7 results match your criteria: "Jönköping University School of Health and Welfare[Affiliation]"

Background: Cost is a key outcome in quality and value, but it is often difficult to estimate reliably and efficiently for use in real-time improvement efforts. We describe a method using patient-reported outcomes (PROs), Markov modeling, and statistical process control (SPC) analytics in a real-time cost-estimation prototype designed to assess cost differences between usual care and improvement conditions in a national multicenter improvement collaborative-the IBD Qorus Learning Health System (LHS).

Methods: The IBD Qorus Learning Health System (LHS) collects PRO data, including emergency department utilization and hospitalizations from patients prior to their clinical visits.

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Objective: To explore how primary healthcare workers in Sweden experienced and perceived the long-term impact of the pandemic on their work.

Design: This is a descriptive qualitative study with individual semistructured interviews conducted 2 years after the onset of COVID-19. Data were analysed using an inductive thematic approach.

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Objective: Surveys are a commonly used tool in quality improvement (QI) projects, but little is known about the standards to which they are designed and applied. We aimed to investigate the quality of surveys used within a QI collaborative, and to characterise the common errors made in survey design.

Methods: Five reviewers (two research methodology and QI, three clinical and QI experts) independently assessed 20 surveys, comprising 250 survey items, that were developed in a North American cystic fibrosis lung transplant transition collaborative.

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Background: Co-production is promoted as an effective way of improving the quality of health and social care but the diversity of measures used in individual studies makes their outcomes difficult to interpret.

Objective: The objective is to explore how empirical studies in health and social care have described the outcomes of co-production projects and how those outcomes were measured.

Design And Methods: A scoping review forms the basis for this systematic review.

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Background: Stress-related biomarkers have the potential to provide objective measures of whether interventions directed at people with dementia (PWD) and their family caregivers (FCG) are successful. The use of such biomarkers has been limited by logistical barriers to sample collection.

Objective: Explore saliva concentration of steroid hormones in dementia care dyads during a music intervention.

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Background: The implementation of artificial intelligence (AI) in mental healthcare offers a potential solution to some of the problems associated with the availability, attractiveness, and accessibility of mental healthcare services. However, there are many knowledge gaps regarding how to implement and best use AI to add value to mental healthcare services, providers, and consumers. The aim of this paper is to identify challenges and opportunities for AI use in mental healthcare and to describe key insights from implementation science of potential relevance to understand and facilitate AI implementation in mental healthcare.

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The rationale was to explore the efficacy/sensitivity of using morning and evening cortisol levels as biomarkers for stress reduction in persons with dementia (PWDs) and their family caregivers (FCGs) participating in a music intervention program. Thirty-two PWD and their FGC were recruited to an 8-week, home-based music intervention program. Daily home-based collection of saliva samples took place at bedtime and upon awakening.

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