## 1 Introduction  
Clinical trials are essential to study the efficacy and risks associated with drugs; however, they are costly and time-consuming, occasionally requiring years for completion. A recent study found that the average cost of development of a novel drug from drug discovery to the marketing approval of a product is between $2 billion and $3 billion and can take anywhere from 12 to 18 years, with clinical trials being the most costly and time-consuming phases of the entire process [1]. The burden of such conventional processes for whole-drug development has become even more challenging with the coronavirus disease 2019 (COVID-19) pandemic, especially because of the difficulty in recruiting and retaining clinical trial participants [2; 3; 4]. Because of the limitations imposed by COVID-19, such as self-isolation, site closures, and travel restrictions, as of October 2021, more than 2100 clinical trials have been reported to be explicitly suspended [5; 6; 7]. To overcome these difficulties, attempts have been made to utilize digital technologies, including Internet of Things (IoT) and patient-generated health data (PGHD) from devices such as biowearables, smartphones, and home medical devices, and to execute decentralized clinical trials (DCTs) [8; 9; 10]. The proliferation of these devices is expected to accelerate patient selection and adherence to trials. In particular, attempts to increase the efficiency of clinical research and medical fields using digital health technology have expanded exponentially as of 2020 [9; 10; 11]. Clinical research professionals (CRPs) at trial sites are responsible for collecting patient data and evaluating drugs. Although data collection is very important in clinical trials, the collection of accurate data is difficult in practice. In particular, for outpatient clinical trials, although frequent visits to the institutions can facilitate data collection, they cause inconvenience to the participants, make it difficult to recruit patients, and increase the possibility of trial discontinuation by participants. The collected data may also be questionable. In many cases, the data report is delayed until the next visit. Therefore, the collected data are often reported to be of poor quality, missing details such as the occurrence of the event itself, the time, and the reaction of the participant [12]. At present, to solve these difficulties in data collection, various technologies for traditional clinical trials and DCTs are being implemented haphazardly. However, most of these technologies and devices have been developed from the perspective of sponsors requesting clinical trials [13; 14]. Although, like many other countries, South Korea, where this study is conducted, ranks sixth (3.68%) in the industry-sponsored trials of 2020 and third (4.5%) in single-site trials. The number of trials is also increasing. However, the proportion of investigator-initiated trial among all the ongoing clinical trials is declining. The impact of investigator-initiated trials in the clinical trial field is decreasing [15]. Thus, there has been no application development reflecting the needs of CRPs conducting clinical trials at actual institutions. Therefore, CRPs have to deal with the burden of using and adapting different platforms provided by various sponsors for clinical trials and educating participants [16]. The CRPs at trial sites who monitor the participants and evaluate drugs are currently exposed to various clinical trial management systems, ranging from traditional systems to systems based on the latest technologies. However, it is difficult to find a system specialized for efficient trial and patient management that can allow CRPs at the trial site to operate in the desired way. In this scenario, the development and introduction of a new trial management system based on the needs of the CRPs at the trial site can save cost and time and yield more accurate clinical trial results quickly by using PGHD.