Longitudinal Evaluation of a Statewide Quality Improvement Program for Nursing Homes.

OBJECTIVES: The National Academies of Sciences, Engineering, and Medicine (NASEM) Nursing Home Quality report recommends that states "develop and operate state-based…technical assistance programs…to help nursing homes…improve care and…operations." The Quality Improvement Program for Missouri (QIPMO) is one such program. This longitudinal evaluation examined and compared differences in quality measures (QMs) and nursing home (NH) characteristics based on intensity of QIPMO services used. DESIGN: A descriptive study compared key QMs of clinical care, facility-level characteristics, and differing QIPMO service intensity use. QIPMO services include on-site clinical consultation by expert nurses; evidence-based practice information; teaching NHs use of quality improvement (QI) methods; and guiding their use of Centers for Medicare and Medicaid Services (CMS)-prepared QM comparative feedback reports to improve care. SETTING AND PARTICIPANTS: All Missouri NHs (n = 510) have access to QIPMO services at no charge. All used some level of service during the study, 2020-2022. METHODS: QM data were drawn from CMS's publicly available website (Refresh April 2023) and NH characteristics data from other public websites. Service intensity was calculated using data from facility contacts (on-site visits, phone calls, texts, emails, webinars). NHs were divided into quartiles based on service intensity. RESULTS: All groups had different beginning QM scores and improved ending scores. Group 2, moderate resource intensity use, started with "worse" overall score and improved to best performing by the end. Group 4, most resource intensity use, improved least but required highest service intensity. CONCLUSIONS AND IMPLICATIONS: This longitudinal evaluation of QIPMO, a statewide QI technical assistance and support program, provides evidence of programmatic stimulation of statewide NH quality improvements. It provides insight into intensity of services needed to help facilities improve. Other states should consider QIPMO success and develop their own programs, as recommended by the NASEM report so their NHs can embrace QI and "initiate fundamental change" for better care for our nation's older adults.

Exploring Hospital Transfers for Long-Stay Nursing Home Residents With End-Stage Renal Disease.

BACKGROUND: Nursing home residents with end-stage renal disease (ESRD) are an understudied, yet growing population within nursing homes. PURPOSE: To describe hospital transfers for nursing home residents diagnosed with ESRD and receiving hemodialysis. METHODS: Data were analyzed for residents with ESRD transferred to the hospital between October 2016 and September 2020 (n = 219). Descriptive statistics, bivariate analyses, logistic regression, and content analysis were used for analysis. RESULTS: Clinical factors associated with transfers included abnormal vitals, altered mental state, and pain. Other factors included lack of care planning and advance directives, provider communication, resident/family preferences, missing/refusing dialysis, and facility resources. The odds of an observation/emergency department only visit was 2.02 times larger when transferred from the dialysis clinic. CONCLUSIONS: Advance care planning and coordinated care between nursing home and dialysis clinics are needed along with proactive planning when residents miss dialysis or experience a condition change at the dialysis clinic.

Data-Driven Analytics to Discover APRN's Impact on Nursing Home Hospitalization: Causal Discovery Analysis.

OBJECTIVES: Research shows advanced practice registered nurses (APRNs) embedded in nursing homes (NHs) reduce resident hospitalizations. However, the specific APRN activities that reduce hospitalizations have not been adequately investigated. This study aims to identify the causal links between APRN activities and NHs resident hospitalization. The study also examined relationships among other variables, including advanced directives, clinical diagnosis, and length of hospitalization. DESIGN: Secondary data analysis. SETTING AND PARTICIPANTS: Residents of NHs participating in the Missouri Quality Initiative for Nursing Homes, 2016-2019. METHODS: We performed a secondary analysis of data from the Missouri Quality Initiative for Nursing Homes Intervention using causal discovery analysis, a machine learning, data-driven technique to determine causal relationships across data. The resident roster and INTERACT resident hospitalization datasets were combined to create the final dataset. Variables in the analysis model were divided into before and after hospitalization. Expert consensus was used to validate and interpret the outcomes. RESULTS: The research team analyzed 1161 hospitalization events and their associated NH activities. APRNs evaluated NH residents before a transfer, expedited follow-up nursing assessments, and authorized hospitalization when necessary. No significant causal relationships were found between APRN activities and the clinical diagnosis of a resident. The analysis also showed multifaceted relationships related to having advanced directives and duration of hospitalization. CONCLUSIONS AND IMPLICATIONS: This study demonstrated the importance of APRNs embedded in NHs to improve resident outcomes. APRNs in NHs can facilitate communication and collaboration among the nursing team, leading to early identification and treatment for resident status changes. APRNs can also initiate more timely transfers by reducing the need for physician authorization. These findings emphasize the crucial role of APRNs in NHs and suggest that budgeting for APRN services may be an effective strategy to reduce hospitalizations. Additional findings regarding advance directives are discussed.

