Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives.

BACKGROUND: Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap. OBJECTIVES: This report had two objectives. First, it aimed to synthesize implementation barrier and facilitator data from employee wellness QI initiatives across Veteran Affairs health care systems through a semantic and ontological approach. Second, it introduced an original framework of this use-case-based taxonomy on implementation barriers and facilitators within a QI process. METHODS: We synthesized terms from combined datasets of all-site implementation barriers and facilitators through QI cause-and-effect analysis and qualitative thematic analysis. We developed the Quality Improvement and Implementation Taxonomy (QIIT) classification scheme to categorize synthesized terms and structure. This framework employed a semantic and ontological approach. It was built upon existing terms and models from the QI Plan, Do, Study, Act phases, the Consolidated Framework for Implementation Research domains, and the fishbone cause-and-effect categories. RESULTS: The QIIT followed a hierarchical and relational classification scheme. Its taxonomy was linked to four QI Phases, five Implementing Domains, and six Conceptual Determinants modified by customizable Descriptors and Binary or Likert Attribute Scales. CONCLUSION: This case report introduces a novel approach to standardize the process and taxonomy to describe evidence translation to QI implementation barriers and facilitators. This classification scheme reduces redundancy and allows semantic agreements on concepts and ontological knowledge representation. Integrating existing taxonomies and models enhances the efficiency of reusing well-developed taxonomies and relationship modeling among constructs. Ultimately, employing STs helps generate comparable and sharable QI evaluations for forecast, leading to sustainable implementation with clinically informed innovative solutions.

Developing a Quality Improvement Implementation Taxonomy for Organizational Employee Wellness Initiatives.

BACKGROUND: Standardized taxonomies (STs) facilitate knowledge representation and semantic interoperability within health care provision and research. However, a gap exists in capturing knowledge representation to classify, quantify, qualify, and codify the intersection of evidence and quality improvement (QI) implementation. This interprofessional case report leverages a novel semantic and ontological approach to bridge this gap. OBJECTIVES: This report had two objectives. First, it aimed to synthesize implementation barrier and facilitator data from employee wellness QI initiatives across Veteran Affairs health care systems through a semantic and ontological approach. Second, it introduced an original framework of this use-case-based taxonomy on implementation barriers and facilitators within a QI process. METHODS: We synthesized terms from combined datasets of all-site implementation barriers and facilitators through QI cause-and-effect analysis and qualitative thematic analysis. We developed the Quality Improvement and Implementation Taxonomy (QIIT) classification scheme to categorize synthesized terms and structure. This framework employed a semantic and ontological approach. It was built upon existing terms and models from the QI Plan, Do, Study, Act phases, the Consolidated Framework for Implementation Research domains, and the fishbone cause-and-effect categories. RESULTS: The QIIT followed a hierarchical and relational classification scheme. Its taxonomy was linked to four QI Phases, five Implementing Domains, and six Conceptual Determinants modified by customizable Descriptors and Binary or Likert Attribute Scales. CONCLUSION: This case report introduces a novel approach to standardize the process and taxonomy to describe evidence translation to QI implementation barriers and facilitators. This classification scheme reduces redundancy and allows semantic agreements on concepts and ontological knowledge representation. Integrating existing taxonomies and models enhances the efficiency of reusing well-developed taxonomies and relationship modeling among constructs. Ultimately, employing STs helps generate comparable and sharable QI evaluations for forecast, leading to sustainable implementation with clinically informed innovative solutions.

The Community Resiliency Model, an interoceptive awareness tool to support population mental wellness.

The objective of this article is to describe the Community Resiliency Model (CRM)®, a sensory-focused, self-care modality for mental well-being in diverse communities, and CRM's emerging evidence base and neurobiological underpinnings as a task-sharing intervention. Frieden's Health Impact Pyramid (HIP) is used as a lens for mental healthcare interventions and their public health impact, with CRM examples. CRM, a sensory awareness model for self-care and mental well-being in acute and chronic stress states, is supported by neurobiological theory and a growing evidence base. CRM can address mental wellness needs at multiple levels of the HIP and matches the task-sharing concept to increase access to mental health resources globally. CRM has the potential for making a significant population mental health impact as an easily disseminated, mental health, self-care modality; it may be taught by trained professionals, lay persons, and community members. CRM carries task-sharing to a new level: scalable and sustainable, those who learn CRM can share the wellness skills informally with persons in their social networks. CRM may alleviate mental distress and reduce stigma, as well as serve a preventive function for populations facing environmental, political, and social threats.

The impact of the Community Resiliency Model (CRM) on the mental well-being of youth at risk for violence: A study protocol.

PURPOSE: Assess the effect of a brief, somatic awareness resiliency training, the Community Resiliency Model (CRM)®, on the mental well-being of incarcerated youth. SPECIFIC AIM 1: Explore the relationship between youth demographics and justice history to baseline well-being scores and response to treatment. Q1: How do personal variables, including length of time in juvenile justice, relate to baseline mental health scores and response to the wellness skills intervention? SPECIFIC AIM 2: Examine the mental health scores over time to determine effectiveness of participating in CRM training while incarcerated. Hypothesis 1: Well-being scores will increase after CRM training. Hypothesis 2: Emotional distress will decrease after participating in a CRM training. Hypothesis 3: Pro-social feelings and behaviors will increase after participating in a CRM training.

