The paper describes the research support model for improving the effectiveness of the medical research data collection process and data quality. Every research project involves a data collection phase, during which different organisation, legal and technology factors are involved, including various procedures (questionnaire design, annotation, database design, data entry, data validation, discrepancy management, medical coding and data mining). The key task of clinical data management is to obtain high-quality data, which can be achieved by minimising data input errors and timely identifying missing data. This process is often time-consuming and takes up a significant part of the research project budget in both veterinary and human medicine. The aim of this study is to elaborate the research support model for the creation of a data collection automation software tool, which will allow one to ensure better data quality, shorten the time for data collection and minimise human work volume and respective human resource expenses, making research projects more effective in terms of their timing and budget. Research work included analysis of the current situation, its shortcomings, typical research project budget distribution and existing automated electronic data collection tools (EDC). Research was carried out in partnership with the Institute of Clinical and Preventive Medicine of the University of Latvia.