Benefits of Information Technology in Healthcare: Artificial Intelligence, Internet of Things, and Personal Health Records.

OBJECTIVES: Systematic evaluations of the benefits of health information technology (HIT) play an essential role in enhancing healthcare quality by improving outcomes. However, there is limited empirical evidence regarding the benefits of IT adoption in healthcare settings. This study aimed to review the benefits of artificial intelligence (AI), the internet of things (IoT), and personal health records (PHR), based on scientific evidence. METHODS: The literature published in peer-reviewed journals between 2016 and 2022 was searched for systematic reviews and meta-analysis studies using the PubMed, Cochrane, and Embase databases. Manual searches were also performed using the reference lists of systematic reviews and eligible studies from major health informatics journals. The benefits of each HIT were assessed from multiple perspectives across four outcome domains. RESULTS: Twenty-four systematic review or meta-analysis studies on AI, IoT, and PHR were identified. The benefits of each HIT were assessed and summarized from a multifaceted perspective, focusing on four outcome domains: clinical, psycho-behavioral, managerial, and socioeconomic. The benefits varied depending on the nature of each type of HIT and the diseases to which they were applied. CONCLUSIONS: Overall, our review indicates that AI and PHR can positively impact clinical outcomes, while IoT holds potential for improving managerial efficiency. Despite ongoing research into the benefits of health IT in line with advances in healthcare, the existing evidence is limited in both volume and scope. The findings of our study can help identify areas for further investigation.

Comparison of cardiovascular disease risk in women with and without breast cancer: secondary data analysis with the 2014-2018 korean national health and nutrition examination survey.

BACKGROUND: Aging breast cancer survivors may be at an elevated risk of cardiovascular disease (CVD), but little is known about CVD risk assessment and breast cancer in Korean women. We hypothesized that Korean breast cancer survivors would have higher risks of future CVD within the next 10 years (i.e., Framingham Risk Score [FRS]) than women without cancer. OBJECTIVES: (1) To compare FRS-based CVD risks in women with and without breast cancer based on propensity score matching; and (2) To explore adiposity-related measures in relation to FRS in Korean women with breast cancer. METHODS: Using the cross-sectional data from the 2014-2018 Korean National Health and National Survey (KNHANES), we identified 136 women with breast cancer aged 30-74 years who had no other cancer and no CVD. The comparison group of 544 women with no cancer were selected by 1:4 nearest-neighbor propensity score matching based on breast cancer diagnosis. CVD risk was assessed by FRS based on multiple traditional risk factors (e.g., cholesterol, blood pressure, diabetes, and smoking). Adiposity was measured by physical examination, including body mass index (BMI) and waist-to-height ratio (WHtR). Physical activity and health behaviors were assessed by self-reports. RESULTS: Women with breast cancer (mean age of 57 years) had similar FRS levels at a low-risk category (< 10%) to women with no cancer (4.9% vs. 5.5%). Breast cancer survivors (mean 8.5 survival years) presented at significantly lower levels of total cholesterol, BMI, and WHtR (all p values < 0.05) than their counterpart. Within the breast cancer group, WHtR ≥ 0.5 was associated with higher FRS, compared to WHtR < 0.5. FRS was not different by survival < 5 years or ≥ 5 years after breast cancer diagnosis. CONCLUSIONS: FRS-based CVD risks were not different in Korean, mostly postmenopausal, women by breast cancer status. Whereas breast cancer survivors had even lower levels of lipid and adiposity measures than women without cancer, those values indicating borderline cardiometabolic risk suggest continued screening and management efforts for these aging women. Future studies are needed to examine longitudinal trajectories of CVD risk factors and CVD outcomes among Korean breast cancer survivors.

Association of Depressive Mood and Frailty With Mortality and Health Care Utilization: Korean National Cohort Study.

