Prioritizing Patient Assessment Data (PAD) Using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©

The study identified priorities of the Patient Assessment Data (PAD) using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©) derived from 644 psychiatric nurses’ responses who were practicing in specific units: Acute Care Units (ACU), General Care Units (GCU), Long-term Care Units (LCU), physically Complicated Disease Care Units (CDCU), and Dementia Care Units (DCU). Secondary analysis of the PsyNACS©on-line survey data using four levels of “importance” was used to determine the priorities: 1) unnecessary;2) quite important;3) important and 4) very important. The Mean Factor Points (MFP) and the Welch’s ANOVA were calculated. PsyNACS©score of 3 or higher indicates the PAD as priority. The results showed that in the ACU PAD1, “Psychological symptom”, “Stress coping”, and “Mood disorder and aggression”, and PAD2 “Information of adherence”, and “Information of the psychiatry rehabilitation”, and PAD7 “Situation of the family and social life”, “Relationship to the health care providers”, and “Relationships with others” are high priority (high importance). Other PADs showed results below PsyNACS©score of 3. The GCU had PAD 3 “Balance of water”, the LCU had PAD 4 “Intention/Point of view”, and “Thoughts of the patient” and PAD 7 “Disease and family”. The CDCU showed PAD 2 “Blood test”, PAD 3 “Excretion situation”, and PAD 5 “General health condition”, “Respiratory and chest symptom”, and “Vital signs”, and the DCU had PAD 1 “Cognition function”, and “Delirium and derangement capacity to register failure”, PAD 3 “Function of eating”, PAD 6 “Egestion and cleanliness” and PAD 8 “Activity and sleeping”, and “Mobility capability”. These classifications indicated levels of importance in the CAD comprising the PAD below the score of “2”. Japanese psychiatric hospitals specify assessments according to functional areas. By prioritizing the CAD for each PAD, more effective and efficient assessments can be performed according to practice unit.

The Development of the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©)

The purpose of this study was to develop the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©. This study used the on-line survey method from February to April 2015. There were 644 respondents comprised of professional nurses with minimum qualification of 3 years’ experience being in a psychiatric unit of a stand-alone 200-bed or more Psychiatric Hospital in Japan. Assessment items were derived from 211 specific items selected from nursing textbooks, excluding the North-American-Nursing-Diagnosis-Association (NANDA). The questionnaire contained Cover Letter, Demographic Data Sheet, and the PsyNACS© questionnaire. There were 644 questionnaires accessed but only 435 were completed and valid. Item levels of importance were evaluated: 1) Unnecessary, 2) Not very important, 3) Important and 4) Very important. Data analysis used descriptive and multivariate statistics. Factor analysis (principal factor analysis, varimax rotation), the Kaiser-Meyer-Olkin (KMO) and the Bartlett’s test of Sphericity assessed the adaptive validity of the factor analysis. Factor loadings were set at 0.4 or more for the configuration of items. Internal consistency and reliability were established using Cronbach’s alpha coefficient. Mean factor points were calculated, including standard deviation, range, and confidence interval at 95%. Statistical significance was at 0.05 level. Nine Patient Assessment Data (PAD) with 2 to 5 Cluster Assessment Data (CAD) each were categorized. Thirty one CADs comprised the Patient Assessment Data: (PAD1) Psychological symptom and stress, (PAD2) Information about treatment, (PAD3) Function of eating and balance of water, (PAD4) Life and value, (PAD5) Vital signs and health assessment, (PAD6) Self-care, (PAD7) Social support, (PAD8) Activity, sleeping and mobility capability, and (PAD9) Sexual function and sexual behavior. The PsyNACS© is a classification of items assessing health care needs within the Japanese psychiatric nursing care environment, and also can be used in various psychiatric patient care situations in all psychiatric units.

The Optimization of Humanoid Robot’s Dialog in Improving Communication between Humanoid Robot and Older Adults

Older adults with dementia are increasing in Japan. Because of this, “communication robots” are being introduced into nursing settings to substitute for the shortage of nurses and other care workers. Our research group is currently developing a humanoid nursing robot with caring function (HNR), specifically for the functional and practical use of older adults with dementia. The purpose of this study was to clarify improvement points of the current function of humanoid robot’s (Pepper) (SoftBank Robotics) dialog pattern for improving optimal communication between humanoid robot and older adults. Dialog programs were installed in the humanoid robot Pepper, including the application program Care Prevention Gymnastics Exercises for Pepper (Pepper-CPGE) that was made by Xing Company, Japan. Dialogues between older adults and Pepper-CPGE were recorded by video camera. Data from transcriptions of the conversations captured from video and from field notes were analyzed focusing on human-robot interaction. From the recorded scenes and conversations, the following were points to be improved: 1) Intonation of the words vocalized by Pepper-CPGE was different from that expected by the older adult resulted in inappropriate responses by the older adult;2) The timing between Pepper’s questions and the responses of the older adult were not timely and did not match (differences in the question-response time), which lead to confusion among the older adults;and 3) Other surroundings older adults were interested in the dialogue with Pepper-CPGE. However, Pepper-CPGE cannot communicate with multiple older adults. ImprovingPepper-CPGE’s ability to communicate with multiple older adults as an older adult’s dialogue with Pepper-CPGE can cause other older adults to also interact not only with the older adult that Pepper-CPGE is interacting with but also with Pepper-CPGE. This study shows that transactive relations among humanoid robots and older adults can be facilitated. Improving communication between humanoid robots and the older adults by optimizing a structured dialogue is needed to enhance appropriate engagement and participation. It is necessary to create a “Caring dialogue Database” for HNRs in order to know the patient/client and to share the aesthetic experiences of human-robot interactions. Also, it is important to develop a dialog pattern that enables humanoid robots to sympathize with older adults.

