NCT04378985

Developing Health Care Service System

Developing Health Care Service System Based on Participatory Big Data

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 384 (estimated)
• Sponsor: Gangnam Severance Hospital · Academic / Other
• Sex: All
• Age: 20 Years – 65 Years
• Healthy volunteers: Not accepted

Summary

"Increased health risks and diseases are believed to be caused by multilevel interactions of genetic and environmental factors (including lifestyle habits). Considering the recent advancements in genetic analysis, wearable devices, and big data analysis techniques, collecting and analyzing personal genetic information, lifelogs, and environmental data and predicting the exact health risks of individuals could be possible.

Detailed description

These changes enable the development of healthcare solutions that allow users to actively engage in healthcare and provide appropriate care measures to sufficiently delay or prevent chronic diseases, thereby minimizing the financial losses of the individuals and the society. In particular, chronic diseases such as metabolic syndrome can be prevented or delayed through healthy lifestyle habits. Controversy regarding the effectiveness of using wearable devices and mobile health applications for maintaining lifestyle habits and losing weight exists. Additionally, a study assessing the health of the participants and the disease prevention care for the participants using the genetic data and the lifelog data by the wearable device has not been conducted yet. Therefore, the objective is to operate a lifestyle correction program for examinees who visited a family medicine and health checkup center to develop a user-participation health and disease prevention care system using genetic data and lifelog data. From adults who visited a family medicine and health checkup center, the following should be performed: (1) collect a variety of clinical information, including lifestyle data, physical information, metabolic parameters, genetic information, and metagenomes, which can affect chronic diseases; (2) establish a service model that combines lifestyle data, examination data, and genetic data and analyzes and identifies one's health level through a smartphone application; and (3) examine the effects on the metabolic parameters, lifestyle data, and metagenome (gut microbiome) after using the device (smart healthcare).This pilot study aimed to provide personalized "my data" by linking clinical data and personal lifestyle patterns of the participants who visited a family medicine and examination center. From adults who visited a family medicine and health check-up center, the following should be performed: 1. Collect a variety of clinical information, including lifestyle data, physical information, metabolic parameters, genetic information, and metagenomes, which can affect chronic diseases 2. Establish a service model that combines lifestyle data, examination data, and genetic data and analyzes and identifies one's health level through a smartphone application 3. Examine the effects on the metabolic parameters, lifestyle data, and metagenome (gut microbiome) after using the device (smart healthcare) "

Conditions

• Metabolic Syndrome

Interventions

Type	Name	Description
DEVICE	Wearing a Wearable device (Fitbit inspire HR)	'Wearing a wearable device (the smart watch) for 8 weeks The smart watch to be used in this study is Fitbit Inspire HR. This is a device that has a high worldwide use rate and has active research on its accuracy. It is worn like a normal watch, and it can check heart rate, exercise level, energy consumed, and sleep quality. The values can be checked in real-time on a smartphone application.'

Timeline

• Start date: 2019-12-20
• Primary completion: 2021-10-30
• Completion: 2021-12-30
• First posted: 2020-05-07
• Last updated: 2020-05-07

Locations

1 site across 1 country: South Korea