Technology Considerations for Enabling eSource in Clinical Research: Industry Perspective.

BACKGROUND: The technological complexities and broad operational scope of eSource impede coordinated, inter-organizational action on advancing at-scale solutions. METHODS: We introduce an architectural framework for articulating technological considerations across organizations. The architecture neither implies nor endorses solution implementations; rather, it proposes solution functionality based upon principles and good clinical practices. RESULTS: Key technology considerations include patterns of anticipated use, implications to the current state of clinical trial operations, and the need for new technologies (i.e., IoT, Big Data, Predictive Analytics). CONCLUSION: Technology considerations drive implications beyond technology-influencing regulatory, process, and ethical realms of clinical research.

Use of EHRs data for clinical research: Historical progress and current applications.

The benefits of reusing EHR data for clinical research studies are numerous. They portend the opportunity to bring new therapies to patients sooner, potentially at a lower cost, and to accelerate learning health cycles-through faster data acquisition in clinical research studies. Metrics have proven that time can be saved, workflow and processes streamlined, and data quality increased significantly. Pilot projects and now actual investigational trials used for regulatory submissions have shown that these benefits support the transformation of clinical research by leveraging EHRs for research. Panelists at a recent collaborative focused on bridging clinical research and clinical care offered varying perspectives on how the latest standards and technologies could be leveraged to facilitate data transfer from EHR systems into clinical research databases, as well as the associated improvements in data quality. Panelists also discussed other avenues to leverage EHR in clinical research. Improvements and exciting possibilities notwithstanding, much work remains. Data ownership and access, attention to metadata and structured data for data sharing, and broader adoption of global standards are key areas for collaboration. With the steady increase in adoption of EHRs around the world, this is an excellent time for all stakeholders to work together and create an environment such that EHRs can be used more readily for research. The capacity for research can thus be increased to provide more high-quality information that will contribute to rapid continuous learning health systems from which all patients can benefit.

eSource for Standardized Health Information Exchange in Clinical Research: A Systematic Review.

The availability of research and outcomes data is the primary limitation to evidence-based practice. Today, only a fraction of clinical decisions are based upon evidence derived from randomized control trials (RCTs), the gold-standard of knowledge discovery. At the same time, clinical trial complexity has steadily increased as has the effort required at clinical investigational sites. Direct use of electronic health record (EHR) data for clinical trials has the potential to address some of these needs, improving data quality and reducing cost.

Evaluative Outcomes in Direct Extraction and Use of EHR Data in Clinical Trials.

Use of electronic health record (EHR) data in clinical trials has long been a goal for researchers. However, few demonstrations and fewer evaluative studies have been published. The variability in outcome choice and measurement hinders synthesis of the extant literature. In collaboration with a contemporaneous systematic review of EHR data use in clinical trial data collection, we analyze reported outcomes and recommend a standardized measure set for the evaluation of human safety, data quality, operational efficiency and cost of eSource solutions.

A comparative effectiveness study of eSource used for data capture for a clinical research registry.

OBJECTIVE: This pilot study compared eSource-enabled versus traditional manual data transcription (non-eSource methods) for the collection of clinical registry information. The primary study objective was to compare the time spent completing registry forms using eSource versus non-eSource methods The secondary objectives were to compare data quality associated with these two data capture methods and the flexibility of the workflows. This study directly addressed fundamental questions relating to eSource adoption: what time-savings can be realized, and to what extent does eSource improve data quality. MATERIALS AND METHODS: The study used time and motion methods to compare eSource versus non-eSource data capture workflows for a single center OB/GYN registry. Direct observation by industrial engineers using specialized computer software captured keystrokes, mouse clicks and video recordings of the study team in their normal work environment completing real-time data collection. RESULTS: The overall average data capture time was reduced with eSource versus non-eSource methods (difference, 151s per case; eSource, 1603s; non-eSource, 1754s; p=0.051). The average data capture time for the demographic data was reduced (difference, 79s per case; eSource, 133s; non-eSource, 213s; p<0.001). This represents a 37% time reduction (95% confidence interval 27% to 47%). eSourced data field transcription errors were also reduced (eSource, 0%; non-eSource, 9%). CONCLUSION: The use of eSource versus traditional data transcription was associated with a significant reduction in data entry time and data quality errors. Further studies in other settings are needed to validate these results.

Using Medical Informatics to Improve Clinical Trial Operations.

The continued escalation of clinical trial costs is becoming a public health concern. During the past decade, medical research funding peaked and there is growing concern that there may be insufficient resources to test many promising medical products. Recent changes in the regulatory environment create opportunities for the use of medical informatics to improve clinical trial operations and reduce costs. We report on a Medical Informatics Europe 2016 workshop conducted during the Health - Exploring Complexity (HEC) 2016 conference. We review presentation given on Secondary Data Use, eSource, and Data Quality in Clinical Trials and report on the workshop's discussions.