RESUMO
The direct use of EHR data in research, often referred to as 'eSource', has long-been a goal for researchers because of anticipated increases in data quality and reductions in site burden. eSource solutions should rely on data exchange standards for consistency, quality, and efficiency. The utility of any data standard can be evaluated by its ability to meet specific use case requirements. The Health Level Seven (HL7 ® ) Fast Healthcare Interoperability Resources (FHIR ® ) standard is widely recognized for clinical data exchange; however, a thorough analysis of the standard's data coverage in supporting multi-site clinical studies has not been conducted. We developed and implemented a systematic mapping approach for evaluating HL7 ® FHIR ® standard coverage in multi-center clinical trials. Study data elements from three diverse studies were mapped to HL7 ® FHIR ® resources, offering insight into the coverage and utility of the standard for supporting the data collection needs of multi-site clinical research studies.
Assuntos
Ensaios Clínicos como Assunto , Registros Eletrônicos de Saúde/normas , Nível Sete de Saúde/normas , Coleta de Dados , HumanosRESUMO
The increased demand of clinical data for the conduct of clinical and translational research incentivized repurposing of the University of Arkansas for Medical Sciences' enterprise data warehouse (EDW) to meet researchers' data needs. The EDW was renamed the Arkansas Clinical Data Repository (AR-CDR), underwent content enhancements, and deployed a self-service cohort estimation tool in late of 2016. In an effort to increase adoption of the AR-CDR, a team of physician informaticist and information technology professionals conducted various informational sessions across the UAMS campus to increase awareness of the AR-CDR and the informatics capabilities. The restructuring of the data warehouse resulted in four-fold utilization increase of the AR-CDR data services in 2017. To assess acceptance rates of the AR-CDR and quantify outcomes of services provided, Everett Rogers' diffusion of innovation (DOI) framework was applied, and a survey was distributed. Results show the factors that had impact on increased adoption were: presence of physician informaticist to mediate interactions between researchers and analysts, data quality, communication with and engagement of researchers, and the AR-CDR's team responsiveness and customer service mindset.
Assuntos
Data Warehousing , Médicos , Pesquisa Translacional Biomédica , Difusão de Inovações , Humanos , Inquéritos e QuestionáriosRESUMO
Studies often rely on medical record abstraction as a major source of data. However, data quality from medical record abstraction has long been questioned. Electronic Health Records (EHRs) potentially add variability to the abstraction process due to the complexity of navigating and locating study data within these systems. We report training for and initial quality assessment of medical record abstraction for a clinical study conducted by the IDeA States Pediatric Clinical Trials Network (ISPCTN) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network (NRN) using medical record abstraction as the primary data source. As part of overall quality assurance, study-specific training for medical record abstractors was developed and deployed during study start-up. The training consisted of a didactic session with an example case abstraction and an independent abstraction of two standardized cases. Sixty-nine site abstractors from thirty sites were trained. The training was designed to achieve an error rate for each abstractor of no greater than 4.93% with a mean of 2.53%, at study initiation. Twenty-three percent of the trainees exceeded the acceptance limit on one or both of the training test cases, supporting the need for such training. We describe lessons learned in the design and operationalization of the study-specific, medical record abstraction training program.
Assuntos
Erros Médicos , Prontuários Médicos , Indexação e Redação de Resumos , Criança , Humanos , Armazenamento e Recuperação da Informação , Projetos de PesquisaRESUMO
While several standards for metadata describing clinical studies exist, comprehensive metadata to support traceability of data from clinical studies has not been articulated. We examine uses of metadata in clinical studies. We examine and enumerate seven sources of data value-level metadata in clinical studies inclusive of research designs across the spectrum of the National Institutes of Health definition of clinical research. The sources of metadata inform categorization in terms of metadata describing the origin of a data value, the definition of a data value, and operations to which the data value was subjected. The latter is further categorized into information about changes to a data value, movement of a data value, retrieval of a data value, and data quality checks, constraints or assessments to which the data value was subjected. The implications of tracking and managing data value-level metadata are explored.