Various digital healthcare devices and apps, such as blood glucose meters, blood pressure monitors, and step-trackers are commonly used by patients; however, digital healthcare devices have not been widely accepted in the medical market as of yet. Despite the various legal and privacy issues involved in their use, the main reason for its poor acceptance is that users do not use such devices voluntarily and continuously. Digital healthcare devices generally do not provide valuable information to users except for tracking self-checked glucose or walking. To increase the use of these devices, users must first understand the health data produced in the context of their personal health, and the devices must be easy to use and integrated into everyday life. Thus, users need to know how to manage their own data. Medical staff must teach and encourage users to analyze and manage their patient-generated healthcare data, and users should be able to find medical values from these digital devices. Eventually, a single customized service that can comprehensively analyze various medical data to provide valuable customized services to users, and which can be linked to various heterogeneous digital healthcare devices based on the integration of various health data should be developed. Digital healthcare professionals should have detailed knowledge about a variety of digital healthcare devices and fully understand the advantages and disadvantages of digital healthcare to help patients understand and embrace the use of such devices.

Various digital healthcare devices and apps, such as blood glucose meters, blood pressure monitors, and step-trackers are commonly used by patients; however, digital healthcare devices have not been widely accepted in the medical market as of yet. Despite the various legal and privacy issues involved in their use, the main reason for its poor acceptance is that users do not use such devices voluntarily and continuously. Digital healthcare devices generally do not provide valuable information to users except for tracking self-checked glucose or walking. To increase the use of these devices, users must first understand the health data produced in the context of their personal health, and the devices must be easy to use and integrated into everyday life. Thus, users need to know how to manage their own data. Medical staff must teach and encourage users to analyze and manage their patient-generated healthcare data, and users should be able to find medical values from these digital devices. Eventually, a single customized service that can comprehensively analyze various medical data to provide valuable customized services to users, and which can be linked to various heterogeneous digital healthcare devices based on the integration of various health data should be developed. Digital healthcare professionals should have detailed knowledge about a variety of digital healthcare devices and fully understand the advantages and disadvantages of digital healthcare to help patients understand and embrace the use of such devices.

Objectives: Despite the popularization of technology and the high penetration rate of smartphones and mobile devices, differences exist in the accessibility, utilization capabilities, and quality of technology depending on users’ characteristics. Since these discrepancies can threaten health information equity, popularization of medical information is essential. This review article examines domestic and international cases of popularization of medical information, and discusses the related issues, expectations, and practical measures to achieve the popularization of medical information. Methods: In this study, medical information was categorized as Electronic Health Records/Electronic Medical Records (EHR/EMRs; hospital-driven medical information), personal health records (PHRs; user-driven medical information), and patient-generated health data (PGHD; user-generated medical information [outside hospitals]). This article reviewed the domestic and international use status, acceptance rates, and use cases for each type of medical information. Issues and expectations about policies and cases related to the popularization of medical information were also described, and finally, practical measures to accomplish the popularization of medical information were discussed. Results: To achieve the popularization of medical information, the following measures should be considered: engaging health consumers to participate in the early stages of information production, cultivating digital literacy, producing easy-to-use and interesting medical content, visualizing health information, and creating a medical thesaurus. Conclusions Healthcare providers should make regular efforts to popularize medical information. The popularization of medical information is an essential process to achieve health equity and digital health equity.

