Digitalisation of adverse drug reactions information source

Abstract

The opportunities offered through information technology including the internet and databases to provide information about adverse drug reactions for healthcare professionals and patients are continuously evolving. These tools empower healthcare professionals, facilitating seamless data retrieval, analysis, and decision-making, ultimately enhancing patient care and research. A digital adverse drug reactions platform helps in aiding the timely detection of adverse drug reactions. The research aimed to understand the perspectives and needs of the general public and healthcare professionals when sourcing information about adverse drug reactions, to identify challenges in developing an adverse drug reactions database and to propose an online platform that presents adverse drug reactions. An evaluation was carried out involving patrons at pharmacies and healthcare professionals working at the pharmacies. Two different self-administered questionnaires were developed, one for the general public and the other one for healthcare professionals. Eight pharmacies were chosen to take part in the study and the research included 105 persons from the general public and 30 healthcare professionals. An Excel® workbook consisting of adverse drug reactions that present with cardiovascular, gastrointestinal, respiratory, thoracic, and mediastinal system organ classes for drugs licensed in Malta was compiled. The adverse drug reactions were extracted from the Summary of Product Characteristics. 1557 adverse drug reactions were included in the workbook. Pharmacy patrons stated that a digital adverse drug reactions information source is useful and healthcare professionals would find this source trustworthy with a mean of 3.8 and 4.1 respectively from the 5-point Likert scale. Patrons of the pharmacy ranked pharmacists, general practitioners, and the internet as the top reference sources of information for adverse drug reactions showing that a digital adverse drug reaction source could be useful in healthcare settings due to its quick and free access. The challenges in developing the online platform are harvesting data accurately and the feasibility of maintaining the information source updated. Integrating the contents of the summary of product characteristics into an adverse drug reactions database using advanced methods such as Artificial Intelligence and Machine Learning holds the potential to streamline data management and improve accuracy.