Bringing the Medical Library to the Forefront of Data Analysis and Precision Medicine: Strategies and Statistics

Background: Currently, biomedical research relies on Bioinformatic data to find causes of diseases, develop precision medicine, track treatment, and predict prognosis. Laboratory and clinical investigators produce large amounts of data that need to be computationally analyzed. However, investigators often lack the skills and/or time required for such analysis, resulting in slow processing that leads to frustration and missed opportunities. The support for investigators with Bioinformatic data is sparse, and the Data Services for the Health Sciences and the Bioinformatics Support Program at the Cushing/Whitney Medical Library (CWML) at Yale University is working together to fill this unmet need.

Description: The CWML recruited Data Services and Bioinformatics Support personnel to support investigators in data management during the research life-cycle and data analysis, respectively. By working together, these two separate entities have been able to provide complete computational analysis support to the investigators. Through individual consultations, demonstration-based instructional sessions, and direct collaborations, this program has been able to speed-up bioinformatic research with licensed analysis software; improve investigators’ knowledge of data analysis in programming languages such as R and Python; and ensure best data practices during research. Evaluation on the effectiveness of the program is being carried out via (1) assessments after instructional sessions to understand whether learning goals have been met; and (2) surveys after a period of consultations to understand whether the investigator’s research has progressed.

Conclusion: At the time of our presentation we will provide statistics and real-life examples to illustrate that Data Services and Bioinformatics Support can successfully work together to provide high quality instructional sessions on data analysis. These sessions can help patrons learn to execute their own analyses in computing languages, such as R, even if they do not have extensive prior knowledge in this area. We have shown that not only are these sessions extremely popular within the medical community, but they are also of interest to a variety of clinical departments, therefore, enabling the medical library to extend support to the entire medical school research community.