Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®).

INTRODUCTION: Distributed research networks (DRNs) are critical components of the strategic roadmaps for the National Institutes of Health and the Food and Drug Administration as they work to move toward large-scale systems of evidence generation. The National Patient-Centered Clinical Research Network (PCORnet®) is one of the first DRNs to incorporate electronic health record data from multiple domains on a national scale. Before conducting analyses in a DRN, it is important to assess the quality and characteristics of the data. METHODS: PCORnet's Coordinating Center is responsible for evaluating foundational data quality, or assessing fitness-for-use across a broad research portfolio, through a process called data curation. Data curation involves a set of analytic and querying activities to assess data quality coupled with maintenance of detailed documentation and ongoing communication with network partners. The first cycle of PCORnet data curation focused on six domains in the PCORnet common data model: demographics, diagnoses, encounters, enrollment, procedures, and vitals. RESULTS: The data curation process led to improvements in foundational data quality. Notable improvements included the elimination of data model conformance errors; a decrease in implausible height, weight, and blood pressure values; an increase in the volume of diagnoses and procedures; and more complete data for key analytic variables. Based on the findings of the first cycle, we made modifications to the curation process to increase efficiencies and further reduce variation among data partners. DISCUSSION: The iterative nature of the data curation process allows PCORnet to gradually increase the foundational level of data quality and reduce variability across the network. These activities help increase the transparency and reproducibility of analyses within PCORnet and can serve as a model for other DRNs.

Supporting open access to clinical trial data for researchers: The Duke Clinical Research Institute-Bristol-Myers Squibb Supporting Open Access to Researchers Initiative.

There are growing calls for sponsors to increase transparency by providing access to clinical trial data. In response, Bristol-Myers Squibb and the Duke Clinical Research Institute have collaborated on a new initiative, Supporting Open Access to Researchers. The aim is to facilitate open sharing of Bristol-Myers Squibb trial data with interested researchers. Key features of the Supporting Open Access to Researchers data sharing model include an independent review committee that ensures expert consideration of each proposal, stringent data deidentification/anonymization and protection of patient privacy, requirement of prespecified statistical analysis plans, and independent review of manuscripts before submission for publication. We believe that these approaches will promote open science by allowing investigators to verify trial results as well as to pursue interesting secondary uses of trial data without compromising scientific integrity.

The ethics and regulatory landscape of including vulnerable populations in pragmatic clinical trials.

Policies have been developed to protect vulnerable populations in clinical research, including the US federal research regulations (45 Code of Federal Regulations 46 Subparts B, C, and D). These policies generally recognize vulnerable populations to include pregnant women, fetuses, neonates, children, prisoners, persons with physical handicaps or mental disabilities, and disadvantaged persons. The aim has been to protect these populations from harm, often by creating regulatory and ethical checks that may limit their participation in many clinical trials. The recent increase in pragmatic clinical trials raises at least two questions about this approach. First, is exclusion itself a harm to vulnerable populations, as these groups may be denied access to understanding how health interventions work for them in clinical settings? Second, are groups considered vulnerable in traditional clinical trials also vulnerable in pragmatic clinical trials? We argue first that excluding vulnerable subjects from participation in pragmatic clinical trials can be harmful by preventing acquisition of data to meaningfully inform clinical decision-making in the future. Second, we argue that protections for vulnerable subjects in traditional clinical trial settings may not be translatable, feasible, or even ethical to apply in pragmatic clinical trials. We conclude by offering specific recommendations for appropriately protecting vulnerable research subjects in pragmatic clinical trials, focusing on pregnant women, fetuses, neonates, children, prisoners, persons with physical handicaps or mental disabilities, and disadvantaged persons.