This study was conducted to test validity of related factors and characteristics of 98 Nursing Diagnosis identified in a previous study by the Korean Nurses Association. Data for this study was collected from 892 nurses in eight teaching hospitals located in Seoul using a cross sectional survey method. Each participating hospital was asked to produce at least 10 cases for every nursing diagnosis. There were 7,422 responses out of a possible 7,840. Out of the 7,422 responses 26 were discarded due to incompleteness. Data were analyzed using SAS. The result of the study shows that most of the related factors and characteristics for each of the 98 nursing diagnosis were ranked at more than 3.5 point out of 5 point Likert scale in terms of significance. Through this study the related factors and characteristics of the 98 nursing diagnosis identificance. Through this study the related factors and characteristics of the 98 nursing diagnosis identified through literature review were validated by experts in nursing diagnosis. These validated related factors and characteristics will be utilized for computerization of the nursing diagnosis process.

The purpose of this study was to identify the degree to which nursing diagnoses accepted by NANDA are used and to identify problems in application of nursing diagnoses in clinical practice. With the expanding potential fur computerization of nursing diagnosis, the survey also included data on the present status of hospital computerization and willingness to use computerized nursing diagnoses. The data collection was done from July 1 to August 3, 1996 using structured questionnaires. The questionnaires were mailed to 1,126 head nurses working in 44 hospitals with on occupacy of over 500 beds located in Korea, of these, 883 were returned from 40 hospitals. Among the 883 questionnaires, 867 were used for the analysis. The results of the analysis are as follows 1. Among 109 nursing diagnoses, pain, constipation, diarrhea, hyperthermia, high risk for infection, sleep pattern disturbance, and anxiety, chronic pain, altered urinary elimination, and altered nutrition: less than body requirements were the ten most frequently used diagnoses. 2. The primary problem in the use of nursing diagnoses was lack of time and personnel. Others were lack of knowledge and motivation, absence of protocols and absence of the appropriate methods to apply nursing diagnoses. 3. Among the 40 hospitals, 27 hospitals used a computerized system and expressed willingness to utilize the computerized system of nursing diagnoses that is planned for the future.

Neural networks have recently attracted considerable attention in the field of classification and other areas. The purpose of this study was to demonstrate an experiment using back-propagation neural network model applied to nursing diagnosis. The network's structure has three layers; one input layer for representing signs and symptoms and one output layer for nursing diagnosis as well as one hidden layer. The first prototype of a nursing diagnosis systern for patients with stomach cancer was developed with 254 nodes for the input layer and 20 nodes for the output layer of 20 nursing diagnoses, by utilizing learning data set collected from 118 patients with stomach cancer. It showed a hitting ratio of .93 when the model was developed with 20,000 times of learning, 6 nodes of hidden layer, 0.5 of momentum and 0.5 of learning coefficient. The system was primarily designed to be an aid in the clinical reasoning process. It was intended to simplify the use of nursing diagnoses for clinical practitioners. In order to validate the developed model, a set of test data from 20 patients with stomach cancer was applied to the diagnosis system. The data for 17 patients were concurrent with the result produced from the nursing diagnosis system which shows the hitting ratio of 85%. Future research is needed to develop a system with more nursing diagnoses and an evaluation process, and to expand the system to be applicable to other groups of patients.

The purpose of this study was to develop and to evaluate the Computerized Nursing Diagnosis/ Intervention System for Nutritional and Eliminative Problems for clinical application. Each stage was processed based on the System Development Life Cycle. At the Strategy Planning Stage, valid nursing diagnoses and interventions were chosen. At the System Analysis Stage, a nursing diagnosis and intervention flowchart was drawn up. At the System Design Stage, a system was developed based on the flowchart and named the Nursing Diagnosis/Intervention System. The Nursing Diagnosis/Intervention System consisted of the Patient's Basic Information, Patient's Nursing Process, Nursing Process, and Code Registration. Each element in flowchart was coded and made into a database. The System was used and evaluated. A total of 30 cases were collected. After the application, the nurses evaluated the System using a 5 point Likert scale. Every item was scored at three points or more and 13 out of 17 items were scored at four points or more, thus the Nursing Diagnosis/Intervention System that was developed in this study was regarded as a useful one.