Development of Algorithm and System for Automatic Generation of Nursing Summaries from Nursing Care Plans

A nursing care planning system that automatically generated nursing summaries from information entered into the Psychiatric Outcome Management System (PSYCHOMS?, Tanioka et al.), was developed to enrich the content of nursing summaries at psychiatric hospitals, thereby reducing the workload of nurses. Preparing nursing summaries entails finding the required information in nursing records that span a long period of time and then concisely summarizing this information. This time consuming process depends on the clinical experience and writing ability of the nurse. The system described here automatically generates the text data needed for nursing summaries using an algorithm that synthesizes patient information recorded in electronic charts, the Nursing Care Plan information or the data entered for North American Nursing Diagnosis Association (NANDA) 13 domains with predetermined fixed phrases. Advantages of this system are that it enables nursing summaries to be generated automatically in real time, simplifies the process, and permits the standardization of useful nursing summaries that reflect the course of the nursing care provided and its evaluation. Use of this system to automatically generate nursing summaries will allow more nursing time to be devoted to patient care. The system is also useful because it enables nursing summaries that contain the required information to be generated regardless of who prepares them.

Consideration of Safety Management When Using Pepper, a Humanoid Robot for Care of Older Adults

Pepper, a humanoid robot, is 1.2 m in height and is designed to move its limbs. There are risks of the older adults experiencing falling and collision accidents when they interact with Pepper. When physical interaction happens between a humanoid robot and human beings, potential harmful physical contact might occur. The aim of this report was to examine the safety management aspects when using Pepper, a humanoid robot for the care of older adults. The older adults’ reactions to Pepper’s functions cannot be predicted. Hence, it is necessary to clarify methods to guarantee its safety in advance and to increase the safety and properties of the robots. The benefits of introducing support robots such as Pepper for aging medical and nursing care settings are obvious. Therefore, engagement in robot development while considering both the risks and benefits is critical. Our academic initiatives have just begun. Through information exchange among researchers, users, engineers, and law specialists, we need to identify latent and prominent risks in situations where Pepper and the older adults interact and deepen our examination of measures against such risks.

Methodology for Developing a Nursing Administration Analysis System

Nursing administration requires a large volume of wide-ranging information, and nurse administrators are limited in their ability to compile and analyze information for nursing administration. The purpose of this study is to create methodology for developing a nursing administration analysis system to aid nurse administrators in performing outcome analysis. In this methodology, information required for nursing administration in the PSYCHOMS? (Psychiatric Outcome Management System, registered trademark) database is analyzed according to the individual needs of nurse administrators. It features a combination of a classification method and an extraction method for obtaining quantitative and qualitative data as information required for nursing administration, and enables nurse administrators to easily obtain analysis results that they directly need. This methodology converts the time required nurse administrators to collect and organize information into time for making considerations in order to devise strategies for improving the quality of nursing care services, and can improve the quality and efficiency of nursing administration. This may lead to an increase of the quality of nursing care services at psychiatric hospitals. This methodology is highly versatile as it can be applied in information management, not only for nursing, but for the entire psychiatric hospital.

Reliability Verification and Practical Effectiveness Evaluation of the Nursing Administration Analysis Formulae Based on PSYCHOMS^(■)

In psychiatric hospitals, the ratios between patients versus physician and patients versus nurse are low as compared to those in general hospitals. Furthermore, usages of electronic medical records are also low so that nurse administrators are limited in their ability to compile, analyze, and generate patient care staffing information for their administrative use. Psychiatric nurse administrators anticipate the development of a nursing administration analysis system that could perform personnel data simulation, manage information on nursing staff, and manage ward/ practice operations. Responding to this situation, the authors developed a nursing administration analysis system utilizing formulae from the Psychiatric Outcome Management System, PSYCHOMS®to aid nurse administrators. Such formulae are awaiting patent approval. The purpose of this study was to examine the validity of the formulae and the Structured Query Language (SQL) statement, and its practical effectiveness of analyzing data. The study findings showed that two kinds of computation expressions—a classification and extraction were able to display required information desired by nurse administrators. Moreover, significant information critical to assigning staff was validated to ensure high quality of nursing care according to the function and characteristic of the hospital ward.