Browsing by Author "Park, Yu Rang"
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- ItemA Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study.(0000-00-00) Lee, Jang Ho; Park, Yu Rang; Kweon, Solbi; Kim, Seulgi; Ji, Wonjun; Choi, Chang-MinBACKGROUND During intrahospital transport adverse events are inevitable Real time monitoring can be helpful for preventing these events during intrahospital transport OBJECTIVE We attempted to determine the viability of risk signal detection using wearable devices and mobile apps during intrahospital transport An alarm was sent to clinicians in the event of oxygen saturation below 90 heart rate above 140 or below 60 beats per minute bpm and network errors We validated the reliability of the risk signal transmitted over the network METHODS We used two wearable devices to monitor oxygen saturation and heart rate for 23 patients during intrahospital transport for diagnostic workup or rehabilitation To determine the agreement between the devices records collected every 4 seconds were matched and imputation was performed if no records were collected at the same time by both devices We used intraclass correlation coefficients ICC to evaluate the relationships between the two devices RESULTS Data for 21 patients were delivered to the cloud over LTE and data for two patients were delivered over Wi Fi Monitoring devices were used for 20 patients during intrahospital transport for diagnostic work up and for three patients during rehabilitation Three patients using supplemental oxygen before the study were included In our study the ICC for the heart rate between the two devices was 0 940 95 CI 0 939 0 942 and that of oxygen saturation was 0 719 95 CI 0 711 0 727 Systemic error analyzed with Bland Altman analysis was 0 428 for heart rate and 1 404 for oxygen saturation During the study 14 patients had 20 risk signals nine signals for eight patients with less than 90 oxygen saturation four for four patients with a heart rate of 60 bpm or less and seven for five patients due to network error CONCLUSIONS We developed a system that notifies the health care provider of the risk level of a patient during transportation using a wearable device and a mobile app Although there were some problems such as missing values and network errors this paper is meaningful in that the previously mentioned risk detection system was validated with actual patients
- ItemCorrection: A Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study.(0000-00-00) Lee, Jang Ho; Park, Yu Rang; Kweon, Solbi; Kim, Seulgi; Ji, Wonjun; Choi, Chang-MinThis corrects the article DOI
- ItemEffect of self-monitoring on long-term patient engagement with mobile health applications.(0000-00-00) Lee, Kyunghee; Kwon, Hyeyon; Lee, Byungtae; Lee, Guna; Lee, Jae Ho; Park, Yu Rang; Shin, Soo-YongDespite the growing adoption of the mobile health mHealth applications apps few studies address concerns with low retention rates This study aimed to investigate how the usage patterns of mHealth app functions affect user retention We collected individual usage logs for 1 439 users of single tethered personal health record app which spanned an 18 months period from August 2011 to January 2013 The user logs contained timestamps whenever an individual uses each function which enables us to identify the usage patterns based on the intensity of using a particular function in the app We then estimated how these patterns were related to 1 the app usage over time using the random effect model and 2 the probability of stopping the use of the application using the Cox proportional hazard model The analyses suggested that the users utilize the app most at the time of the adoption and gradually reduce their usage over time The average duration of use after starting the app was 25 62 weeks SD 18 41 The degree of the usage reduction however decreases as the self monitoring function is more frequently used coefficient 0 002 P 0 013 none of the other functions has this effect Moreover engaging with the self monitoring function frequently coefficient 0 18 P 0 003 and regularly coefficient 0 10 P 0 001 significantly also reduces the probability of abandoning the application Specifically the estimated survival rate indicates that after 40 weeks since the adoption the probability of the regular users of self monitoring to stay in use was about 80 while that of non user was about 60 This study provides the empirical evidence that sustained use of mHealth app is closely linked to the regular usage on self monitoring function The implications can be extended to the education of users and physicians to produce better outcomes as well as application development for effective user interfaces