Patient-generated health data (PGHD) are health-related data generated, recorded, and collected by patients or caregivers. Its main advantage is that patients can actively participate in their own health care, since the data-generating agents are patients and caregivers, not hospitals. Due to the development and popularization of information and communications technology and digital devices, the number of studies using PGHD for better health care is increasing. When PGHD was used in the outpatient setting, healthcare providers were better able to understand each patients’ condition using more accurate data, and to monitor patient health status between visits. In particular, to manage chronic diseases suchas diabetes, it is essential to monitor daily blood sugar and change nutrient intake in the context of medication, overall diet, and exercise. However, problems associated with data quality, data extraction, and insufficient evidence and research to guide use of this kind of data in clinical setting are yet to be solved. Further, the gap between patient and healthcare providers’ perceptions of PGHD persists. We suggest that PGHD, electronic medical record data in hospitals, and claims and genome data could be combined to good effect. This combination can help patients and healthcare providers make better decisions with respect to patient health and to maintain patient engagement. In addition, the collection of PGHD through sophisticated sensors, and data analysis through advanced portals could combine medical big data with daily big data. Eventually, a personalized healthcare automation system through PGHD-based algorithms could provide healthcare artificial intelligence services.

Patient-generated health data (PGHD) are health-related data generated, recorded, and collected by patients or caregivers. Its main advantage is that patients can actively participate in their own health care, since the data-generating agents are patients and caregivers, not hospitals. Due to the development and popularization of information and communications technology and digital devices, the number of studies using PGHD for better health care is increasing. When PGHD was used in the outpatient setting, healthcare providers were better able to understand each patients’ condition using more accurate data, and to monitor patient health status between visits. In particular, to manage chronic diseases suchas diabetes, it is essential to monitor daily blood sugar and change nutrient intake in the context of medication, overall diet, and exercise. However, problems associated with data quality, data extraction, and insufficient evidence and research to guide use of this kind of data in clinical setting are yet to be solved. Further, the gap between patient and healthcare providers’ perceptions of PGHD persists. We suggest that PGHD, electronic medical record data in hospitals, and claims and genome data could be combined to good effect. This combination can help patients and healthcare providers make better decisions with respect to patient health and to maintain patient engagement. In addition, the collection of PGHD through sophisticated sensors, and data analysis through advanced portals could combine medical big data with daily big data. Eventually, a personalized healthcare automation system through PGHD-based algorithms could provide healthcare artificial intelligence services.

Objectives: Despite the popularization of technology and the high penetration rate of smartphones and mobile devices, differences exist in the accessibility, utilization capabilities, and quality of technology depending on users’ characteristics. Since these discrepancies can threaten health information equity, popularization of medical information is essential. This review article examines domestic and international cases of popularization of medical information, and discusses the related issues, expectations, and practical measures to achieve the popularization of medical information. Methods: In this study, medical information was categorized as Electronic Health Records/Electronic Medical Records (EHR/EMRs; hospital-driven medical information), personal health records (PHRs; user-driven medical information), and patient-generated health data (PGHD; user-generated medical information [outside hospitals]). This article reviewed the domestic and international use status, acceptance rates, and use cases for each type of medical information. Issues and expectations about policies and cases related to the popularization of medical information were also described, and finally, practical measures to accomplish the popularization of medical information were discussed. Results: To achieve the popularization of medical information, the following measures should be considered: engaging health consumers to participate in the early stages of information production, cultivating digital literacy, producing easy-to-use and interesting medical content, visualizing health information, and creating a medical thesaurus. Conclusions Healthcare providers should make regular efforts to popularize medical information. The popularization of medical information is an essential process to achieve health equity and digital health equity.

Objectives: This study aimed to assess the feasibility of implementing OpenNotes in Korea. It involved developing and evaluating the Open-CHA service, which provides clinical summary information to patients diagnosed with craniofacial deformities and their caregivers following outpatient visits. Methods: The study included 109 patients diagnosed with craniofacial deformities, along with their caregivers. The Open-CHA service was developed by referencing OpenNotes and involved a user needs assessment, a pilot test, and an evaluation of its effectiveness. Data were analyzed using descriptive statistics and the paired t-test. Results: Short message service templates for the Open-CHA service based on a user needs assessment conducted with patients, caregivers, and healthcare professionals. These templates were refined and improved following a pilot test. After the implementation of the Open-CHA service, most participants evaluated OpenNotes positively. Additionally, there were observed increases in health knowledge and efficacy in patient-physician interactions. A statistically significant improvement in mobile health literacy was also confirmed. Conclusions The implementation of the Open-CHA service significantly enhanced mobile health literacy among patients with craniofacial deformities and their caregivers, indicating positive outcomes for the potential adoption of OpenNotes in Korea. This suggests that introducing OpenNotes into the Korean healthcare system is appropriate.

