Background: South Korea took preemptive action against coronavirus disease (COVID-19) by implementing extensive testing, thorough epidemiological investigation, strict social distancing, and rapid treatment of patients according to disease severity. The Korean government entrusted large-scale hospitals with the operation of living and treatment support centers (LTSCs) for the management for clinically healthy COVID-19 patients. Objective: The aim of this paper is to introduce our experience implementing information and communications technology (ICT)-based remote patient management systems at a COVID-19 LTSC. Methods: We adopted new electronic health record templates, hospital information system (HIS) dashboards, cloud-based medical image sharing, a mobile app, and smart vital sign monitoring devices. Results: Enhancements were made to the HIS to assist in the workflow and care of patients in the LTSC. A dashboard was created for the medical staff to view the vital signs and symptoms of all patients. Patients used a mobile app to consult with their physician or nurse, answer questionnaires, and input self-measured vital signs; the results were uploaded to the hospital information system in real time. Cloud-based image sharing enabled interoperability between medical institutions. Korea’s strategy of aggressive mitigation has “flattened the curve” of the rate of infection. A multidisciplinary approach was integral to develop systems supporting patient care and management at the living and treatment support center as quickly as possible. Conclusions: Faced with a novel infectious disease, we describe the implementation and experience of applying an ICT-based patient management system in the LTSC affiliated with Seoul National University Hospital. ICT-based tools and applications are increasingly important in health care, and we hope that our experience will provide insight into future technology-based infectious disease responses.

Background: New health care services such as smart health care and digital therapeutics have greatly expanded. To effectively use these services, digital health literacy skills, involving the use of digital devices to explore and understand health information, are important. Older adults, requiring consistent health management highlight the need for enhanced digital health literacy skills. To address this issue, it is imperative to develop methods to assess older adults’ digital health literacy levels. Objective: This study aimed to develop a tool to measure digital health literacy. To this end, it reviewed existing literature to identify the components of digital health literacy, drafted preliminary items, and developed a scale using a representative sample. Methods: We conducted a primary survey targeting 600 adults aged 55-75 years and performed an exploratory factor analysis on 74 preliminary items. Items with low factor loadings were removed, and their contents were modified to enhance their validity. Then, we conducted a secondary survey with 400 participants to perform exploratory and confirmatory factor analyses. Results: A digital health literacy scale consisting of 25 items was developed, comprising 4 subfactors: use of digital devices, understanding health information, use and decision regarding health information, and use intention. The model fit indices indicated excellent structural validity (Tucker-Lewis Index=0.924, comparative fit index=0.916, root-mean-square error of approximation=0.088, standardized root-mean-square residual=0.044). High convergent validity (average variance extracted>0.5) and reliability (composite reliability>0.7) were observed within each factor. Discriminant validity was also confirmed as the square root of the average variance extracted was greater than the correlation coefficients between the factors. This scale demonstrates high reliability and excellent structural validity. Conclusions: This study is a significant first step toward enhancing digital health literacy among older adults by developing an appropriate tool for measuring digital health literacy. We expect this study to contribute to the future provision of tailored education and treatment based on individual literacy levels.

Park D, et al. J Korean Med Sci. 2017 Jan;32(1):95-101. https://doi.org/10.3346/jkms.2017.32.1.95

Smoking is an important variable for clinical research, but there are few studies regarding automatic obtainment of smoking classification from unstructured bilingual electronic health records (EHR). We aim to develop an algorithm to classify smoking status based on unstructured EHRs using natural language processing (NLP). With acronym replacement and Python package Soynlp, we normalize 4711 bilingual clinical notes. Each EHR notes was classified into 4 categories: current smokers, past smokers, never smokers, and unknown. Subsequently, SPPMI (Shifted Positive Point Mutual Information) is used to vectorize words in the notes. By calculating cosine similarity between these word vectors, keywords denoting the same smoking status are identified. Compared to other keyword extraction methods (word co-occurrence-, PMI-, and NPMI-based methods), our proposed approach improves keyword extraction precision by as much as 20.0%. These extracted keywords are used in classifying 4 smoking statuses from our bilingual EHRs. Given an identical SVM classifier, the F1 score is improved by as much as 1.8% compared to those of the unigram and bigram Bag of Words. Our study shows the potential of SPPMI in classifying smoking status from bilingual, unstructured EHRs. Our current findings show how smoking information can be easily acquired for clinical practice and research.

Health information exchange can improve health outcomes and reduce unnecessary medical expenses. An important task in health information exchange is to prove data integrity and strengthen the right to self-determination of individuals. This can be addressed using blockchain technology and dynamic consents. We aimed to develop a blockchain-based mobile platform called HealthPocket to exchange reliable health information with proven integrity through a dynamic consent system based on the HL7 FHIR standards. Through HealthPocket, subjects can selectively provide their consent to share specific medical and PGHD through proper authorization, and each response is converted into the JSON format with FHIR compatibility. We conducted a usability test to demonstrate health information exchange between primary and tertiary medical institutions. A total of 116 subjects used the HealthPocket mobile application to selectively share health information for at least one month, and conducted a questionnaire about their experience. In addition, medical staff of the institution could access the medical information shared by the participants and use it for treatment. The user surveys for patients examined the perceived usefulness, perceived ease of use, and overall service satisfaction. The mean overall satisfaction with the health information exchange service was the highest (4.67 out of 5 points). As security, personal information protection, and interoperability are main concerns related to health information exchange, blockchain technology can provide suitable solutions. For instance, when health information is exchanged using blockchain technology, it is impossible to alter data blocks. Therefore, by using a blockchain-based platform and dynamic consent system, we ensured the integrity of medical data.

Background: Digital health care is an important strategy in the war against COVID-19. South Korea introduced living and treatment support centers (LTSCs) to control regional outbreaks and care for patients with asymptomatic or mild COVID-19. Seoul National University Hospital (SNUH) introduced information and communications technology (ICT)–based solutions to manage clinically healthy patients with COVID-19. Objective: This study aims to investigate satisfaction and usability by patients and health professionals in the optimal use of a mobile app and wearable device that SNUH introduced to the LTSC for clinically healthy patients with COVID-19. Methods: Online surveys and focus group interviews were conducted to collect quantitative and qualitative data. Results: Regarding usability testing of the wearable device, perceived usefulness had the highest mean score of 4.45 (SD 0.57) points out of 5. Regarding usability of the mobile app, perceived usefulness had the highest mean score of 4.62 (SD 0.48) points out of 5. Regarding satisfaction items for the mobile app among medical professionals, the “self-reporting” item had the highest mean score of 4.42 (SD 0.58) points out of 5. In focus group interviews of health care professionals, hospital information system interfacing was the most important functional requirement for ICT-based COVID-19 telemedicine. Conclusions: Improvement of patient safety and reduction of the burden on medical staff were the expected positive outcomes. Stability and reliability of the device, patient education, accountability, and reimbursement issues should be considered as part of the development of remote patient monitoring. In responding to a novel contagious disease, telemedicine and a wearable device were shown to be useful during a global crisis.