OBJECTIVES: To investigate the association of depressive mood and frailty with mortality and health care utilization (HCU) and identify the coexisting effect of depressive mood and frailty in older adults. DESIGN: A retrospective study using nationwide longitudinal cohort data. SETTING AND PARTICIPANTS: A total of 27,818 older adults age 66 years from the National Screening Program for Transitional Ages between 2007 and 2008, part of the National Health Insurance Service-Senior cohort. METHODS: Depressive mood and frailty were measured by the Geriatric Depression Scale and Timed Up and Go test, respectively. Outcomes were mortality and HCU, including long-term care services (LTCS), hospital admissions, and total length of stay (LOS) from the index date to December 31, 2015. Cox proportional hazards regression and zero-inflated negative binomial regression were performed to identify differences in outcomes by depressive mood and frailty. RESULTS: Participants with depressive mood and frailty represented 50.9% and 2.4%, respectively. The prevalence of mortality and LTCS use in the overall participants was 7.1% and 3.0%, respectively. More than 3 hospital admissions (36.7%) and total LOS above 15 days (53.2%) were the most common. Depressive mood was associated with LTCS use [hazard ratio (HR) 1.22, 95% confidence interval (CI) 1.05-1.42] and hospital admissions [incidence rate ratio (IRR) 1.05, 95% CI 1.02-1.08]. Frailty had associations with mortality risk (HR 1.96, 95% CI 1.44-2.68), LTCS use (HR 4.86, 95% CI 3.45-6.84), and LOS (IRR 1.30, 95% CI 1.06-1.60). The coexistence of depressive mood and frailty was associated with increased LOS (IRR 1.55, 95% CI 1.16-2.07). CONCLUSIONS AND IMPLICATIONS: Our findings highlight the need to focus on depressive mood and frailty to reduce mortality and HCU. Identifying combined problems in older adults may contribute to healthy aging by reducing adverse health outcomes and the burden of health care costs.

Development of an Ecological Momentary Assessment-Triggered Text Message Library for Peripheral Artery Disease.

This study developed an ecological momentary assessment (EMA)-triggered text message library based on the behavior change wheel framework to encourage exercise engagement in patients with peripheral artery disease (PAD). This study was conducted in three steps. In Step 1, semi-structured interviews were conducted with 15 patients with PAD. Their accounts of their exercise experiences revealed six barriers and three facilitators through thematic analysis. In Step 2, based on the findings from the prior step, the EMA survey was developed; its items included barriers to exercise, PAD-related leg symptoms, and general conditions. In Step 3, intervention functions to overcome exercise barriers were mapped, and 120 text messages were generated. Responses to the exercise barriers in the EMA survey triggered the automatic text messages. Additional studies are needed to examine the end-user acceptability of the text message library and the effectiveness of EMA-triggered text message interventions.

Diagnostic accuracy of clinical outcome prediction using nursing data in intensive care patients: A systematic review.

BACKGROUND: Nursing data consist of observations of patients' conditions and information on nurses' clinical judgment based on critically ill patients' behavior and physiological signs. Nursing data in electronic health records were recently emphasized as important predictors of patients' deterioration but have not been systematically reviewed. OBJECTIVE: We conducted a systematic review of prediction models using nursing data for clinical outcomes, such as prolonged hospital stay, readmission, and mortality in intensive care patients, compared to physiological data only. In addition, the type of nursing data used in prediction model developments was investigated. DESIGN: A systematic review. METHODS: PubMed, CINAHL, Cochrane CENTRAL, EMBASE, IEEE Xplore Digital Library, Web of Science, and Scopus were searched. Clinical outcome prediction models using nursing data for intensive care patients were included. Clinical outcomes were prolonged hospital stay, readmission, and mortality. Data were extracted from selected studies such as study design, data source, outcome definition, sample size, predictors, reference test, model development, model performance, and evaluation. The risk of bias and applicability was assessed using the Prediction model Risk of Bias Assessment Tool checklist. Descriptive summaries were produced based on paired forest plots and summary receiver operating characteristic curves. RESULTS: Sixteen studies were included in the systematic review. The data types of predictors used in prediction models were categorized as physiological data, nursing data, and clinical notes. The types of nursing data consisted of nursing notes, assessments, documentation frequency, and flowsheet comments. The studies using physiological data as a reference test showed higher predictive performance in combined data or nursing data than in physiological data. The overall risk of bias indicated that most of the included studies have a high risk. CONCLUSIONS: This study was conducted to identify and review the diagnostic accuracy of clinical outcome prediction using nursing data in intensive care patients. Most of the included studies developed models using nursing notes, and other studies used nursing assessments, documentation frequency, and flowsheet comments. Although the findings need careful interpretation due to the high risk of bias, the area under the curve scores of nursing data and combined data were higher than physiological data alone. It is necessary to establish a strategy in prediction modeling to utilize nursing data, clinical notes, and physiological data as predictors, considering the clinical context rather than physiological data alone. REGISTRATION: The protocol for this study is registered with PROSPERO (registration number: CRD42021273319).

