A Stepwise Procedure to Define a Data Collection Framework for a Clinical Biobank

Abstract

Introduction: Current guidelines for clinical biobanking have a strong focus on obtaining, handling, and storage of biospecimens. However, to allow for research tying biomarker analysis to clinical decision making, there should be more focus on collection of data on donor characteristics. Therefore, our aim was to develop a stepwise procedure to define a framework as a tool to help start the data collection process in clinical biobanking.

Materials and methods: The Radboud Biobank (RB) is a central clinical biobanking facility designed in accordance with the standards set by the Parelsnoer Institute, a Dutch national biobank originally initiated with eight different disease cohorts. To organize the information of these cohorts, we used our experience and knowledge in the field of biobanking and translational research to identify research domains and information categories to classify data. We extended this classification system to a stepwise procedure for defining a data collection framework and examined its utility for existing RB biobanks.

Results: Our approach resulted in the definition of a three-step procedure: (1) Identification of research domains and relevant questions within the field that may benefit from biobank samples. (2) Identification of information categories and accompanying subcategories that are relevant for answering questions in identified research domains. (3) Reduction to an efficient framework based on essentiality and quality criteria. We showed the utility of the procedure for three existing RB biobanks.

Discussion: We developed guidelines for the definition of a framework that supports the standardization of the biobank data collection process. Connecting the biobank database to pertinent information collected from the electronic health record will improve data quality and efficiency for both care and research. This is crucial when using the corresponding biospecimens for scientific research. Further, it also facilitates the combination of different clinical biobanks for a specific disease.

Keywords: clinical biobank; data; electronic health record; framework; guidelines; standardization.