The Clinical and Translational Science Awards (CTSA) Consortium, a network of academic health care institutions with CTSA hubs, is charged with improving the national clinical and translational research enterprise. The CTSA Consortium and the NIH National Center for Advancing Translational Sciences implemented the Common Metrics Initiative comprised of standardized metrics and a shared performance improvement framework. This article summarizes hubs’ perspectives on its value during the initial implementation.

The value was assessed across 58 hubs. Survey items assessed change in perceived ability to manage performance and advance clinical and translational science. Semi-structured interviews elicited hubs’ perspectives on meaningfulness and value-added of the Common Metrics Initiative and hubs’ recommendations.

Hubs considered their abilities to manage performance to have improved, but there was no change in perceived ability to advance clinical and translational science. The initiative added value by providing a formal structured process, enabling strategic conversations, facilitating improvements in processes, providing an external impetus for improvement, and providing justification for funds invested. Hubs were concerned about the usefulness of the metrics chosen and whether the value-added was sufficient relative to the effort required. Hubs recommended useful benchmarking, disseminating best practices and promoting peer-to-peer learning, and expanding the use of data to inform the initiative.

Implementing Common Metrics and a performance improvement framework yielded concrete short-term benefits, but concerns about usefulness remained, particularly considering the effort required. The Common Metrics Initiative should focus on facilitating cross-hub collaboration around metrics that address high-priority impact areas for individual hubs and the Consortium.

The Clinical and Translational Science Awards (CTSA) Consortium, about 60 National Institutes of Health (NIH)-supported CTSA hubs at academic health care institutions nationwide, is charged with improving the clinical and translational research enterprise. Together with the NIH National Center for Advancing Translational Sciences (NCATS), the Consortium implemented Common Metrics and a shared performance improvement framework.

Initial implementation across hubs was assessed using quantitative and qualitative methods over a 19-month period. The primary outcome was implementation of three Common Metrics and the performance improvement framework. Challenges and facilitators were elicited.

Among 59 hubs with data, all began implementing Common Metrics, but about one-third had completed all activities for three metrics within the study period. The vast majority of hubs computed metric results and undertook activities to understand performance. Differences in completion appeared in developing and carrying out performance improvement plans. Seven key factors affected progress: hub size and resources, hub prior experience with performance management, alignment of local context with needs of the Common Metrics implementation, hub authority in the local institutional structure, hub engagement (including CTSA Principal Investigator involvement), stakeholder engagement, and attending training and coaching.

Implementing Common Metrics and performance improvement in a large network of research-focused organizations proved feasible but required substantial time and resources. Considerable heterogeneity across hubs in data systems, existing processes and personnel, organizational structures, and local priorities of home institutions created disparate experiences across hubs. Future metric-based performance management initiatives across heterogeneous local contexts should anticipate and account for these types of differences.

To quantifying the interdependency within the regulatory environment governing human subject research, including Institutional Review Boards (IRBs), federally mandated Medicare coverage analysis and contract negotiations.

Over 8000 IRB, coverage analysis and contract applications initiated between 2013 and 2016 were analyzed using traditional and machine learning analytics for a quality improvement effort to improve the time required to authorize the start of human research studies.

Staffing ratios, study characteristics such as the number of arms, source of funding and number and type of ancillary reviews significantly influenced the timelines. Using key variables, a predictive algorithm identified outliers for a workflow distinct from the standard process. Improved communication between regulatory units, integration of common functions, and education outreach improved the regulatory approval process.

Understanding and improving the interdependencies between IRB, coverage analysis and contract negotiation offices requires a systems approach and might benefit from predictive analytics.

The time required to obtain Institutional Review Board (IRB) approval is a frequent subject of efforts to reduce unnecessary delays in initiating clinical trials. This study was conducted by and for IRB directors to better understand factors affecting approval times as a first step in developing a quality improvement framework.

807 IRB-approved clinical trials from 5 University of California campuses were analyzed to identify operational and clinical trial characteristics influencing IRB approval times.

High workloads, low staff ratios, limited training, and the number and types of ancillary reviews resulted in longer approval times. Biosafety reviews and the need for billing coverage analysis were ancillary reviews that contributed to the longest delays. Federally funded and multisite clinical trials had shorter approval times. Variability in between individual committees at each institution reviewing phase 3 multisite clinical trials also contributed to delays for some protocols. Accreditation was not associated with shorter approval times.

Reducing unnecessary delays in obtaining IRB approval will require a quality improvement framework that considers operational and study characteristics as well as the larger institutional regulatory environment.

The National Center for Advancing Translation Science (NCATS) is implementing a new strategic management plan called the results-based accountability framework. This framework is part of the common metrics initiative. For successful implementation and adoption of new management strategies, it is important to assess current stakeholders’ experiences and needs.

Interviews were conducted with principal investigators who are conducting research and supported by the Center for Clinical Translational Science at the University of Utah. Between July and August 2016, 15 interviews were completed and audio recorded. A qualitative content analysis was conducted on the transcripts.

Results indicated the need to provide education about the continuum of clinical translational research; time constraints during pre-award; barriers to IRB submissions; difficulty balancing other responsibilities in academic health centers; and the need for shared study coordinator resources.

Implementing a new management philosophy requires an understanding key stakeholders attitudes and needs. The research identified ways to help engage investigators with centralized resources supported by NCATS and implementation of common metrics at this university.