No abstract available.
Internet*

OBJECTIVES: This study aimed to develop an effective and efficient obesity treatment and management service platform for obese children/teenagers. METHODS: The integrated smart platform was planned and established through cooperation with service providers such as hospitals and public health centers, obese children/teenagers who constitute the service's user base, and IT development and policy institutions and companies focusing on child-teen obesity management and treatment. RESULTS: Based on guidelines on intervention strategies to manage child-teen obesity, we developed two patient/parent mobile applications, one web-monitoring service for medical staff, one mobile application for food-craving endurance, and one mobile application for medical examinations. CONCLUSIONS: The establishment of the integrated service platform was successfully completed; however, this study was restrictively to the hospital where the pilot program took place. The effectiveness of the proposed platform will be verified in the future in tests involving other organizations.
Delivery of Health Care ; Humans ; Medical Staff ; Mobile Applications ; Obesity* ; Pediatric Obesity ; Public Health ; User-Computer Interface

OBJECTIVES: We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. METHODS: We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. RESULTS: An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. CONCLUSIONS: The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.
Diagnosis ; Eosine Yellowish-(YS) ; Fluorescence ; Hematoxylin* ; Image Processing, Computer-Assisted ; Methods* ; Microscopy ; Microscopy, Confocal* ; Staining and Labeling

OBJECTIVES: In hospitals, the pharmacy information system (PIS) is usually a sub-system of the hospital information system (HIS). The PIS supports the distribution and management of drugs, shows drug and medical device inventory, and facilitates preparing needed reports. In this study, pharmacy information systems implemented in general teaching hospitals affiliated to medical universities in Tehran (Iran) were evaluated using a multi-dimensional tool. METHODS: This was an evaluation study conducted in 2015. To collect data, a checklist was developed by reviewing the relevant literature; this checklist included both general and specific criteria to evaluate pharmacy information systems. The checklist was then validated by medical informatics experts and pharmacists. The sample of the study included five PIS in general-teaching hospitals affiliated to three medical universities in Tehran (Iran). Data were collected using the checklist and through observing the systems. The findings were presented as tables. RESULTS: Five PIS were evaluated in the five general-teaching hospitals that had the highest bed numbers. The findings showed that the evaluated pharmacy information systems lacked some important general and specific criteria. Among the general evaluation criteria, it was found that only two of the PIS studied were capable of restricting repeated attempts made for unauthorized access to the systems. With respect to the specific evaluation criteria, no attention was paid to the patient safety aspect. CONCLUSIONS: The PIS studied were mainly designed to support financial tasks; little attention was paid to clinical and patient safety features.
Checklist ; Clinical Pharmacy Information Systems ; Drug Information Services ; Hospital Information Systems ; Hospitals, Teaching* ; Humans ; Information Systems* ; Medical Informatics ; Patient Safety ; Pharmacists ; Pharmacy*

OBJECTIVES: This study was conducted to perform an effect size analysis of psychosocial interventions for internet addiction and to identify the intervention moderators applied to school-aged children. METHODS: For the meta-analysis, studies were included that were published in English or Korean until January 2015, without limitation in terms of the year. They were retrieved from 11 electronic databases and by manual searches according to predefined inclusion criteria. RESULTS: A total of 37 studies were selected, which included 11 treatment conditions and covered a total of 1,490 participants. The effect size estimates showed that psychosocial interventions had a large effect for reducing internet addiction (standardized mean difference [SMD], -1.19; 95% confidence interval [CI], -1.52 to -0.87) and improving self-control (SMD, 0.29; 95% CI, 0.11 to 0.47) and self-esteem (mean difference, 3.58; 95% CI, 2.03 to 5.12). The moderator analyses reveals that group treatments, a selective approach, a long duration, a community setting, or higher school grade had a larger effect. CONCLUSIONS: The findings of this review suggest that psychosocial intervention may be used to prevent Internet addiction in school-aged children, although further research should be conducted using a randomized controlled trial design or diverse age groups to provide evidence-based recommendations.
Behavior, Addictive ; Child ; Humans ; Internet* ; Self-Control*

OBJECTIVES: Despite the importance of the protection of patients' health information in clinical settings, little is known about the awareness of this concept in nursing students due to the lack of a suitable measurement tool. Hence, this study attempted to redevelop the Patients' Health Information Protection Awareness Scale, and evaluate its construct validity and reliability for nursing students. METHODS: A cross-sectional descriptive study was conducted. Nursing students who were in their 3rd and 4th year were recruited from 10 universities in Korea to assess the construct validity, and 30 experts (27 nurses and 3 faculty members) participated in the content validation process. RESULTS: The content validity assessment indicated that 23 items were ideal. The assessment of construct validity using exploratory factor analysis revealed three factors: communication, management, and referrals. They together accounted for 54.1% of the variance in scale scores. The three-factor scale had good fit in the confirmatory factor analysis. Scale reliability was confirmed, with a Cronbach's alpha of 0.94 for all items. CONCLUSIONS: This study was the first attempt to redevelop the Patients' Health Information Protection Awareness Scale for student nurses. The 23-item scale was shown to be a reliable and valid tool. It facilitates the assessment of nursing students' awareness of patient information protection. Academic nursing programs and health organizations can use its scores to implement adequate education plans to safeguard information in nursing students.
Computer Security* ; Education ; Health Information Management ; Humans ; Korea ; Nursing ; Referral and Consultation ; Reproducibility of Results ; Students, Nursing