Mobile health platform based on user-centered design to promote exercise for patients with peripheral artery disease.

BACKGROUND: Peripheral artery disease (PAD) is a cardiovascular disease that can be improved by risk factor modification. Mobile health (mHealth) intervention is an effective method of healthcare delivery to promote behavior changes. An mHealth platform can encourage consistent involvement of participants and healthcare providers for health promotion. This study aimed to develop an mHealth platform consisting of a smartphone application (app) synchronized with a wearable activity tracker and a web-based portal to support exercise intervention in patients with PAD. METHODS: This study was conducted based on an iterative development process, including analysis, design, and implementation. In the analysis phase, a literature review and needs assessment through semi-structured interviews (n = 15) and a questionnaire-based survey (n = 138) were performed. The initial prototype design and contents were developed based on the users' requirements. In the implementation phase, multidisciplinary experts (n = 4) evaluated the heuristics, following which the mHealth platform was revised. User evaluation of the usability was performed by nurses (n = 4) and patients with PAD (n = 3). RESULTS: Through the development process, the functional requirements of the platform were represented through visual display, reminder, education, self-monitoring, goal setting, goal attainment, feedback, and recording. In-app videos of exercise and PAD management were produced to provide information and in-app automatic text messages were developed for user motivation. The final version of the platform was rated 67.86 out of 100, which indicated "good" usability. CONCLUSIONS: The mHealth platform was designed and developed for patients with PAD and their healthcare providers. This platform can be used to educate and promote individualized exercise among patients with PAD.

Major Adverse Events in Patients with Peripheral Artery Disease after Endovascular Revascularization: A Retrospective Study.

OBJECTIVE: For peripheral artery disease (PAD) patients, after endovascular revascularization, it is crucial to manage associated factors that can affect the risk of major adverse events. We aimed to investigate the associated factors of major adverse events in these patients. MATERIALS AND METHODS: We conducted a retrospective longitudinal analysis using the electronic medical records from a tertiary hospital in Korea and included the data of 1263 patients. Eligible patients were categorized into four groups based on diabetes mellitus (DM) and regular exercise. The major adverse events included major adverse limb events and major adverse cardiovascular events. Major adverse events-free survival was assessed using the Kaplan-Meier method, and associated factors of major adverse events were analyzed using Cox proportional hazards analyses. RESULTS: Kaplan-Meier survival curves showed that patients with DM and non-regular exercise had a shorter major adverse events-free survival. The Cox regression analysis showed that for patients with critical limb ischemia or chronic kidney disease, the risk of major adverse events increased, while group variables were not significant. CONCLUSION: Target management of patients with DM, critical limb ischemia, and chronic kidney disease is essential to reduce major adverse events after endovascular revascularization in patients with PAD.

Development of Home-Based Exercise Mobile Application for Patients with Peripheral Artery Disease.

This study aimed to develop a home-based exercise application to improve the exercising performance in patients with peripheral artery disease. This application is based on a theoretical framework and is paired with a wearable device, Fitbit Charge4. The application comprised five main categories with 30 screens: login, a record of exercise, goal achievement, information, and motivation. Using the application to nursing practice can manage and encourage patients to exercise without limitations of time and place.

Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision.

Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelligence. One such problem are deepfakes. Deepfake is a compound word for deep learning and fake. It refers to a fake video created using artificial intelligence technology or the production process itself. Deepfakes can be exploited for political abuse, pornography, and fake information. This paper proposes a method to determine integrity by analyzing the computer vision features of digital content. The proposed method extracts the rate of change in the computer vision features of adjacent frames and then checks whether the video is manipulated. The test demonstrated the highest detection rate of 97% compared to the existing method or machine learning method. It also maintained the highest detection rate of 96%, even for the test that manipulates the matrix of the image to avoid the convolutional neural network detection method.

Functional Status and Health-Related Quality of Life in Patients with Peripheral Artery Disease: A Cross-Sectional Study.

