Dataset Information

Optimizing a knowledge translation intervention: a qualitative formative study to capture knowledge translation needs in nursing homes.

ABSTRACT:

Background

Knowledge translation (KT) has emerged as an important consideration to reduce knowledge-to-practice gaps in healthcare settings. Research on KT approaches in nursing homes (NHs) is lacking. There is a need to understand the challenges faced in NHs and how these can be managed. This study is part of the larger IMPAKT (IMPlementation and Action for Knowledge Translation) study which addresses KT in NHs. The aim of the study presented here was to identify crucial staff and organizational needs in order to inform the development of a KT intervention in NHs.

Methods

A multimethod qualitative approach was applied. We invited practice development nurses (PDNs) to describe current practice, and to identify problems and needs concerning KT in NHs. We followed the recommendations of the development phase of the MRC framework for developing complex interventions. Data were collected through four focus groups and participatory observations in six NHs. Analysis was conducted according to structural thematic analysis based on a phenomenological hermeneutic method.

Results

We identified three themes that expressed the PDNs' perceived needs for successful KT implementation: (1) narrowing the PDN role, (2) developing an EBP culture and (3) establishing collaborative alliances. Nine subthemes derived from the PDNs' experiences and current practice, illustrating needs at individual, relational and organizational levels.

Conclusions

Rigorous development of complex interventions may add relevance to the intervention, increase the likelihood of success and reduce research waste. Insight into the NH context and organization have helped us define problems and articulate needs that must be addressed when tailoring the IMPAKT intervention.

Trial registration

The IMPAKT trial was retrospectively registered in the ISRCTN Registry (Trial ID: 12,437,773) on March 19th, 2020.

SUBMITTER: Steinskog TD

PROVIDER: S-EPMC8218383 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCare personalization is key to the well-being of people with dementia according to person-centered care. With the development of the internet of things, a large quantity of personal data can be collected securely and reliably, which has the potential to facilitate care personalization for people with dementia. Yet, there are limited assistive technologies developed for this purpose, and the user acceptance of assistive technologies is low in nursing homes. Therefore, through a data-enabled design approach, a digital platform was developed for helping the care team in a nursing home to personalize dementia care, specifically in the management of behavioral and psychological dementia symptoms.ObjectiveThis study aimed to evaluate the digital platform in a real-life context with potential users from the following two aspects: (1) to explore if the digital platform could help with generating insights on the current state of each person with dementia and (2) to gather feedback on the digital platform from the care team.MethodsThe digital platform was deployed in the nursing home for 7 weeks and the data collected were visualized and presented to the care team via the digital platform. The visualizations were analyzed by the researchers for pattern detection. Meanwhile, the care team was asked to examine the visualizations and were interviewed for the following: (1) if any insights and actions were generated from the examination, (2) the usefulness of the digital platform, and (3) the improvements they would like to see.ResultsThe data collected on the digital platform demonstrated its potential for pattern detection. Insights were generated by the care team and categorized into "client level," "ward level," and "team level." The corresponding actions taken by the care team were classified into "investigation" and "implementation." User acceptance varied across the care team, and three aspects of improvement for the digital platform were identified.ConclusionsBy evaluating the digital platform, this study gained insights on applying data-enabled design for personalizing dementia care; besides, it offers future researchers some recommendations on how to integrate assistive technologies in the nursing home context.

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Project description:ObjectivesThe homeless population is aging, and their use of nursing homes is not well understood. We compared comorbidities (substance use, mental health conditions, and physical illness) and nursing home measures (source of admission, length of stay, and mortality in the facility) of veterans who were homeless, at risk for being homeless, or stably housed in the year prior to admission.DesignCross-sectional analysis.Setting and participantsAll veterans admitted to a nursing home between January 2010 and December 2016 and their housing status in the year prior to their nursing home admission.MeasurementsAdjusted relative risks (ARRs) for the association between housing status, comorbidities, and nursing home measures.ResultsVeterans who were homeless in the year prior to their community nursing home admission were younger (n = 3355; 62.5 years [SD = 10.3 years]) at admission compared to stably housed veterans (n = 64 884; 75.3 years [SD = 11.9 years]). After adjustment for demographic characteristics, homeless veterans were more likely to have diagnoses for alcohol abuse (ARR = 2.18; 95% confidence interval [CI] = 2.05-2.31), drug abuse (ARR = 3.03; 95% CI = 2.74-3.33), mental health condition (ARR = 1.49; 95% CI = 1.45-1.54), dementia (ARR = 1.14; 95% CI = 1.04-1.25), liver disease (ARR = 1.32; 95% CI = 1.23-1.41), lung disease (ARR = 1.08; 95% CI = 1.04-1.13), and trimorbidity (co-occurring substance abuse, mental illness, and physical illness) (ARR = 2.57; 95% CI = 2.40-2.74) compared to stably housed veteran nursing home users. Homeless veterans were more likely to be admitted to a nursing home from a hospital (ARR = 1.13; 95% CI = 1.08-1.17) and remain in the nursing home 90 days after admission (ARR = 1.10; 95% CI = 1.04-1.16), but were less likely to die in the facility (ARR = 0.72; 95% CI = 0.67-0.78) compared to stably housed veterans.ConclusionsHomeless veteran nursing home users have different characteristics than stably housed veteran nursing home users. These differences may challenge nursing home staff caring for homeless patients. Nursing homes should assess resident housing status to help provide linkages with existing social services. J Am Geriatr Soc 67:1707-1712, 2019.