Characteristics of COVID-19-Related Free Telephone Consultations by Public Health Nurses in Japan: A Retrospective Study

Experience and Resilience of Japanese Public Health Nurses during the COVID-19 Pandemic and Their Impact on Burnout

Japanese public health nurses (PHNs) at public health centers (PHCs) have played critical roles in infection prevention and control during the COVID-19 pandemic. This study aimed to examine the actual pandemic-related experiences of PHNs and the relation between their experiences, individual resilience, two components of organizational resilience (system and human resilience), and burnout. An analysis of the responses of 351 PHNs revealed that mid-level PHNs scored higher in experience and lower in organizational resilience compared with those in other positions. More than 80% of respondents experienced inappropriate staff allocation. Multiple regression revealed that burnout was positively associated with the components of the experience of PHNs and negatively with individual and human resilience. In hierarchical multiple regression with depersonalization as the dependent variable, the sign of system resilience reversed from negative to positive when human resilience was added. The results highlight the need to prepare for future health crises including establishing a system with enough personnel, promoting human resilience such as collaboration among staff members, and burnout prevention measures, especially among mid-level PHNs. The study also described alternative approaches to comprehend system resilience-namely, a suppression variable of human resilience, promotion of depersonalization, and multicollinearity-and the need for further research on organizational resilience.

A Robust Design-Based Expert System for Feature Selection and COVID-19 Pandemic Prediction in Japan

Expert systems are frequently used to make predictions in various areas. However, the practical robustness of expert systems is not as good as expected, mainly due to the fact that finding an ideal system configuration from a specific dataset is a challenging task. Therefore, how to optimize an expert system has become an important issue of research. In this paper, a new method called the robust design-based expert system is proposed to bridge this gap. The technical process of this system consists of data initialization, configuration generation, a genetic algorithm (GA) framework for feature selection, and a robust mechanism that helps the system find a configuration with the highest robustness. The system will finally obtain a set of features, which can be used to predict a pandemic based on given data. The robust mechanism can increase the efficiency of the system. The configuration for training is optimized by means of a genetic algorithm (GA) and the Taguchi method. The effectiveness of the proposed system in predicting epidemic trends is examined using a real COVID-19 dataset from Japan. For this dataset, the average prediction accuracy was 60%. Additionally, 10 representative features were also selected, resulting in a selection rate of 67% with a reduction rate of 33%. The critical features for predicting the epidemic trend of COVID-19 were also obtained, including new confirmed cases, ICU patients, people vaccinated, population, population density, hospital beds per thousand, middle age, aged 70 or older, and GDP per capital. The main contribution of this paper is two-fold: Firstly, this paper has bridged the gap between the pandemic research and expert systems with robust predictive performance. Secondly, this paper proposes a feature selection method for extracting representative variables and predicting the epidemic trend of a pandemic disease. The prediction results indicate that the system is valuable to healthcare authorities and can help governments get hold of the epidemic trend and strategize their use of healthcare resources.

Impact of a nurse-led teleconsultation strategy for cardiovascular disease management during COVID-19 pandemic in India: a pyramid model feasibility study

OBJECTIVE

The COVID-19 pandemic necessitated the use of telemedicine to maintain continuity of care for patients with cardiovascular diseases (CVDs). This study aimed to demonstrate the feasibility of implementing a nurse-led teleconsultation strategy for CVD management during the COVID-19 pandemic in India and evaluated the impact of nurse-led teleconsultations on patient treatment satisfaction.

DESIGN, SETTING AND PARTICIPANTS

We developed a two-stage teleconsultation strategy and tested the feasibility of implementing a nurse-led teleconsultation strategy to manage CVD in a northern state (Punjab) in India. A multidisciplinary team of experts developed the treatment protocol used for teleconsultations to manage CVD. Nurses were trained to provide teleconsultation, triaging of patients and referrals to the physicians. Patients with CVD who had an outpatient visit or hospitalisation between September 2019 and March 2020 at the Dayanand Medical College Hospital, Ludhiana, India, were contacted by phone and offered teleconsultations. Telemedicine strategy comprised: stage 1 nurse-led teleconsultations and stage 2 physician-led teleconsultations. Descriptive analysis was performed to report the proportion of patients triaged by the two-stage telemedicine strategy, and patient's clinical characteristics, and treatment satisfaction between the nurse-led versus physician-led teleconsultations.

RESULTS

Overall, nurse-led stage 1 teleconsultations were provided to 12 042 patients with CVD. The mean (SD) age of the participants was 58.9 years (12.8), and men were 65.4%. A relatively small proportion of patients (6.3%) were referred for the stage-2 physician-led teleconsultations and of these only 8.4% required hospitalisations. During stage 1 nurse-led teleconsultations, patients were referred to the physicians due to uncontrolled diabetes (24.9%), uncontrolled hypertension (18.7%) and congestive heart failure (16.2%). The patient's treatment satisfaction was similar between the nurse-led versus physician-led teleconsultations (p=0.07).

CONCLUSION

This study showed that a nurse-led telemedicine strategy is feasible to implement in a resource-constraint setting for triaging patients with CVD and reduces physician's burden.

Content Analysis of the Free COVID-19 Telephone Consultations Available during the First Wave of the Pandemic in Japan

This cross-sectional study aimed to (1) describe the unclassified contents of telephone consultation services provided by a public health center during the first wave of COVID-19 in Japan and (2) examine whether the contents required assistance from public health nurses (PHNs). We analyzed a total of 207 calls in which the purpose of the call was unclassified into pre-set categories. PHNs transcribed the exact text of the consultation conversations recorded from 25 March to 20 April 2020 in City A. Approximately half of the calls were from residents. Seven categories were extracted through a qualitative content analysis. The most common topic was infection control measures, where the presence of COVID-19 infection was assumed (n = 62); the second most common was extreme anxiety and fear of infection (n = 50). Questions about the COVID-19 response system (n = 30), discrimination and misunderstandings about COVID-19 (n = 24), and response measures for COVID-19 outbreaks within organizations (n = 18) were also included. The unclassified consultations included various topics, several of which required the expertise of a PHN. Each local government should consider sharing and task-shifting telephone consultation services among PHNs and other staff to reduce their burden and allow them to concentrate on conducting infection control more effectively.