages: Scoping – Identification of development topics Concept Modeling – Deep dive understanding of topics Standards Development – Development of standards content Internal Review – Targeted review Public Review – User community review Publication – Freely available on the CDISC website Results The project Standards Development and Internal Review stages completed in September 2020, resulting in the following topics available for the Public Review stage. - Questionnaires, Ratings and Scales (including standard symptom measures, patient/investigator reported outcomes, and socio-economic measures) - Prior and Baseline, and On-Study Treatments (including response to prior treatment) - Disease Staging (location and phenotypic descriptions of the disease) - Endoscopy Assessments - Cross-section Imaging Assessments (including CT, MRI and Ultrasound) - Histopathology of Biopsy Samples - Biomarkers of Interest for Crohn’s Disease Conclusion To make the greatest impact on Crohn’s disease research, widespread promotion of the availability of the standards for researchers to adopt and implement to their data is of highest importance. CDISC provides complementary education courses and implementation information to assist in this adoption. Widespread adoption of the standards will bring clarity to Crohn’s disease data and will enable the accessibility, interoperability, and reusability of data, driving operational efficiencies, expediting regulatory review, and reducing time to market.

Review of Relative effectiveness assessments (REAs) of pharmaceuticals at the European network for health technology assessment (EUnetHTA): A first step towards a consolidated European perspective on comparative effectiveness & safety?

ObjectivesREAs from Joint Action (JA1−3) were reviewed and compared versus Health Technology Assessments (HTA) in France, Germany, UK, Italy. MethodsEUnetHTA REAs published until end of 2019 were identified. Leveraging information derived from the HTA bodies’ website key process (population; timing; national HTA bodies involved) and content characteristics (evidence base; comparative therapy, endpoints, subgroups) were determined and compared against national appraisals. ResultsAll twelve pharmaceutical EUnetHTA assessment finalized until end of 2019 were included with Ustekinumab being the most recent (October 2019) and Pazopanib the first assessment (September 2012). In all but three assessments EUnetHTA’s assessment did not cover the full EMA indication. Since JA3 time intervals between EMA approval and EUnetHTA assessment were < 80 days. Number of (co-)authoring HTA bodies ranged between 2 (in 6 REAs) and > 10 (Pazopanib). EUnetHTA did consider non – RCT evidence in 7 procedures; take a rather inclusive approach regarding appropriate comparative treatments; approach endpoints less restrictively than e.g. the German IQWiG/GBA; not apply a predetermined set of subgroups analyses. In seven REAs, national appraisal showed inhomogeneities across the 4 countries. National appraisals for Sotagliflozin and Ustekinumab were not yet available. ConclusionsA joint European HTA assessment has the potential to address the challenge of heterogeneity across the various national European HTA bodies and to determine joint European clinical development data standards that are aligned with regulatory requirements.

2020 AHA/ACC Key Data Elements and Definitions for Coronary Revascularization: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Coronary Revascularization).

Biykem Bozkurt, MD, FACC, FAHA, Chair Hani Jneid, MD, FACC, FAHA, Chair-Elect Srinath Adusumalli, MD, MSc, FACC Sana Al-Khatib, MD, MHS, FACC, FAHA[‖][1] H. Vernon Anderson, MD, FACC, FAHA[‖][1] Deepak L. Bhatt, MD, MPH, FACC, FAHA Bruce E. Bray, MD, FACC Grant Nigel Graham, MD, FACC

P108 The importance of developing consensus-driven clinical data standards for Crohn’s disease to amplify data

Abstract Background When CDISC standards are applied, data is collected, organised and analysed in a clear and consistent manner so that all researchers can leverage and share information from individuals and studies around the world. Required by the USA Food and Drug Administration (FDA) and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) and adopted by the world’s leading research organisations, CDISC standards enable the accessibility, interoperability, and reusability of data. Adopting CDISC standards is an invaluable investment that leads to more meaningful, more efficient research for your organisation and the entire global research community. Methods With support from The Leona M. and Harry B. Helmsley Charitable Trust and following the CDISC consensus-based standards development process, a team of Crohn’s disease and standards development experts was created to develop clinical data standards for Crohn’s disease. The CDISC standards development process consists of five stages: Results The project scoping stage completed in July 2019. The scoping team, consisting of Crohn’s disease clinical SMEs, identified the following topics that would most benefit from development of clinical data standards and to move into the concept modelling and standards development phases of the project: Package 1 Package 2 Endoscopy assessments The first package of data standards for Crohn’s disease will be available for Public Review in July 2020 and is anticipated to be published in Q1 2021 for use by researchers and industry. The second package of data standards will be available for Public Review in Q3 2020 with publication in Q2 2021. Conclusion CDISC’s vision is to encourage the global adoption of standards to leverage and realise the full potential of data and produce faster, more efficient research, paving the way for more breakthroughs in Crohn’s disease treatments, therapies and cures. ECCO attendees and the Crohn’s disease community are encouraged to participate in CDISC’s informational webinars and Public Review stages to foster all-inclusive development, approval and adoption of the data standards.

