PNS13 An Investment Example on Digitalization, a Unique System Designed for Medical Device Tracking: UTS

Abstract

Medical Device Product Tracking System (UTS) is a national healthcare investment on digitalization implemented by Turkish Medicines and Medical Devices Agency (TITCK) in 2017. The purpose of this study is to discuss the benefits of this investment to healthcare system by taking into consideration patient and quality-oriented design of UTS. In this study, the UTS Usage Report published by TITCK in 2019 was analyzed for system adaptation and usage prevalence throughout country. To evaluate features for patient safety and product quality maintenance, the new applications versus pre-existing practices were compared by a survey analysis. The investment budget and other data were received from TITCK directly. The total investment for UTS was $18,394,292, which constituted 0.04% of the total budget allocated to healthcare expenditures in Turkey in 2017. The number of medical device companies and products registered to UTS in 2019 are 43,332 and 3,773,070, respectively. There are 22,187 healthcare providers using UTS. UTS mobile application, which was not previously available, has been downloaded by more than 15,000 users in 2019. Citizens can quickly make their complaints from application regarding quality and use of any medical device. While disposable products could be used more than once before UTS, it is currently controllable with the help of system tracking. UTS has a special module designed to have a faster and easier vigilance process. As of January 2017, 9875 adverse event notifications have been delivered from users and health institutions through the system. UTS is a strategic and nationwide healthcare investment example on digitalization in Turkey. It supports patient safety via traceability of medical devices, potential benefits for patients via discouraging multi-usage of single-use products, quality via controlling certification, improving recall processes, better insights for policy and planning via big data analysis.