http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Factors Affecting Nurses’ Performance of Cancer Pain Management in a Tertiary Hospital
Minhwa Kang,서민정 한국호스피스완화의료학회 2022 한국호스피스.완화의료학회지 Vol.25 No.3
Purpose: More than 60% of patients with advanced cancer experience pain, and uncontrolled pain reduces the quality of life. Nurses are the closest healthcare providers to the patient and are suitable for managing cancer pain using pharmacological and non-pharmacological interventions. This study aimed to identify factors affecting the performance of cancer pain management among nurses. Methods: This study was conducted among 155 participating nurses working at a tertiary hospital who had experience with cancer pain management. Data collection was performed between October 18, 2021 and October 25, 2021. Data analysis was conducted using descriptive statistics, the independent-sample ttest, one-way analysis of variance, and hierarchical regression analysis. Results: There were 110 subjects (71.0%) who had no experience of cancer pain management education. The results of regression analysis indicated that barriers included medical staff, patients, and the hospital system for cancer pain management (β=0.28, P<0.001). The performance of cancer pain management was also affected by experience of cancer pain management training (β=0.22, P=0.007), and cancer pain management knowledge (β=0.21, P=0.006). The explanatory power of the variable was 16.6%. Conclusion: It is crucial to assess system-related obstacles, as well as patients and medical staff, in order to improve nurses’ cancer pain management performance. A systematic approach incorporating multidisciplinary interventions from interprofessional teams is required for effective pain management. Furthermore, pain management education is required both for cancer ward nurses and nurses in other wards.
Kim Si-Ho,Wi Yu Mi,문치숙,Kang Ji-Man,Kim Minhwa,Kim Jungok,김종만,Seok Hyeri,Shi Hye Jin,Lee Su Jin,Lee Ji Yeon,Jeong Su Jin,Choe Pyoeng Gyun,Huh Kyungmin,Lee Sang-Oh,Kim Sang Il 대한이식학회 2023 Korean Journal of Transplantation Vol.37 No.3
We present a summary of the evidence on testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and organ procurement from deceased donors and provide recommendations based on current clinical data and the guidelines from major transplant organizations. Because of the limited historical experience with coronavirus disease 2019 (COVID-19), certain recommendations in this document are based on theoretical rationales rather than clinical data. The recommendations in this manuscript may be subject to revision as subsequent clinical studies provide definitive evidence regarding COVID-19 in organ procurement.
이규환(Lee, Kyuwhan),정지오(Chung, Jio),신대진(Shin, Daejin),정민화(Chung, Minhwa),강경희(Kang, Kyunghee),장윤희(Jang, Yunhee),장경호(Jang, Kyungho) 한국음성학회 2016 말소리와 음성과학 Vol.8 No.2
In emergency dispatching at 119 Command & Dispatch Center, some inconsistencies between the ‘standard emergency aid system’ and ‘dispatch protocol,’ which are both mandatory to follow, cause inefficiency in the dispatcher’s performance. If an emergency dispatch system uses automatic speech recognition (ASR) to process the dispatcher’s protocol speech during the case registration, it instantly extracts and provides the required information specified in the "standard emergency aid system,’ making the rescue command more efficient. For this purpose, we have developed a Korean large vocabulary continuous speech recognition system for 400,000 words to be used for the emergency dispatch system. The 400,000 words include vocabulary from news, SNS, blogs and emergency rescue domains. Acoustic model is constructed by using 1,300 hours of telephone call (8 kHz) speech, whereas language model is constructed by using 13 GB text corpus. From the transcribed corpus of 6,600 real telephone calls, call logs with emergency rescue command class and identified major symptom are extracted in connection with the rescue activity log and National Emergency Department Information System (NEDIS). ASR is applied to emergency dispatcher’s repetition utterances about the patient information. Based on the Levenshtein distance between the ASR result and the template information, the emergency patient information is extracted. Experimental results show that 9.15% Word Error Rate of the speech recognition performance and 95.8% of emergency response detection performance are obtained for the emergency dispatch system.