• Journal of Korean Clinical Nursing Research
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• v.16 no.2
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• pp.127-140
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• 2010

Purpose: This study was performed to verify reliability and validity of Korean Patient Classification System for nurses(KPCS-1), to estimate nursing time conversion index, and to classify patients into groups according to KPCS-1 scores. Methods: KPCS-1 was revised from KPCS by a professional review team. Interrater reliability and construct validity of KPCS-1 were verified by data from 433 patients. Direct and indirect nursing time of 204 patients were measured by stopwatch observation and self reports for 24 hours. Nursing time conversion index was calculated. Results: KPCS-1 consisted of 12 area, 50 nursing activities, and 73 items. The interrater reliability was tested between two nurse group (r=.88, p<.001) and construct validity was verified according to medical department (F=10.97, p<.001) and patient pattern (F=5.54, p=.001). The correlation of nursing time and classification score was also statistically significant (r=.56, p<.001). The nursing time conversion index was 9.03 minutes per 1 classification score. The patients were classified into 4 groups by the classification scores. Conclusion: KPCS-1 can be a useful factor type patient classification system for general ward. Further study is needed to evaluate validity and reliability for refining KPCS-1 and to develop ways connecting the scores with nursing outcomes.

• Korea Journal of Hospital Management
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• v.25 no.3
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• pp.14-28
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• 2020

Purpose: The purpose of this study was to calculate the total daily nursing workload and the optimum number of nurses per intensive care unit (ICU) based on the nursing intensity and the direct nursing time per inpatient using the patient classification. Methods: Two ICUs at one general hospital were investigated. To calculate the nursing intensity, patient classification according to the nursing needs was conducted for 10 days in each unit during September 2018. We performed patient classifications for a total of 167 patient-days in the Medical Intensive Care Unit (MICU) and 86 patient-days in the Surgical Intensive Care Unit (SICU). The total number of person-days for nurses who responded to the Nursing Time survey was 151 for MICU and 85 for SICU. In each unit, direct and non-direct nursing hours, nursing intensity score, and direct nursing hours were analyzed using descriptive statistics such as frequency, percentage, and average calculated using Microsoft Excel. The amount of nursing workload and the optimum number of nurses were calculated according to the formula developed by the authors. Findings: For the MICU, the average direct nursing time per patient was 5.59 hours for Group 1, 6.98 hours for Group 2, and 9.28 hours for Group 3. For the SICU, the average direct nursing time per patient was 5.43 hours for Group 1, 7.21 hours for Group 2, 9.75 hours for Group 3, and 12.82 hours for Group 4. Practical Implications: This study confirmed that the appropriate number of nurses was not secured in the nursing unit of this study, and that leisure time such as meal time during nursing work hours was not properly guaranteed. The findings suggest that to create working environments where nurses can serve for extended periods of time without compromising their professional standards, hospitals should secure an appropriate number of nurses.

• Journal of Korean Clinical Nursing Research
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• v.18 no.3
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• pp.354-367
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• 2012

Purpose: This study was done to verify validity and reliability of a neonatal patient classification system (NeoPCS-1). Methods: An expert group of 8 nurse managers and 40 nurses from 8 Neonatal Intensive Care Units in Korea, verified content validity of the measurement using item level content validity index (I-CVI). The participants were nurses caring for 469 neonates. Data were collected from November 11 to December 14, 2011 and analyzed using descriptive statistics, ANOVA, intraclass correlation coefficient, and K-cluster analysis with PASW 18.0 program. Results: Nursing domains and activities included 8 items with 91 activities. I-CVI was above .80 in all areas. Interrater reliability was significant between two raters (r=.95, p<.001). Classification scores for participants according to patient types and nurses' intuition were significantly higher for the following patients; gestational age (${\leq}29$ weeks), body weight (<1,000 gm), and transfer from hospital. Six groups were classified using cluster analysis method based on nursing needs. Patient classification scores were significantly different for the groups. Conclusion: These results show adequate validity and reliability for the NeoPCS-1 based on nursing needs. Study is needed to refine the measurement and develop index scores to estimate number of nurses needed for adequate neonatal care.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.3
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• pp.475-488
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• 2002

Purpose : The purpose of this study is to establish a basis of patient classification in the ICU by selecting the determination critical indicator of special nursing activities that show high interrilation with daily total nursing care time. Method : This study is composed of the six steps. The first step is the listing direct nursing activities in the ICU. The last step is the determination indicator of each group were selected on the basis of their relationship to the daily total nursing care time of each patient classification group and each nursing activity. Result : Result shows that: 1. direct nursing activities in the ICU are 149 items of 13 territories. 2. the average time and frequency for each direct nursing activities 3. total direct nursing care time of 42 patients in ICU for 2 days. According to the results of the Cluster analysis, the first group is 10 people, the second group is 13 people, the third group is 16 people, the fourth group is 3 people. 4. Determination critical indicator is the item that is r>0.6(p<0.05) of Pearson Correlation between each patient daily total nursing care time and 149 items of nursing activities. The nursing activities selected were as follows: 2 items in the first group, 17 items in the second group. 16 items in the third group, 8 items in the fourth group. Conclusion : This study can help future studies which measure nursing activities standard time or assigns value to nursing activities time.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.9-17
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• 2021

