Dataset Information

Standardized cardiovascular data for clinical research, registries, and patient care: a report from the Data Standards Workgroup of the National Cardiovascular Research Infrastructure project.

ABSTRACT: Relatively little attention has been focused on standardization of data exchange in clinical research studies and patient care activities. Both are usually managed locally using separate and generally incompatible data systems at individual hospitals or clinics. In the past decade there have been nascent efforts to create data standards for clinical research and patient care data, and to some extent these are helpful in providing a degree of uniformity. Nonetheless, these data standards generally have not been converted into accepted computer-based language structures that could permit reliable data exchange across computer networks. The National Cardiovascular Research Infrastructure (NCRI) project was initiated with a major objective of creating a model framework for standard data exchange in all clinical research, clinical registry, and patient care environments, including all electronic health records. The goal is complete syntactic and semantic interoperability. A Data Standards Workgroup was established to create or identify and then harmonize clinical definitions for a base set of standardized cardiovascular data elements that could be used in this network infrastructure. Recognizing the need for continuity with prior efforts, the Workgroup examined existing data standards sources. A basic set of 353 elements was selected. The NCRI staff then collaborated with the 2 major technical standards organizations in health care, the Clinical Data Interchange Standards Consortium and Health Level Seven International, as well as with staff from the National Cancer Institute Enterprise Vocabulary Services. Modeling and mapping were performed to represent (instantiate) the data elements in appropriate technical computer language structures for endorsement as an accepted data standard for public access and use. Fully implemented, these elements will facilitate clinical research, registry reporting, administrative reporting and regulatory compliance, and patient care.

SUBMITTER: Anderson HV

PROVIDER: S-EPMC3664644 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Standardized cardiovascular data for clinical research, registries, and patient care: a report from the Data Standards Workgroup of the National Cardiovascular Research Infrastructure project.

Anderson H Vernon HV Weintraub William S WS Radford Martha J MJ Kremers Mark S MS Roe Matthew T MT Shaw Richard E RE Pinchotti Dana M DM Tcheng James E JE

Journal of the American College of Cardiology 20130306 18

Relatively little attention has been focused on standardization of data exchange in clinical research studies and patient care activities. Both are usually managed locally using separate and generally incompatible data systems at individual hospitals or clinics. In the past decade there have been nascent efforts to create data standards for clinical research and patient care data, and to some extent these are helpful in providing a degree of uniformity. Nonetheless, these data standards generall ...[more]

PMID: 23500238

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Project description:BACKGROUND:Health services researchers spend a substantial amount of time performing integration, cleansing, interpretation, and aggregation of raw data from multiple public or private data sources. Often, each researcher (or someone in their team) duplicates this effort for their own project, facing the same challenges and experiencing the same pitfalls discovered by those before them. OBJECTIVE:This paper described a design process for creating a data warehouse that includes the most frequently used databases in health services research. METHODS:The design is based on a conceptual iterative process model framework that utilizes the sociotechnical systems theory approach and includes the capacity for subsequent updates of the existing data sources and the addition of new ones. We introduce the theory and the framework and then explain how they are used to inform the methodology of this study. RESULTS:The application of the iterative process model to the design research process of problem identification and solution design for the Healthcare Research and Analytics Data Infrastructure Solution (HRADIS) is described. Each phase of the iterative model produced end products to inform the implementation of HRADIS. The analysis phase produced the problem statement and requirements documents. The projection phase produced a list of tasks and goals for the ideal system. Finally, the synthesis phase provided the process for a plan to implement HRADIS. HRADIS structures and integrates data dictionaries provided by the data sources, allowing the creation of dimensions and measures for a multidimensional business intelligence system. We discuss how HRADIS is complemented with a set of data mining, analytics, and visualization tools to enable researchers to more efficiently apply multiple methods to a given research project. HRADIS also includes a built-in security and account management framework for data governance purposes to ensure customized authorization depending on user roles and parts of the data the roles are authorized to access. CONCLUSIONS:To address existing inefficiencies during the obtaining, extracting, preprocessing, cleansing, and filtering stages of data processing in health services research, we envision HRADIS as a full-service data warehouse integrating frequently used data sources, processes, and methods along with a variety of data analytics and visualization tools. This paper presents the application of the iterative process model to build such a solution. It also includes a discussion on several prominent issues, lessons learned, reflections and recommendations, and future considerations, as this model was applied.

Project description:Importance:Publicly available data sets hold much potential, but their unique design may require specific analytic approaches. Objective:To determine adherence to appropriate research practices for a frequently used large public database, the National Inpatient Sample (NIS) of the Agency for Healthcare Research and Quality (AHRQ). Design, Setting, and Participants:In this observational study of the 1082 studies published using the NIS from January 2015 through December 2016, a representative sample of 120 studies was systematically evaluated for adherence to practices required by AHRQ for the design and conduct of research using the NIS. Exposures:None. Main Outcomes and Measures:All studies were evaluated on 7 required research practices based on AHRQ's recommendations and compiled under 3 domains: (1) data interpretation (interpreting data as hospitalization records rather than unique patients); (2) research design (avoiding use in performing state-, hospital-, and physician-level assessments where inappropriate; not using nonspecific administrative secondary diagnosis codes to study in-hospital events); and (3) data analysis (accounting for complex survey design of the NIS and changes in data structure over time). Results:Of 120 published studies, 85% (n?=?102) did not adhere to 1 or more required practices and 62% (n?=?74) did not adhere to 2 or more required practices. An estimated 925 (95% CI, 852-998) NIS publications did not adhere to 1 or more required practices and 696 (95% CI, 596-796) NIS publications did not adhere to 2 or more required practices. A total of 79 sampled studies (68.3% [95% CI, 59.3%-77.3%]) among the 1082 NIS studies screened for eligibility did not account for the effects of sampling error, clustering, and stratification; 62 (54.4% [95% CI, 44.7%-64.0%]) extrapolated nonspecific secondary diagnoses to infer in-hospital events; 45 (40.4% [95% CI, 30.9%-50.0%]) miscategorized hospitalizations as individual patients; 10 (7.1% [95% CI, 2.1%-12.1%]) performed state-level analyses; and 3 (2.9% [95% CI, 0.0%-6.2%]) reported physician-level volume estimates. Of 27 studies (weighted; 218 studies [95% CI, 134-303]) spanning periods of major changes in the data structure of the NIS, 21 (79.7% [95% CI, 62.5%-97.0%]) did not account for the changes. Among the 24 studies published in journals with an impact factor of 10 or greater, 16 (67%) did not adhere to 1 or more practices, and 9 (38%) did not adhere to 2 or more practices. Conclusions and Relevance:In this study of 120 recent publications that used data from the NIS, the majority did not adhere to required practices. Further research is needed to identify strategies to improve the quality of research using the NIS and assess whether there are similar problems with use of other publicly available data sets.

Dataset Information

Standardized cardiovascular data for clinical research, registries, and patient care: a report from the Data Standards Workgroup of the National Cardiovascular Research Infrastructure project.

Publications

Standardized cardiovascular data for clinical research, registries, and patient care: a report from the Data Standards Workgroup of the National Cardiovascular Research Infrastructure project.

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