PCN432 EVALUATION OF MISSING DATA IMPUTATION STRATEGIES IN CLINICAL TRIAL AND EMR DATA USING STANDARDIZED DATA MODELS

Data missingness is a major challenge in clinical trials and observational real-world healthcare research.1 Studies often exclude records which contain incomplete data, but this strategy can introduce bias. Therefore, we evaluated the utility of different techniques for imputing missing data. Because biases tend to differ between randomized controlled trial and observational datasets,2 we conducted this assessment in both clinical trial and real-world datasets for Acute Myeloid Leukemia (AML). Evaluations of this sort are challenged by data presented in variable formats. 1 Thus, we used a standard data model to facilitate meaningful comparison across data types. Clinical trial data was derived from a pooled dataset of 7 clinical trials (n=719) for relapsed/refractory AML from a 2012-2017 Medidata archive of trials, created using CDISC SDTM. Real-world data was obtained from a US-based geographically representative oncology-focused electronic medical record dataset. We converted all datasets to the OMOP Common Data Model (v5) and used the SHYFT Strata platform to standardize application of imputation methods. We then artificially introduced missingness into the datasets. We applied widely-used3 imputation methods, including Predictive Mean Matching, K Nearest Neighbor, Iterative Imputer, and MICE to repeatedly generate values for the missing data. We evaluated quality of imputed values using standard approaches including RMSE, unsupervised classification error (UCE), and AUC scores. We observed variation in imputation method performance both within and between data sources consistent with previous reports. The use of a standardized data model enabled us to provide a robust evaluation of strategies and make reliable comparisons between the results on a faster timeline. Imputation techniques can significantly improve the informativeness of HEOR when appropriate methods are tested and applied. Clinical data standards such as the OMOP CDM are well suited to enable rigorous and repeatable methodological evaluations.

Clinical data standards and the new world of research science, technology, and data sources

Clinical data standards and the new world of research science, technology, and data sources

Correction to: 2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography) and the American Society of Echocardiography

HomeCirculation: Cardiovascular ImagingVol. 12, No. 8Correction to: 2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography) and the American Society of Echocardiography Free AccessCorrectionPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessCorrectionPDF/EPUBCorrection to: 2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography) and the American Society of Echocardiography Originally published20 Aug 2019https://doi.org/10.1161/HCI.0000000000000028Circulation: Cardiovascular Imaging. 2019;12:e000028In the article by Douglas et al, “2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography) and the American Society of Echocardiography,” which published ahead of print on June 24, 2019, and appears with the July 2019 issue of the journal (Circ Cardiovasc Imaging. 2019;12:e000027. doi: 10.1161/HCI.0000000000000027), several corrections were needed.On page 1, the title of the article read, “…(Writing Committee to Develop Cardiovascular Endpoints Data Standards)….” It has been updated to read, “…(Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography)….”On page 1, the citation for the article read, “…(Writing Committee to Develop Cardiovascular Endpoints Data Standards)….” It has been updated to read, “…(Writing Committee to Develop Clinical Data Standards for Transthoracic Echocardiography)….”On page 10, in Appendix 2, “Reviewer Relationships With Industry and Other Entities…,” the following information for Sofia C. Masri has been added:ReviewerRepresentationEmploymentConsultantSpeakers BureauOwnership/ Partnership/ PrincipalPersonal ResearchInstitutional, Organizational, or Other Financial BenefitExpert WitnessSofia C. MasriContent ReviewerUniversity of Washington Medical College—Assistant Professor of Medicine and CardiologyNoneNoneNoneNoneNoneNoneThese corrections have been made to the current online version of the article, which is available at https://www.ahajournals.org/doi/10.1161/HCI.0000000000000027. Previous Back to top Next FiguresReferencesRelatedDetailsCited By Khaniukov O, Sapozhnychenko L, Smolyanova O, Kovtun O and Doroshenko A (2020) THE INVOLVEMENT OF KIDNEYS IN PATIENTS WITH CHRONIC HEART FAILURE ISCHEMIC ETIOLOGY AND LIVER STEATOSIS, Bulletin of Problems Biology and Medicine, 10.29254/2077-4214-2020-2-156-174-178, 2:1, (174), . Zherko O and Shkrebneva E (2021) New score scale for assessing the risk of establishing chronic heart failure with preserved ejection fraction, Medical Visualization, 10.24835/1607-0763-939, 25:3, (83-96) August 2019Vol 12, Issue 8 Advertisement Article InformationMetrics © 2019 American Heart Association, Inc.https://doi.org/10.1161/HCI.0000000000000028 Originally publishedAugust 20, 2019 PDF download Advertisement

2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards) and the American Society of Echocardiography.

2019 ACC/AHA/ASE Key Data Elements and Definitions for Transthoracic Echocardiography: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards) and the American Society of Echocardiography.

692-P: Development and Adoption of CDISC Clinical Data Standards for Type 1 Diabetes (T1D)

Development and adoption of global, non-proprietary and platform-independent CDISC standards a) enables traceability from data collection through data analysis, b) improves data quality, c) reduces costs, d) streamlines processes facilitating data sharing, and e) enables reliable and accurate data reuse. CDISC collaborates with type 1 diabetes subject matter experts to lead a unique effort that brings academia and industry together to create T1D clinical data standards in the areas of pediatrics, devices, exercise, and prevention. The T1D team is tasked with developing standards for collection, tabulation, and analysis of the data by building on existing foundational diabetes standards. They will use a multiphase, consensus-driven process, that includes scoping key data concepts commonly used in T1D clinical studies. The Pediatrics and Devices team has identified several data concepts that would benefit from development of data standards: diabetic ketoacidosis, diabetes history, CGM data, insulin management, laboratory tests related to diabetes, and vital signs percentiles for pediatrics. The public review of the standards developed will be launched in Summer 2019. The Prevention and Exercise team has initiated the scoping process to identify the most urgent areas for standards development, which will be followed by modeling. The public review of these standards will commence beginning of 2020. As the project progresses, the T1D community is encouraged to participate in the informational webinars and public review stages, which will enable all-inclusive development and adoption of the resultant data standards. Factors involved in the adoption of clinical data standards within organizations will be discussed. Disclosure J.M. Owen: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust