• Korean Journal of Adult Nursing
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• v.22 no.6
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• pp.570-581
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• 2010

Purpose: This study was conducted to develop a Cancer Patient Guide with patients involvement using evidenced based practice research. The purpose of this patient guide was to help patients undergoing chemotherapy to manage their nausea and vomiting based on evidence. Methods: The design of the research was a methodological study. The participants consisted of seven cancer patients who were asked about their ' need for nausea and vomiting management, and secondly, 16 expert & 15 cancer patients to evaluate the Cancer Patient Guide using the DESCERN tool. Results: 1) Sixty-four relevant research evidences based articles were reviewed. 2) Patients were interviewed as to their needs in controlling nausea and vomiting. 3) The preliminary Cancer Patient Guide utilizing the research evidenced and the cancer patients interviews was then evaluated and revised by the experts and cancer patients. Lastly, the Cancer Patient which included an overview of chemotherapy, pathophysiology of nausea & vomiting, pharmacological and non-pharmacological interventions was finalized with each intervention supported by research evidence and patients' narratives of their experience. Conclusion: The Cancer Patient Guide was developed using evidenced based research and cancer patients in-put and be used to improve patients' self-management skill of nausea and vomiting in chemotherapy. The guide t also provides evidence based patient friendly information and contributes as a baseline data for developing and evaluating evidence-based guide for patients.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.194-204
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• 2022

This study is a one-group pretest-posttest design to evaluate the effect of problem-based learning (PBL) for patient safety on self-leadership, patient safety competencies, and reflective thinking of nursing students. The research was conducted from March 2 to April 15, 2022, in which 57 nursing students participated. PBL for patient safety was examined in a total of 8 sessions in the order of motivation, problem identification, task performance planning, problem-solving methods, summary and solution, presentation, and evaluation. The following topics of patient safety were selected for each team: nursing records, high-alert medication, medication error and intravenous fluid regulation, blood transfusion care, fall, bedsore, infection control, and pain management. We provided feedback on the learning process and outcomes of nursing students. According to the results, self-leadership showed a statistically significant improvement in self-expectations (t=2.60, p=0.01), goal setting (t=2.84, p<0.01), self-reward (t=3.32, p<0.01), and self-criticism (t=2.32, p=0.02). Patient safety competencies showed a statistically significant improvement in patient safety knowledge (t=13.05, p<0.001) and patient safety skills (t=4.87, p<0.001) but not in reflective thinking. The results prove that PBL for patient safety is an effective teaching-learning strategy to improve self-leadership and patient safety competencies. Future studies must develop and validate specific and long-term teaching-learning methods to improve reflective thinking.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1095-1105
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• 2013

This paper proposes the RDMS(Rough Set Theory based Disease Monitoring System) which efficiently manages diseases in Healthcare System. The RDMS is made up of DCM(Data Collection Module), RDRGM(RST based Disease Rules Generation Module), and HMM(Healthcare Monitoring Module). The DCM collects bio-metric informations from bio sensor of patient and stores it in RDMS DB according to the processing procedure of data. The RDRGM generates disease rules using the core of RST and the support of attributes. The HMM predicts a patient's disease by analyzing not only the risk quotient but also that of complications on the patient's disease by using the collected patient's information by DCM and transfers a visualized patient's information to a patient, a family doctor, etc according to a patient's risk quotient. Also the HMM predicts the patient's disease by comparing and analyzing a patient's medical information, a current patient's health condition, and a patient's family history according to the rules generated by RDRGM and can provide the Patient-Customized Medical Service and the medical information with the prediction result rapidly and reliably.

• International Journal of Costume and Fashion
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• v.14 no.2
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• pp.67-79
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• 2014

Recent research suggested that hospitals have not responded to consumer demand for the improved aesthetic and comfort of their patient garments. Thus a new patient garment has been developed considering human factors based on the Functional-Modesty-Aesthetics model. Based on the reviewed literature and the model, necessary design requirements were identified. Then the patient garment was evaluated in comparison to existing ones with regard to potential patients' satisfaction levels. As a result, the developed patient garment received better evaluations in the aspects of overall aesthetic satisfaction, color satisfaction, and willingness to wear than the existing patient garments.

