Cognitive and Initial Psychometric Testing of the Errors of Care Omission Survey: A New Patient Safety Tool for Primary Care

Protocol for evaluating quality and safety for the public through home care nursing in Italy: a multicentre cross-sectional descriptive observational study (AIDOMUS-IT)

INTRODUCTION

Considering the increasing complexity of care and workload for home care nurses due to the ageing of the population, it is crucial to describe the work environment and the community care setting. The aim of this study protocol is to map the characteristics and identify gaps of home care in the community to design future interventions aimed at ensuring quality and safety.

METHODS AND ANALYSIS

This is a national cross-sectional descriptive observational study using the survey method. Nurses from all participating community care centres will be recruited through convenience sampling by the coordinators of each centre, who will act as facilitators for this study. All community care recipients and their informal carers during the study period will be invited to complete a survey.To map the characteristics and identify gaps of home care in the community, three sources of data will be collected: (1) organisational characteristics, professional satisfaction, intention to leave and burn-out; (2) experience of care recipients and their informal carers and (3) improper access to the emergency department, readmission to hospital, comorbidities, services offered and users' level of autonomy, and main and secondary diagnoses.Considering the total Italian nursing population of approximately 450 000 registered nurses, a sample size of 1% of this population, equal to approximately 4600 nurses, was hypothesised.This study started in July 2022 and is planned to end in December 2023.Data will be analysed using descriptive and inferential statistics.

ETHICS AND DISSEMINATION

This study protocol was approved by the Liguria Regional Ethics Committee in November 2022. Informed consent will be obtained from participants and confidentiality will be ensured. Data collected for this study will be kept anonymised in a protected database.The results of the study will be disseminated mainly through conferences, publications and meetings with government representatives.

How robots impact nurses' time pressure and turnover intention: A two-wave study

AIMS

To examine the relationships among effort ensuring robots' smooth operation (EERSO), time pressure, missed care, and nurses' turnover intention, and how robot performance moderates such relations.

BACKGROUND

Robots may reduce nurses' workload but typically still require some effort of nurses for robots' smooth operation. However, the negative impact of EERSO on nurses' workplace outcomes is unknown.

METHODS

This study used a two-wave follow-up design. Data were collected in a medical center in Taiwan, with first wave collected in 2019 and second wave collected between 2019 and 2020. A total of 331 participants were followed through the two waves.

RESULTS

EERSO is positively linked to missed care and time pressure. Time pressure is also positively linked to missed care and turnover intention. Positive robot performance weakens the positive link between EERSO and time pressure.

CONCLUSION

Using robots may help reduce nurses' workload, but it also requires nurses' efforts to maintain robots' continuous operation, that is, EERSO. It may adversely impact nursing professional workplaces.

IMPLICATIONS FOR NURSING MANAGEMENT

Nurse managers should reduce nurses' time pressure whilst suggest hospital managers to seek robots that require minimal EERSO.