This implementation science project aims to implement a nurse-led model of care in 11 nursing homes in the German speaking part of Switzerland, to reduce avoidable hospitalisations. The model will be introduced using a non-randomized stepped-wedge design. First, training will be delivered to leadership teams and to geriatric nurse experts, secondly after a baseline measurement period, including distribution of questionnaires and collection of resident data mainly national quality indicators and data regarding hospitalisations, the nurse led model will be implemented and thereafter 2 measurement periods will follow (6 months after the beginning of the intervention and at the end). Quantitative resident data will be retrieved from the RAI-NH three-monthly, and hospitalization data with the help of a data platform, reflection tools and hospital discharge reports continuously from the baseline period until the end of the data collection in 02.2020. The hypotheses of the project are: * To assess the effectiveness of the nurse-led care model on unplanned hospitalizations (primary outcome) and additional resident and staff outcomes, hypothesizing that nursing homes with a nurse-led care model have lower rates of unplanned hospitalizations and show improvements in additional resident and staff outcomes * To assess the effect of the degree of adoption on client outcomes, hypothesizing that a higher degree of adoption is related to better client outcomes * To describe the implementation costs the Swiss nurse-led interprofessional NH care model on the NH level and to assess the economic impact of INTERCARE with a cost-effectiveness analysis adopting a health care system perspective (comparing the increase in staff costs with the decrease of days of avoidable hospitalizations) * To explore resident/family and staff perceptions of service outcomes (e.g., timeliness) and the acceptability of the nurse-led care model; * To describe the degree to which the model was adopted, its feasibility, the fidelity with which it was applied, and the barriers and facilitators met by NH leadership and nurse experts.
This multicentre study uses a mixed-methods approach to evaluate testing of a nurse-led care model intervention. Each of the 11 NHs participating in this study will recruit at least one registered nurse with at least three years' long-term care experience, which will undergo training to become a geriatric nurse expert. Training of the geriatric nurse experts will be delivered as a blended-learning approach, combining face to face (F2F) teaching and E-learning modules. The 8 modules will cover the following topics: 1. leadership, 2. communication, 3. comprehensive geriatric assessment, 4. geriatric syndromes, 5. chronic conditions, 6. acute conditions, 7. pharmacology in geriatrics and 8. quality improvement. Modules 1-3 and 8 will be delivered as 5 days of F2F teaching before the implementation start, followed by E-learnings, and 8 expert meetings to be continued throughout the intervention. The last meeting takes place in November 2019. Additionally, the practical training will be enhanced by individual supervision with an experienced nurse expert and/or geriatrician. Modules 4-7 will be delivered via E-learning modules. All modules will cover approximately 66h of F2F learning and 60 hours of E-learning, depending on the level of education and experience of each nurse. In total the geriatric nurse expert training should account for approximately 125 hours. The registered nurse which will take on the role of geriatric nurse expert will either be recruited within the pool of nurses in each respective NH or recruited from the outside. The nurse-led care model will be built with core components, such as interprofessional collaboration, presence of a geriatric nurse expert, comprehensive geriatric assessment, advance care planning, guidance and coaching, data driven quality and evidence-based tools. Each NH will have to implement these core components along with implementing the role of geriatric nurse expert. The intervention will be implemented and evaluated by means of a non-randomized quasi experimental stepped-wedge design, over a period of 21 months. The stepped wedge design allows inclusion of all NHs, thus does not exclude NHs from receiving the INTERCARE \| Research plan Version 1.1/09.05. 2018 20/53 intervention. The "stepped" or "graded" unidirectional allocation to the intervention enables each NH to act as its own control. After a 3-month baseline phase, NHs will sequentially begin implementation of the nurse-led care model, which they will continue to use post-implementation. A get-in period of 1 month will be planned to address possible timing problems at the intervention start. Another advantage of the design is the graded start in the NHs facilitating delivery of the intervention, as each NH will discuss with the research team when they will receive the intervention. The first two NHs will start their baseline data collection in June 2018 and implement the intervention in September 2018, and every month thereafter, two other NHs will start with the intervention. A non-randomized design was chosen to enable NHs to choose when they will start with the intervention, to allow for each NH to prepare accordingly for the implementation. Limitations of this study design might arise from its novelty. So far, no gold standard for data analysis has been established. In addition to this, non-randomization of the starting point of the intervention may imply that NHs were prepared for the intervention and this may be reflected in the results.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
944
A nurse-model of care consisting of a specifically trained geriatric nurse expert, communication and quality improvement tools will be implemented in 11 nursing homes in the German speaking part of Switzerland
Obesunne
Arlesheim, Switzerland
St Christophorus
Basel, Switzerland
Marienhaus
Basel, Switzerland
Domicil schwabgut
Bern, Switzerland
Zentrum Schlossmat
Burgdorf, Switzerland
Viva Luzern
Lucerne, Switzerland
Reusspark
Niederwil, Switzerland
Number of all unplanned hospitalizations /1000 resident care days
Due to the complexity involved in the measurement of avoidable hospitalizations, we will follow experts' recommendation \[24\], tracking all unplanned hospital admissions as a primary endpoint. The primary endpoint will be calculated as number of unplanned hospitalisations per 1000 resident care days.
Time frame: 21 months
Avoidable hospitalizations
Number of hospitalizations for ambulatory care sensitive conditions (ACSC). ACSCs will be assessed via the residents' hospital discharge report.
Time frame: 21 months
Avoidable emergency department (ED) visits
Number of avoidable ED visits per 1000 care days
Time frame: 21 months
Resident quality indicators: Pain
National quality indicators such as pain are collected by means of the Resident assessment Instrument for nursing homes in routine practice, and are collected independently of the study. The quality indicator "pain" will be measured by: * % of residents with self-reported pain * % of residents with observed pain (i.e. daily pain of moderate intensity or non-daily pain of severe intensity)
Time frame: 21 months
Resident quality indicators: physical restraints
National quality indicators such as physical restraints are collected by means of the Resident assessment Instrument for nursing homes in routine practice, and are collected independently of the study. The quality indicator "physical restraint" will be measured by: % of residents with daily fixation of the trunk or seating that does not allow standing during the preceding 7 days, or with daily use of bedrails over the preceding 7 days
Time frame: 21 months
Resident quality indicators: Polypharmacy
National quality indicators such as polypharmacy are collected by means of the Resident assessment Instrument for nursing homes in routine practice, and are collected independently of the study. The quality indicator "polypharmacy" will be measured by: % of residents receiving 9 or more medications (active components) over the preceding 7 days
Time frame: 21 months
Resident quality indicators: weight loss
National quality indicators such as weight loss are collected by means of the Resident assessment Instrument for nursing homes in routine practice, and are collected independently of the study. The quality indicator "weight loss" will be measured by: % of residents with weight loss of 5% or more during the preceding 30 days, or of 10% or more in the preceding 180 days.
Time frame: 21 months
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