- ItemImpact of a Wearable Device-Based Walking Programs in Rural Older Adults on Physical Activity and Health Outcomes: Cohort Study.(0000-00-00) Jang, Il-Young; Kim, Hae Reong; Lee, Eunju; Jung, Hee-Won; Park, Hyelim; Cheon, Seon-Hee; Lee, Young Soo; Park, Yu RangBACKGROUND Community dwelling older adults living in rural areas are in a less favorable environment for health care compared with urban older adults We believe that intermittent coaching through wearable devices can help optimize health care for older adults in medically limited environments OBJECTIVE We aimed to evaluate whether a wearable device and mobile based intermittent coaching or self management could increase physical activity and health outcomes of small groups of older adults in rural areas METHODS To address the above evaluation goal we carried out the Smart Walk program a health care model wherein a wearable device is used to promote self exercise particularly among community dwelling older adults managed by a community health center We randomly selected older adults who had enrolled in a population based prospective cohort study of aging the Aging Study of Pyeongchang Rural Area The Smart Walk program was a 13 month program conducted from March 2017 to March 2018 and included 6 months of coaching 1 month of rest and 6 months of self management We evaluated differences in physical activity and health outcomes according to frailty status and conducted pre and postanalyses of the Smart Walk program We also performed intergroup analysis according to adherence of wearable devices RESULTS We recruited 22 participants 11 robust and 11 prefrail older adults The two groups were similar in most of the variables except for age frailty index and Short Physical Performance Battery score associated with frailty criteria After a 6 month coaching program the prefrail group showed significant improvement in usual gait speed mean 0 73 SD 0 11 vs mean 0 96 SD 0 27 P 02 International Physical Activity Questionnaire scores in kcal mean 2790 36 SD 2224 62 vs mean 7589 72 SD 4452 52 P 01 and European Quality of Life 5 Dimensions score mean 0 84 SD 0 07 vs mean 0 90 SD 0 07 P 02 although no significant improvement was found in the robust group The average total step count was significantly different and was approximately four times higher in the coaching period than in the self management period 5 584 295 83 vs 1 289 084 66 PUnder 001 We found that participants in the long self group who used the wearable device for the longest time showed increased body weight and body mass index by mean 0 65 SD 1 317 and mean 0 097 SD 0 513 respectively compared with the other groups CONCLUSIONS Our Smart Walk program improved physical fitness anthropometric measurements and geriatric assessment categories in a small group of older adults in rural areas with limited resources for monitoring Further validation through various rural public health centers and in a large number of rural older adults is required
- ItemManaging Patient-Generated Health Data Through Mobile Personal Health Records: Analysis of Usage Data.(0000-00-00) Park, Yu Rang; Lee, Yura; Kim, Ji Young; Kim, Jeonghoon; Kim, Hae Reong; Kim, Young-Hak; Kim, Woo Sung; Lee, Jae-HoBACKGROUND Personal health records PHRs and mHealth apps are considered essential tools for patient engagement Mobile PHRs mPHRs can be a platform to integrate patient generated health data PGHD and patients medical information However in previous studies actual usage data and PGHD from mPHRs have not been able to adequately represent patient engagement OBJECTIVE By analyzing 5 years PGHD from an mPHR system developed by a tertiary hospital in South Korea we aimed to evaluate how PGHD were managed and identify issues in PGHD management based on actual usage data Additionally we analyzed how to improve patient engagement with mPHRs by analyzing the actively used services and long term usage patterns METHODS We gathered 5 years December 2010 to December 2015 of log data from both hospital patients and general users of the app We gathered data from users who entered PGHD on body weight blood pressure BP blood glucose levels 10 year cardiovascular disease CVD risk metabolic syndrome risk medication schedule insulin and allergy We classified users according to whether they were patients or general users based on factors related to continuous use 28 days for weight BP and blood glucose and 180 days for CVD and metabolic syndrome and analyzed the patients characteristics We compared PGHD entry counts and the proportion of continuous users for each PGHD by user type RESULTS The total number of mPHR users was 18 265 patients n 16 729 91 59 with 3620 users having entered weight followed by BP n 1625 blood glucose n 1374 CVD n 764 metabolic syndrome n 685 medication n 252 insulin n 72 and allergy n 61 Of those 18 256 users 3812 users had at least one PGHD measurement of whom 175 used the PGHD functions continuously patients n 142 81 14 less than 1 of the users had used it for more than 4 years Except for weight BP blood glucose CVD and metabolic syndrome the number of PGHD records declined General users continuous use of PGHD was significantly higher than that of patients in the blood glucose PUnder 001 and BP P 03 functions Continuous use of PGHD in health management BP blood glucose and weight was significantly greater among older users PUnder 001 and men PUnder 001 In health management BP weight and blood glucose overall chronic disease and continuous use of PGHD were not statistically related P 08 but diabetes PUnder 001 and cerebrovascular diseases P 03 were significant CONCLUSIONS Although a small portion of users managed PGHD continuously PGHD has the potential to be useful in monitoring patient health To realize the potential specific groups of continuous users must be identified and the PGHD service must target them Further evaluations for the clinical application of PGHD feedback regarding user interfaces and connections with wearable devices are needed