In this study, we propose a part of the CDSS(Clinical Decision Support System) study, a system that can classify chemotherapy, one of the treatment methods for colorectal cancer patients. In the treatment of colorectal cancer, the selection of chemotherapy according to the patient's condition is very important because it is directly related to the patient's survival period. Therefore, in this study, chemotherapy was classified using a machine learning algorithm by creating a baseline model, a pathological model, and a combined model using both characteristics of the patient using the individual and pathological characteristics of colorectal cancer patients. As a result of comparing the prediction accuracy with Top-n Accuracy, ROC curve, and AUC, it was found that the combined model showed the best prediction accuracy, and that the LGBM algorithm had the best performance. In this study, a chemotherapy classification model suitable for the patient's condition was constructed by classifying the model by patient characteristics using a machine learning algorithm. Based on the results of this study in future studies, it will be helpful for CDSS research by creating a better performing chemotherapy classification model.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.5-16
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• 2007

Purpose: This study is to verify the validity and reliability of classified items and criteria of the patient classification system(PCS) based on Park's definition of nursing intensity. Methods: An expert group of 8 persons verified the content validity of the tools. The 1817 inpatients at a tertiary hospital in Seoul, Korea were classified into 4 groups according to two tools for verifying concurrent validity and interraters' reliability. These verifications were performed from September to October, 2004. Results: Nursing domains of the tools have been divided into 12 items: hygiene, nutrition, elimination, exercise & activity, education & counseling, emotional support, communication & consciousness, treatment & examination, medication, measurement & observation, coordination of multidisciplinary team, admission & discharge & transfer management. Content validity was verified by the content validity index(above 0.75 in all 12 areas). Interraters' reliability was no significant difference in the results of the patient classification between the two raters(A group 93.75%. B group 88.24%). Concurrent validity was also verified by the agreement of two tools(73.7%). Conclusion: These results showed that the reliability and validity of the PCS based on the nursing intensity were verified. These will use an data for nursing productivity in the future.

• The Journal of the Korean dental association
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• v.53 no.2
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• pp.96-102
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• 2015

There is a need to comprehend dental accidents accurately, and construct patient-safety-system in order to prevent consistently increasing dental accident or dispute. This study is aimed to provide basic data for an efficient counterplain by looking through and classifying already occurred dental accidents from an angle of patient safety. Recently, the number of dispute on dental implant was the highest according to rapid growth of dental implant. As a result of classifying dental accidents by International Classification for Patient Safety (ICPS), it is confirmed that cause of accident is different by each type of dental treatment. It is expected to help preventing and managing dental disputes properly by studying actual state of dental disputes in perspective of patient safety. Effort to reduce dental accidents and activity to pursue patient safety have thread in connection. I believe that financial profits of dental clinic and improvement of quality in dental treatment can be achieved through these efforts.

• Journal of the Korean Society of Physical Medicine
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• v.12 no.4
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• pp.19-28
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• 2017

PURPOSE: The purpose of this study was to describe the Proprioceptive Neuromuscular Facilitation (PNF) Intervention strategy applied International Classification of Functioning, Disability and Health (ICF) Tool about strength, range of motion, scapular stability, pain and function of shoulder for patients with adhesive capsulitis. METHODS: The data was collected by patient with adhesive capsulitis. The patient was a 50-year-old male diagnosed with right shoulder with adhesive capsulitis. We applied the PNF Intervention strategy applied ICF Tool to patient with adhesive capsulitis. PNF interventions were consisting of such as combination of isotonic and stabilizing reversal technique and various positions. PNF interventions were applied, such as those aiming at decreasing pain and disability and increasing range of motion and function for the four weeks. Parameters of result were collected for strength, range of motion, scapular stability, pain and function of shoulder using the hand held dynamometer, goniometer, lateral scapula slide test, and shoulder pain and disability index, respectively. RESULTS: Clinical benefits were observed the patient with adhesive capsulitis for strength, range of motion, scapular stability, pain, and function of shoulder. The patient with adhesive capsulitis improved strength, range of motion, scapular stability, pain, and function of shoulder. CONCLUSION: Patient reported improved strength, range of motion, scapular stability, pain, and function of shoulder after intervention.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.287-298
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• 2013

To develop a technique classifying patients based on computerized clinical data followed by validity verification by comparing with nurse's examination. Class scores were determined by nurses for a day on 348 resident patients in 7 wards of a general hospital according to KPCS-1. The class scores were simultaneously evaluated by reviewing the computerized clinical data acquired from the hospital management information system. These two class scores were both significantly different among different departments as well as disease patterns. Intraclass correlation analysis resulted a very high correlation coefficient of 0.96(p<0.01) between the two scoring methods, but the clinical data scores were somewhat higher. An automated patient classification system seemed possible to be developed in future with further enhancement of the present results based on computerized clinical data without manual scoring, which can be applied for performance evaluation as well as workforce planning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.