• Korean Journal of Hospice Care
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• v.6 no.2
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• pp.69-78
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• 2006

Purpose: This study was conducted to analysis relationship about quality of life and family burden of the home-based hospice patient families. Method: The subjects consisted of 94 families with home-based hospice patient. The ages of the subjects were 17-73 years with hospice patient who receivedhome visiting care and registered at 4 hospitals in Daegu and Kyung-Buk. The data was collected from March to November 2004. The instruments used for the study were Quality of Life Scale (GLS) and Family Burden Questionnaire (FBQ). The analysis was done using frequency, mean, standard deviation, correlation and stepwise multiple regression with SPSS WIN 11.0. Results: The results were as follows: 1. The mean score of family burden was 3.36 ($\pm0.55$). The highest mean score of family burden 6 factors were wellness of future 3.85($\pm1.10$), and the second was economic family burden 3.63($\pm0.97$). 2. The mean score of quality of life was 3.09 ($\pm0.48$). The lowest score of quality of life 6 factors were economic status 2.86($\pm0.54$), and the second was physical state and function 3.01($\pm0.62$). 3. In the home-based hospice patient families, family burden had significant negative correlation with quality of life(r=-0.25, p=0.012). 4. Emotional status accounted for 11% of family burden in the home-based hospice patient families by means of stepwise multiple regression. 5. Economical status accounted for 18 and age accounted for an additional 11% of quality of life in the home-based hospice patient families by means of stepwise multiple regression. Conclusion: The finding showed that family burden and quality of life of home-based hospice patient families were significantly negative correlation and the highest factor of family burden was wellness of future and the most important factor of quality of life was economic status.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1049-1065
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• 2023

Recently, with the development of IoT, AI, and mobile terminals, medical information platforms are expanding. The medical information platform can determine a patient's emergency situation, and medical staff can easily access patient information through a mobile terminal. However, in the existing platform, emergency situation decision is delayed, and faster and stronger authentication is required in emergency situations. Therefore, we propose an edge computing-based medical information platform for automatic authentication using patient situations. We design an edge computing-based medical information platform architecture capable of rapid transmission of biometric data of IoT and quick emergency situation decision, and implement the platform data flow in emergency situations. Relying on this platform, we propose the automatic authentication using patient situations. The automatic authentication protects patient information through patient-centered authentication by using the patient's situation as an authentication factor, and enables quick authentication by automatically proceeding with mobile terminal authentication after user authentication in emergencies without user intervention. We compared the proposed platform with existing platforms to show that it can make quick and stable emergency decisions. In addition, comparing the automatic authentication with existing authentication showed that it is fast and protects medical information centered on patient situations in emergency situations.

• Korean Medical Education Review
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• v.21 no.2
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• pp.80-91
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• 2019

The tripartite mission of 'academic medicine' is education, research, and patient care. Academic medical centers (AMCs) are carrying out the mission and ultimately aiming to improve the health of people and communities. Globally, AMCs are facing a tremendous financial risk stemming from the changes in health insurance reimbursement plans and a shortage of human resources. Innovative AMCs in the United States are trying to transform their physician-centered, and siloed structure into a patient-centered, and integrated structure. They are also building integrated systems with primary healthcare groups to provide continuous patient care from primary to tertiary levels and making strategic networks based on value-based payment and the patient-centered model. These changes have been proven to improve outcomes of patient care and increase fiscal revenues, which are both crucial in supporting education and research. To address the shortage of human resources, programs are being built to develop newly appointed faculty for the future. AMCs have different approaches to bringing changes into their organizations; however, there is a common emphasis on 'a patient-centered approach,' which helps them set more explicit organizational values and make strategic decisions based on their values. Korean AMCs are facing similar challenges to AMCs in the United States in spite of many differences between the countries' healthcare systems. The innovative efforts of AMCs in the United States to address the challenges will be helpful, well-worked examples for Korean AMCs with similar challenges.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.167-176
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• 2020