Practical resiliency training for healthcare workers during COVID-19: results from a randomised controlled trial testing the Community Resiliency Model for well-being support.

OBJECTIVE: To introduce the Community Resiliency Model (CRM) as mental well-being support for healthcare workers working through the height of the COVID-19 pandemic. DESIGN: Randomised controlled trial with a no treatment control group. SETTING: Two large urban health systems in the Southern United States between October 2020 and June 2021. PARTICIPANTS: Eligible participants were currently employed as healthcare workers within the participating healthcare systems. 275 employees registered and consented electronically in response to email invitations. 253 participants completed the baseline survey necessary to be randomised and included in analyses. INTERVENTION: Participants were assigned 1:1 to the control or intervention group at the time of registration. Intervention participants were then invited to 1-hour virtual CRM class teaching skills to increase somatic awareness in the context of self and other care. MAIN OUTCOME MEASURES: Self-reported data were collected rating somatic awareness, well-being, symptoms of stress, work engagement and interprofessional teamwork. RESULTS: Baseline data on the total sample of 275 (53% nurses) revealed higher symptoms of stress and lower well-being than the general population. The intervention participants who attended a CRM class (56) provided follow-up survey data at 1 week (44) and 3 months (36). Significant improvement for the intervention group at 3 months was reported for the well-being measures (WHO-5, p<0.0087, d=0.66; Warwick-Edinburgh Mental Well-Being Scale, p<0.0004, d=0.66), teamwork measure (p≤0.0002, d=0.41) and stress (Secondary Traumatic Stress Scale, p=0.0058, d=46). CONCLUSION: Baseline results indicate mental health is a concern for healthcare workers. Post intervention findings suggest that CRM is a practical approach to support well-being for healthcare workers during a crisis such as this pandemic. The simple tools that comprise the model can serve as a starting point for or complement self-care strategies to enhance individual resilience and buffer the effects of working in an increasingly stressful work environment.

A Nurse-Led, Well-Being Promotion Using the Community Resiliency Model, Atlanta, 2020-2021.

The wrath of COVID-19 includes a co-occurring global mental health pandemic, raising the urgency for our health care sector to implement strategies supporting public mental health. In Georgia, a successful nurse-led response to this crisis capitalized on statewide organizations' existing efforts to bolster well-being and reduce trauma. Partnerships were formed and joint aims identified to disseminate a self-care modality, the Community Resiliency Model, to organizations and communities throughout the state. (Am J Public Health. 2022;112(S3):S271-S274. https://doi.org/10.2105/AJPH.2022.306821).

Role of Supplemental Nutrition Assistance Program in Improving Diet Quality: Implications for Nurses.

The Supplemental Nutrition Assistance Program (SNAP) provides access to healthy food for low-income individuals and households. Food security, however, does not necessarily achieve higher diet quality for beneficiaries. Diet quality is an important consideration for the development and management of chronic illness, a significant public health concern. In this study, we review incentives and disincentives implemented to improve the diet quality, the evidence on SNAP including benefits, challenges, and the politics of funding. New interventions and policies will be needed in order to improve the overall diet quality of SNAP households. SNAP should align with nutritional science to meet national public health goals. Nurses are trusted advocates for patients and the public and are uniquely positioned to aid in this effort. Informed by evidence, nurses willing to leverage their influence, can lead this needed change.

Translating What Works: A New Approach to Improve Diabetes Management.

BACKGROUND: The most efficacious strategies to improve diabetes control include case management, health care team changes, patient education, and facilitated transmission of patient data to clinicians ("facilitated relay"), but these strategies have not been translated to permit general use in clinical practice. METHODS: A web-based decision support program was developed to include these features, and assessed in patients who had A1c ≥7.0% despite using metformin with/without sulfonylureas or insulin. Staff entered patients' glucose data, obtained management recommendations, reviewed the plan with a clinician, and discussed the new plan with patients. RESULTS: 113 subjects were 96% male and 32% black, with average age 65.6 years and BMI 32.8. During prior primary care, A1c averaged 8.32 ± 0.16% (SEM). In all patients, baseline A1c was 8.18 ± 0.11%, and decreased to 7.54 ± 0.12%, 7.16 ± 0.13%, and 7.54 ± 0.16% at 3, 6, and 12 months, respectively, all P < .001. In 42 subjects who provided glucose data and made requested changes in medications, A1c was 8.12 ± 0.09% at baseline and fell to 7.29 ± 0.11%, 6.98 ± 0.10%, and 7.05 ± 0.10% at 3, 6, and 12 months, respectively, all P < .001. Chart review of 16 subjects followed for 12 months demonstrated that hypoglycemia (symptoms and/or glucose <70 mg/dl) averaged less than 1 episode/patient/month, and there was no severe hypoglycemia. CONCLUSIONS: A novel decision support program improved A1c with little hypoglycemia. Use of this approach should allow primary care teams to keep patients well controlled, and reduce the need for specialist referrals.