Abstract
Introduction</br> <p>In order to avoid unnecessary hospital admission and associated complications, there is an urgent need to improve the early detection of infection in nursing home residents. Monitoring signs and symptoms with checklists or aids called decision support tools may help nursing home staff to detect infection in residents, particularly during the current COVID-19 pandemic. We plan to conduct a survey exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes in England and Sweden.</p>
Methods and analysis</br> <p>An international cross-sectional descriptive survey, using a pretested questionnaire, will be used to explore nurses, care workers and managers views and experiences of how infections are detected and managed in practice in nursing homes. Data will be analysed descriptively and univariate associations between personal and organisational factors explored. This will help identify important factors related to awareness, knowledge, attitudes, belief and skills likely to affect future implementation of a decision support tool for the early detection of infection in nursing home residents.</p>
Ethics and dissemination</br> <p>This study was approved using the self-certification process at the University of Surrey and Linköping University ethics committee (Approval 2018/514-32) in 2018. Study findings will be disseminated through community/stakeholder/service user engagement events in each country, publication in academic peer-reviewed journals and conference presentations. A LAY summary will be provided to participants who indicate they would like to receive this information. This is the first stage of a plan of work to revise and evaluate the Early Detection of Infection Scale (EDIS) tool and its effect on managing infections and reducing unplanned hospital admissions in nursing home residents. Implementation of the EDIS tool may have important implications for the healthcare economy; this will be explored in cost–benefit analyses as the work progresses.</p>