Recommendation Systems is the top requirements for many people and researchers for the need required by them with the proper suggestion with their personal indeed, sorting and suggesting doctor to the patient. Most of the rating prediction in recommendation systems are based on patient's feedback with their information regarding their treatment. Patient's preferences will be based on the historical behaviour of similar patients. The similarity between the patients is generally measured by the patient's feedback with the information about the doctor with the treatment methods with their success rate. This paper presents a new method of predicting Top Ranked Doctor's in recommendation systems. The proposed Recommendation system starts by identifying the similar doctor based on the patients' health requirements and cluster them using K-Means Efficient Clustering. Our proposed K-Means Clustering with Content Based Doctor Recommendation for Cancer (KMC-CBD) helps users to find an optimal solution. The core component of KMC-CBD Recommended system suggests patients with top recommended doctors similar to the other patients who already treated with that doctor and supports the choice of the doctor and the hospital for the patient requirements and their health condition. The recommendation System first computes K-Means Clustering is an unsupervised learning among Doctors according to their profile and list the Doctors according to their Medical profile. Then the Content based doctor recommendation System generates a Top rated list of doctors for the given patient profile by exploiting health data shared by the crowd internet community. Patients can find the most similar patients, so that they can analyze how they are treated for the similar diseases, and they can send and receive suggestions to solve their health issues. In order to the improve Recommendation system efficiency, the patient can express their health information by a natural-language sentence. The Recommendation system analyze and identifies the most relevant medical area for that specific case and uses this information for the recommendation task. Provided by users as well as the recommended system to suggest the right doctors for a specific health problem. Our proposed system is implemented in Python with necessary functions and dataset.

• The Korean Journal of Emergency Medical Services
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• v.22 no.3
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• pp.47-54
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• 2018

Purpose: The purpose of this study was to present evidence for quality management based on analysis of patient transportation and response intervals among emergency medical squads. Methods: The chi-square test was used to determine whether mental status and patient assessment affected direct medical control and hospital destination. One way analysis of variance was used to compare response intervals depending on mental status and patient assessment using data drawn from 1172 prehospital care reports. Results: There was a statistically significant relationship between mental status and direct medical control (p<.001); there was a statistically significant relationship between patient assessment and hospital destination (p=.011). However, there was no statistically significant relationship between mental status and hospital destination. The interval from arrival at the patient's side to departure from the scene showed a statistically significant difference (p<.001, p<.001), however, it took the longest time (16.8 minutes) in unresponsive patients. It showed a statistically significant difference (p<.001) in the interval from arrival at patient's side to departure from the scene depending on patient assessment; however, it took the longest time (9.6 minutes) in emergency patients. Conclusion: There was call for direct medical control based on patient assessment; however, patient transportation and response intervals were not appropriate.

• The Journal of Korean Medicine
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• v.42 no.2
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• pp.98-106
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• 2021

Objectives: The objective of this case report is to find a therapeutic effect of Gyeji-tang in panic disorder patients, based on Shanghanlun provision. Methods: At patient's first visit, we had conducted a medical interview in order to diagnose the physical and mental symptoms of the patient. A questionnaire called BAI had been also used to measure the degree of anxiety in panic disorder. After all the diagnoses had been done, the patient was allowed to take 120cc of Gyeji-tang, three times a day for 25 weeks. 25 weeks later, we conducted a second medical interview to compare with the initial treatment and to evaluate whether his physical and mental symptoms had been decreased or not. Likewise, the patient was asked to fill out the BAI questionnaire to measure the decline of anxiety degree. Results: Based on Shanghanlun provision, the patient with panic disorder due to overwork was diagnosed as Tai-yang-bing. Considering that the patient was having dyspnea, 15th provision of Gyeji-tang was selected and administered for 25 weeks. After 25 weeks, we could have observed that the main physical symptoms such as palpitation, dyspnea, stifling, headache, and fatigue were moderately improved. Moreover, the BAI score, which was evaluated to measaure the degree of anxiety, was also decreased from 49 points to the level of normal condition, 16 points. Conclusions: A 44 year old male patient who suffered from panic disorder due to overwork was allowed to take 15th provision Gyeji-tang for 25 weeks, based on Shanghanlun Provision. In results, the main physical symtpoms including dyspnea, palpitation, stifling, headache, and fatigue, and mental symptom such as extreme anxiety were all effectively improved.