Objectives: This study aimed to assess the feasibility of implementing OpenNotes in Korea. It involved developing and evaluating the Open-CHA service, which provides clinical summary information to patients diagnosed with craniofacial deformities and their caregivers following outpatient visits. Methods: The study included 109 patients diagnosed with craniofacial deformities, along with their caregivers. The Open-CHA service was developed by referencing OpenNotes and involved a user needs assessment, a pilot test, and an evaluation of its effectiveness. Data were analyzed using descriptive statistics and the paired t-test. Results: Short message service templates for the Open-CHA service based on a user needs assessment conducted with patients, caregivers, and healthcare professionals. These templates were refined and improved following a pilot test. After the implementation of the Open-CHA service, most participants evaluated OpenNotes positively. Additionally, there were observed increases in health knowledge and efficacy in patient-physician interactions. A statistically significant improvement in mobile health literacy was also confirmed. Conclusions The implementation of the Open-CHA service significantly enhanced mobile health literacy among patients with craniofacial deformities and their caregivers, indicating positive outcomes for the potential adoption of OpenNotes in Korea. This suggests that introducing OpenNotes into the Korean healthcare system is appropriate.

Objectives: This study aimed to assess the feasibility of implementing OpenNotes in Korea. It involved developing and evaluating the Open-CHA service, which provides clinical summary information to patients diagnosed with craniofacial deformities and their caregivers following outpatient visits. Methods: The study included 109 patients diagnosed with craniofacial deformities, along with their caregivers. The Open-CHA service was developed by referencing OpenNotes and involved a user needs assessment, a pilot test, and an evaluation of its effectiveness. Data were analyzed using descriptive statistics and the paired t-test. Results: Short message service templates for the Open-CHA service based on a user needs assessment conducted with patients, caregivers, and healthcare professionals. These templates were refined and improved following a pilot test. After the implementation of the Open-CHA service, most participants evaluated OpenNotes positively. Additionally, there were observed increases in health knowledge and efficacy in patient-physician interactions. A statistically significant improvement in mobile health literacy was also confirmed. Conclusions The implementation of the Open-CHA service significantly enhanced mobile health literacy among patients with craniofacial deformities and their caregivers, indicating positive outcomes for the potential adoption of OpenNotes in Korea. This suggests that introducing OpenNotes into the Korean healthcare system is appropriate.

Objectives: This study aimed to assess the feasibility of implementing OpenNotes in Korea. It involved developing and evaluating the Open-CHA service, which provides clinical summary information to patients diagnosed with craniofacial deformities and their caregivers following outpatient visits. Methods: The study included 109 patients diagnosed with craniofacial deformities, along with their caregivers. The Open-CHA service was developed by referencing OpenNotes and involved a user needs assessment, a pilot test, and an evaluation of its effectiveness. Data were analyzed using descriptive statistics and the paired t-test. Results: Short message service templates for the Open-CHA service based on a user needs assessment conducted with patients, caregivers, and healthcare professionals. These templates were refined and improved following a pilot test. After the implementation of the Open-CHA service, most participants evaluated OpenNotes positively. Additionally, there were observed increases in health knowledge and efficacy in patient-physician interactions. A statistically significant improvement in mobile health literacy was also confirmed. Conclusions The implementation of the Open-CHA service significantly enhanced mobile health literacy among patients with craniofacial deformities and their caregivers, indicating positive outcomes for the potential adoption of OpenNotes in Korea. This suggests that introducing OpenNotes into the Korean healthcare system is appropriate.