Peripheral artery disease (PAD) is a progressive atherosclerotic disease that negatively affects individuals' functional status and health-related quality of life (HRQOL). This study aimed to investigate the HRQOL and associated factors in patients with PAD in Korea. We conducted a cross-sectional study using self-administered questionnaires in a tertiary hospital in Seoul. We measured HRQOL using the EuroQol-5 dimensions-5 levels (EQ-5D-5L) questionnaire and the functional status using a PAD-specific walking impairment questionnaire. We also measured health behavior, social support, walking impairment, general health perceptions, and clinical characteristics; lastly, we performed a descriptive analysis and multiple linear regression analysis. Participants of this study comprised 138 patients (mean age 69.04 ± 10.94 years; men 91.3%). The mean EQ-5D-5L utility score was 0.81 ± 0.17. The patients' HRQOL was significantly associated with claudication pain (ß = -0.188, p = 0.012), walking distance (ß = 0.371, p < 0.001), and stair climbing (ß = 0.315, p = 0.001). The regression model predicted 60.4% of patients' HRQOL (F = 15.92, p < 0.001). Our study showed that less severe claudication pain and a low degree of difficulty in walking distance and stair climbing were significantly related to better HRQOL. To enhance patients' HRQOL, health professionals should focus on managing symptoms and improving functional status.

Factors associated with nurses' user resistance to change of electronic health record systems.

BACKGROUND: Electronic health record (EHR) systems often face user resistance in hospitals, which results in a failure to acquire their full benefits. To implement the EHR successfully, it is crucial to reduce nurses' resistance to use the system. This study aimed to investigate the factors associated with nurses' resistance to use the EHR system. METHODS: A descriptive correlational study was conducted with nurses working at four university hospitals in Korea using self-administered questionnaires to measure user resistance behavior, resistance to change, perceived usefulness, perceived ease of use, perceived value, colleagues' opinions, self-efficacy for change, and organizational support for change. Path analysis was performed to examine direct and indirect association with user resistance behavior. RESULTS: A total of 223 nurses completed the questionnaires. All seven factors were found to be significantly associated with user resistance, either directly or indirectly. The total effect on user resistance behavior was highest in resistance to change (0.65), followed by perceived usefulness (- 0.33); both had direct but no indirect effects. Conversely, self-efficacy for change (- 0.25), perceived value (- 0.21), colleagues' opinions (- 0.16), perceived ease of use (- 0.16), and organizational support for change (- 0.05) had indirect but no direct effects. CONCLUSIONS: The study examined the factors associated with nurses' user resistance behavior after the implementation of a new EHR system. These findings could help hospitals develop better EHR implementation strategies to reduce user resistance behavior among the nursing staff.

Effectiveness of Mobile Health-Based Exercise Interventions for Patients with Peripheral Artery Disease: Systematic Review and Meta-Analysis.

BACKGROUND: Peripheral artery disease (PAD) affects over 236 million people worldwide, and exercise interventions are commonly used to alleviate symptoms of this condition. However, no previous systematic review has evaluated the effects of mobile health (mHealth)-based exercise interventions for patients with PAD. OBJECTIVE: This study aimed to assess the effect of mHealth-based exercise interventions on walking performance, functional status, and quality of life in patients with PAD. METHODS: A systematic review and meta-analysis were conducted. We searched in seven databases to identify randomized controlled trials of patients with PAD published in English up to December 4, 2020. Studies were included if patients participated in mHealth-based exercise interventions and were assessed for walking performance. We analyzed pooled effect size on walking performance, functional status, and quality of life based on the standardized mean differences between groups. RESULTS: A total of seven studies were selected for the systematic review, and six studies were included in the meta-analysis. The duration of interventions in the included studies was 12 to 48 weeks. In the pooled analysis, when compared with the control groups, the mHealth-based exercise intervention groups were associated with significant improvements in pain-free walking (95% CI 0.13-0.88), maximal walking (95% CI 0.03-0.87), 6-minute walk test (6MWT) distance (95% CI 0.59-1.24), and walking distance (95% CI 0.02-0.49). However, benefits of the interventions on walking speed, stair-climbing ability, and quality of life were not observed. CONCLUSIONS: mHealth-based exercise interventions for patients with PAD were beneficial for improving pain-free walking, maximal walking, and 6MWT distance. We found that exercise interventions using mHealth are an important strategy for improving the exercise effectiveness and adherence rate of patients with PAD. Future studies should consider the use of various and suitable functions of mHealth that can increase the adherence rates and improve the effectiveness of exercise.

