Data management and quality control strategies for population based cohort study

Abstract

Large-scale cohort study has unique advantages in the field of etiology research for its large sample size a multi-time point data, but it also brings great difficulty in data management and quality control at the same time. Recently, China has initiated a number of large-scale population cohort studies, posing enormous challenges to the management and quality control of related cohort data. This paper summarizes the existing experience and consensus in the field of cohort study in China from the characteristics of the cohort data, aiming at the types and main forms of the four main sources of questionnaire data, clinical diagnosis and treatment data, biological sample detection data and observation outcome data, from the data storage, circulation and transmission work.The contents and methods of queue data management are comprehensively summarized. Corresponding data quality control strategies are advised in the questionnaire evaluation, data logic verification, survey object sampling and multi-database review, etc. The goal of this review is to provide guidance for the management of data and the formulation of quality control strategies in the cohort study in China.