Needles in a Haystack: Finding Qualitative and Quantitative Collaborators in Academic Medical Centers.

Translational research is a data-driven process that involves transforming scientific laboratory- and clinic-based discoveries into products and activities with real-world impact to improve individual and population health. Successful execution of translational research requires collaboration between clinical and translational science researchers, who have expertise in a wide variety of domains across the field of medicine, and qualitative and quantitative scientists, who have specialized methodologic expertise across diverse methodologic domains. While many institutions are working to build networks of these specialists, a formalized process is needed to help researchers navigate the network to find the best match and to track the navigation process to evaluate an institution's unmet collaborative needs. In 2018, a novel analytic resource navigation process was developed at Duke University to connect potential collaborators, leverage resources, and foster a community of researchers and scientists. This analytic resource navigation process can be readily adopted by other academic medical centers. The process relies on navigators with broad qualitative and quantitative methodologic knowledge, strong communication and leadership skills, and extensive collaborative experience. The essential elements of the analytic resource navigation process are as follows: (1) strong institutional knowledge of methodologic expertise and access to analytic resources, (2) deep understanding of research needs and methodologic expertise, (3) education of researchers on the role of qualitative and quantitative scientists in the research project, and (4) ongoing evaluation of the analytic resource navigation process to inform improvements. Navigators help researchers determine the type of expertise needed, search the institution to find potential collaborators with that expertise, and document the process to evaluate unmet needs. Although the navigation process can create a basis for an effective solution, some challenges remain, such as having resources to train navigators, comprehensively identifying all potential collaborators, and keeping updated information about resources as methodologists join and leave the institution.

Methods for training collaborative biostatisticians.

The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a "train the trainer" approach to enable CBs who have successfully completed training to train new staff or faculty.