Mothers' experience of caring for home-quarantined children after close contact with COVID-19 in Korea: an exploratory qualitative study.

Purpose: The world saw a shift into a new society consequent to the coronavirus disease 2019 (COVID-19), which made home quarantine mandatory for a person in close contact with those who tested positive. For children, however, home quarantine was not limited only to themselves but parents, especially mothers were involved and required to quarantine. This qualitative study aimed to explore and understand mothers' experience and their related psychosocial issues while caring for their school-aged children in Korea, who had to home quarantine after coming in close contact with COVID-19 positive individuals. Methods: Data were collected from October 2020 to January 2021 via in-depth, semi-structured interviews with nine mothers of children who had to home quarantine. Interviews were conducted face-to-face in an independent space near the participant's home or workplace (n=5) or via online platforms or telephone (n=4). The data were analyzed using thematic analysis through several iterative team meetings. Results: Thematic analysis revealed the following four themes: "Unable to be relieved due to uncertain situations surrounding me," "Blame and hurt toward me, others, and one another," "Pulling myself together for my children in my broken daily life," and "Changes in the meaning of life amid COVID-19." Conclusion: The narratives show that mothers experienced psychosocial difficulties while caring for their children during home quarantine. It is necessary to reduce the social stigma toward individuals in home quarantine and establish policies to ensure work-family compatibility for such mothers.

Building Consensus on the Priority-Setting for National Policies in Health Information Technology: A Delphi Survey.

OBJECTIVE: With growing attention on the healthcare industry as a potential market for big data and artificial intelligence in the Fourth Industrial Revolution, countries around the world are introducing and developing various policies and projects related to health information technology (HIT). To assist prioritizing HIT topics in policy making, this study adopts the Delphi technique to garner expert opinions from various fields of health informatics. METHODS: Data were collected from November 2019 to February 2020 using the Delphi technique through two rounds of surveys administered via email. The Delphi panel consisted of 16 experts with a high level of experience in health informatics. They were from the Health Information Policy Advisory Committee of the Ministry of Health and Welfare of Korea, and the board of directors of the Korean Society of Medical Informatics. The experts were asked to assess the importance, urgency, and difficulty of HIT topics in three domains: technology, application, and infrastructure. RESULTS: Of the 40 topic items, a 100% agreement was reached for the importance of 6 items, including 2 items in technology, 1 item in application, and 3 items in infrastructure domains. Especially, Quadrant I of a 2×2 matrix showing high importance and high urgency included 7 items in the technology domain, 2 items in the application domain, and 13 items in the infrastructure domain. CONCLUSION: Most items with high importance and urgency belonged to the infrastructure domain. The findings indicated that fostering an infrastructural environment should be polices with top priorities of HIT.

JLVEA: Lightweight Real-Time Video Stream Encryption Algorithm for Internet of Things.

Along with the recent growth of Internet of Things (IoT) security camera market, there have been a number of personal information leakage incidents from security attacks targeting such cameras. Therefore, a permutation-based video encryption algorithm was proposed to secure video streams in low-performance processors such as IoT security cameras. However, existing permutation-based video encryption algorithms are vulnerable to known-plaintext attacks since they use the same permutation list for every frame. Moreover, situation deduction based on the color composition is possible. In this paper, we propose a new permutation-based video encryption algorithm that updates the permutation list for every frame using a crypto secure pseudo-random number generator without significantly increasing memory usage. By doing so, the algorithm becomes robust to known-plaintext attacks, which has been a common problem with existing permutation-based video encryption algorithms. In addition, color channel separation can prevent attackers from deducing situations through color composition. Pre-compression encryption is applied to make the algorithm robust to data loss because of packet loss. We implement the proposed algorithm and conduct an experiment to show its performance in terms of probability of data loss because of packet loss, encryption speed, and memory usage.

Development of Cloud-Based UAV Monitoring and Management System.

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation.

DMP: detouring using multiple paths against jamming attack for ubiquitous networking system.

To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio) and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector), and a conventional JAM (Jammed Area Mapping) service with one reroute.