OBJECTIVES: The number of deaths caused by cardiovascular disease and stroke is predicted to reach 23.3 million in 2030. As a contribution to support prevention of this phenomenon, this paper proposes a mining model using a naïve Bayes classifier that could detect cardiovascular disease and identify its risk level for adults. METHODS: The process of designing the method began by identifying the knowledge related to the cardiovascular disease profile and the level of cardiovascular disease risk factors for adults based on the medical record, and designing a mining technique model using a naïve Bayes classifier. Evaluation of this research employed two methods: accuracy, sensitivity, and specificity calculation as well as an evaluation session with cardiologists and internists. The characteristics of cardiovascular disease are identified by its primary risk factors. Those factors are diabetes mellitus, the level of lipids in the blood, coronary artery function, and kidney function. Class labels were assigned according to the values of these factors: risk level 1, risk level 2 and risk level 3. RESULTS: The evaluation of the classifier performance (accuracy, sensitivity, and specificity) in this research showed that the proposed model predicted the class label of tuples correctly (above 80%). More than eighty percent of respondents (including cardiologists and internists) who participated in the evaluation session agree till strongly agreed that this research followed medical procedures and that the result can support medical analysis related to cardiovascular disease. CONCLUSIONS: The research showed that the proposed model achieves good performance for risk level detection of cardiovascular disease.
Adult* ; Bayes Theorem ; Bays* ; Cardiovascular Diseases* ; Classification ; Coronary Vessels ; Data Mining ; Diabetes Mellitus ; Diagnostic Techniques, Cardiovascular ; Humans ; Kidney ; Medical Records ; Methods ; Mining ; Risk Factors ; Sensitivity and Specificity ; Stroke ; Surveys and Questionnaires

OBJECTIVES: The interpretation of clinical data for the diagnosis of coronary heart disease can be done using algorithms in data mining. Most clinical data interpretation systems for diagnosis developed using data mining algorithms with a black-box approach cannot recognize examination attribute relationships with the incidence of coronary heart disease. METHODS: This study proposes a system to interpretation clinical examination results for the diagnosis of coronary heart disease based the decision tree algorithm. This system comprises several stages. First, oversampling is carried out by a combination of the synthetic minority oversampling technique (SMOTE), feature selection, and the C4.5 classification algorithm. System testing is done using k-fold cross-validation. The performance parameters are sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV) and the area under the curve (AUC). RESULTS: The results showed that the performance of the system has a sensitivity of 74.7%, a specificity of 93.7%, a PPV of 74.2%, an NPV of 93.7%, and an AUC of 84.2%. CONCLUSIONS: This study demonstrated that, by using C4.5 algorithms, data can be interpreted in the form of a decision tree, to aid the understanding of the clinician. In addition, the proposed system can provide better performance by category.
Area Under Curve ; Classification ; Coronary Disease* ; Data Mining ; Decision Trees ; Diagnosis* ; Heart Diseases ; Incidence ; Sensitivity and Specificity

OBJECTIVES: The objective of this investigation was to demonstrate the possibility of the construction of a real-time prescription drug monitoring system (PDMOS) using data from the nationwide Drug Utilization Review (DUR) system in Korea. METHODS: The DUR system collects information on drug prescriptions issued by healthcare practitioners and on drugs dispensed by pharmacies. PDMOS was constructed using this data. The screen of PDMOS is designed to exhibit the number of drug prescriptions, the number of prescriptions dispensed by pharmacies, and the dispensed prescription drug costs on a daily and weekly basis. Data was sourced from the DUR system between June 1, 2016 and July 18, 2016. The TOGA solution developed by the EYEQMC Co. Ltd. of Seoul, Korea was used to produce the screen shots. RESULTS: Prescription numbers by medical facilities were more numerous than the number of prescriptions dispensed by pharmacies, as expected. The number of prescriptions per day was between 2 to 3 million. The prescriptions issued by primary care clinics were most numerous, at 75% of the total number of prescriptions. Daily prescription drug costs were found to be approximately US $50 million. The prescription drug costs were highest on Mondays and were reduced towards the end of the week. Prescriptions and dispensed prescriptions numbered approximately 1,200 and 1,000 million, respectively. CONCLUSIONS: The construction of a real-time PDMOS has been successful to provide daily and weekly information. There was a lag time of only one day at the national level in terms of information extraction, and scarcely any time was required to load the data. Therefore, this study highlights the potential of constructing a PDMOS to monitor the estimate the number of prescriptions and the resulting expenditures from prescriptions.
Delivery of Health Care ; Drug Costs ; Drug Monitoring* ; Drug Prescriptions ; Drug Utilization ; Drug Utilization Review ; Health Expenditures ; Information Storage and Retrieval ; Korea ; Pharmacies ; Prescription Drugs ; Prescriptions* ; Primary Health Care ; Seoul

OBJECTIVES: To develop a tool which can easily access the hospital information system (HIS) to facilitate outpatient care and maximize patient satisfaction on his or her hospital visit. METHODS: Our Center for Informatics developed an outpatient guidance system (OGS) after careful analysis of the list of daily tasks undergone by patients and related work processes. Bluetooth beacons were installed to assist patients, to inform them of points of interest, and to guide them along the proper routes to and within the hospital. RESULTS: The OGS conveniently provided patients' clinic schedules, routes to the hospital, and direct costs; all of this information was embedded in the HIS accessed from patients' personal mobile devices or kiosks. Patients were also able to identify their locations within the hospital, receiving proper directions to subsequent task. Since its launch in October 2014, the number of mobile accesses increased from 4,011 to 8,242 per month within a year. CONCLUSIONS: The substantial growth of interest in and use of our OGS in such a short period indicate that this system has been successfully incorporated into patients' daily activities. We believe that this system will continue to help improve health services and the well-being of those visiting the hospital.
Ambulatory Care ; Appointments and Schedules ; Health Services ; Hospital Information Systems ; Humans ; Informatics ; Outpatients* ; Patient Care ; Patient Satisfaction ; Smartphone