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1.
Implement Sci Commun ; 3(1): 74, 2022 Jul 16.
Article in English | MEDLINE | ID: mdl-35842692

ABSTRACT

BACKGROUND: Effective communication in transitions between healthcare team members is associated with improved patient safety and experience through a clinically meaningful reduction in serious safety events. Family-centered rounds (FCR) can serve a critical role in interprofessional and patient-family communication. Despite widespread support, FCRs are not utilized consistently in many institutions. Structured FCR approaches may prove beneficial in increasing FCR use but should address organizational challenges. The purpose of this study was to identify intervention, individual, and contextual determinants of high adherence to common elements of structured FCR in pediatric inpatient units during the implementation phase of a large multi-site study implementing a structured FCR approach. METHODS: We performed an explanatory sequential mixed methods study from September 2019 to October 2020 to evaluate the variation in structured FCR adherence across 21 pediatric inpatient units. We analyzed 24 key informant interviews of supervising physician faculty, physician learners, nurses, site administrators, and project leaders at 3 sites using a qualitative content analysis paradigm to investigate site variation in FCR use. We classified implementation determinants based on the Consolidated Framework for Implementation Research. RESULTS: Provisional measurements of adherence demonstrated considerable variation in structured FCR use across sites at a median time of 5 months into the implementation. Consistent findings across all three sites included generally positive clinician beliefs regarding the use of FCR and structured rounding approaches, benefits to learner self-efficacy, and potential efficiency gains derived through greater rounds standardization, as well as persistent challenges with nurse engagement and interaction on rounds and coordination and use of resources for families with limited English proficiency. CONCLUSIONS: Studies during implementation to identify determinants to high adherence can provide generalizable knowledge regarding implementation determinants that may be difficult to predict prior to implementation, guide adaptation during the implementation, and inform sustainment strategies.

2.
Int J Older People Nurs ; 17(3): e12447, 2022 May.
Article in English | MEDLINE | ID: mdl-35043568

ABSTRACT

BACKGROUND: Persons living with dementia (PLWD) are at risk for chronic wounds; however, they are rarely included in research. OBJECTIVES: To inform practice and research directions, the aim of this integrative review was to identify and synthesise previous knowledge about the characteristics of chronic wounds in PLWD, in terms of chronic wound types, prevalence, setting and interventions. DESIGN: A literature search was conducted for publications in English using PubMed, Web of Science and CINAHL. The minimum information required for inclusion was how many PLWD enrolled in the study had wounds. METHODS: This integrative review followed the Whittemore and Knafl methodology. Data extraction and synthesis were guided by a directed content analysis, with a coding structure based on an initial review of the literature. RESULTS: Thirty-six articles met the inclusion criteria. The majority were missing characteristics of PLWD including severity of dementia and race/ethnicity/nationality, and none mentioned skin tone. Most focused on pressure injuries in the nursing home and acute care setting. Few included information on interventions. Only one discussed challenges of wound care for a PLWD exhibiting aggression. CONCLUSION: There is a gap in the literature regarding PLWD and chronic wounds other than pressure injuries that are common in older adults (e.g. diabetic foot ulcers, venous leg ulcers). Research is warranted among those PLWD who live alone and those who receive wound care from family caregivers to understand experiences. Knowledge can inform the development of future novel interventions for wound healing. Future research is needed regarding chronic wounds in those who exhibit behavioural and psychological symptoms of dementia. RELEVANCE TO CLINICAL PRACTICE: Nurses that care for chronic wounds in PLWD can contribute their knowledge to include information in guidelines on best care practices and contribute their perspective to research teams for future research.


Subject(s)
Dementia , Diabetic Foot , Aged , Caregivers , Humans
3.
Article in English | MEDLINE | ID: mdl-30559601

ABSTRACT

One challenge in using naturalistic driving data is producing a holistic analysis of these highly variable datasets. Typical analyses focus on isolated events, such as large g-force accelerations indicating a possible near-crash. Examining isolated events is ill-suited for identifying patterns in continuous activities such as maintaining vehicle control. We present an alternative approach that converts driving data into a text representation and uses topic modeling to identify patterns across the dataset. This approach enables the discovery of non-linear patterns, reduces the dimensionality of the data, and captures subtle variations in driver behavior. In this study topic models are used to concisely described patterns in trips from drivers with and without untreated obstructive sleep apnea (OSA). The analysis included 5000 trips (50 trips from 100 drivers; 66 drivers with OSA; 34 comparison drivers). Trips were treated as documents, and speed and acceleration data from the trips were converted to "driving words." The identified patterns, called topics, were determined based on regularities in the co-occurrence of the driving words within the trips. This representation was used in random forest models to predict the driver condition (i.e., OSA or comparison) for each trip. Models with 10, 15 and 20 topics had better accuracy in predicting the driver condition, with a maximum AUC of 0.73 for a model with 20 topics. Trips from drivers with OSA were more likely to be defined by topics for smaller lateral accelerations at low speeds. The results demonstrate topic modeling as a useful tool for extracting meaningful information from naturalistic driving datasets.

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