Calling all nurses-Now is the time to take action on improving the quality of care in nursing homes.

For a number of decades, nurses have raised concerns about nursing-related issues in nursing homes (NH) such as inadequate registered nurse (RN) staffing, insufficient RN and advanced practice registered nurse (APRN) gerontological expertise, and lack of RN leadership competencies. The NASEM Committee on the Quality of Care in Nursing Homes illuminated the long-standing issues and concerns affecting the quality of care in nursing homes and proposed seven goals and associated recommendations intended to achieve the Committee's vision: Nursing home residents receive care in a safe environment that honors their values and preferences, addresses goals of care, promotes equity, and assesses the benefits and risks of care and treatments. This paper outlines concrete and specific actions nurses and nursing organizations can take to ensure the recommendations are implemented.

Sharing Lessons From Successes: Long-term Care Facilities That Weathered the Storm of COVID-19 and Staffing Crises.

PURPOSE: To identify leadership styles and staffing strategies in Missouri long-term care (LTC) facilities that stood out among their peers as "positive deviants" with regard to COVID-19 infections and staffing shortages. METHODS: Statewide survey of all LTC facilities to identify exemplar facilities with stable staffing and low rates of COVID-19. Interviews with senior leaders were conducted in 10 facilities in the state to understand the strategies employed that led to these "positive outliers." A result-based educational program was designed to describe their actions and staff reactions. RESULTS: Exemplar leaders used transformational leadership style. Top reasons for their success were as follows: (1) trusting and supportive staff relationships; (2) positive presence and communication; and (3) use of consistent staffing assignments. Strong statewide participation was noted in the educational programs.

Digital Methodology for Mobile Clinical Decision Support Development in Long-Term Care.

The global COVID-19 pandemic has driven innovations in methods to sustain initiatives for the design, development, evaluation, and implementation of clinical support technology in long-term care settings while removing risk of infection for residents, family members, health care workers, researchers and technical professionals. We adapted traditional design and evaluation methodology for a mobile clinical decision support app - designated Mobile Application Information System for Integrated Evidence ("MAISIE") - to a completely digital design methodology that removes in-person contacts between the research team, developer, and nursing home staff and residents. We have successfully maintained project continuity for MAISIE app development with only minor challenges while working remotely. This digital design methodology can be implemented in projects where software can be installed without in-person technical support and remote work is feasible. Team skills, experience, and relationships are key considerations for adapting to digital environments and maintaining project momentum.

Impact of Web-Based Cognitive Behavioral Therapy for Insomnia on Stress, Health, Mood, Cognitive, Inflammatory, and Neurodegenerative Outcomes in Rural Dementia Caregivers: Protocol for the NiteCAPP CARES and NiteCAPP SHARES Randomized Controlled Trial.

BACKGROUND: Chronic insomnia affects up to 63% of family dementia caregivers. Research suggests that chronic insomnia prompts changes in central stress processing that have downstream negative effects on health and mood, as well as on cognitive, inflammatory, and neurodegenerative functioning. We hypothesize that cognitive behavioral therapy for insomnia (CBT-I) will reverse those downstream effects by improving insomnia and restoring healthy central stress processing. Rural caregivers are particularly vulnerable, but they have limited access to CBT-I; therefore, we developed an accessible digital version using community input (NiteCAPP CARES). OBJECTIVE: This trial will evaluate the acceptability, feasibility, and short-term and long-term effects of NiteCAPP CARES on the sleep and stress mechanisms underlying poor caregiver health and functioning. METHODS: Dyads (n=100) consisting of caregivers with chronic insomnia and their coresiding persons with dementia will be recruited from Columbia and surrounding areas in Missouri, United States. Participant dyads will be randomized to 4 weeks (plus 4 bimonthly booster sessions) of NiteCAPP CARES or a web-based sleep hygiene control (NiteCAPP SHARES). Participants will be assessed at baseline, after treatment, and 6- and 12-month follow-ups. The following assessments will be completed by caregivers: 1 week of actigraphy and daily diaries measuring sleep, Insomnia Severity Index, arousal (heart rate variability), inflammation (blood-derived biomarkers: interleukin-6 and C-reactive protein), neurodegeneration (blood-derived biomarkers: plasma amyloid beta [Aß40 and Aß42], total tau, and phosphorylated tau [p-tau181 and p-tau217]), cognition (Joggle battery, NIH Toolbox for Assessment of Neurological and Behavioral Function, and Cognitive Failures Questionnaire), stress and burden, health, and mood (depression and anxiety). Persons with dementia will complete 1 week of actigraphy at each time point. RESULTS: Recruitment procedures started in February 2022. All data are expected to be collected by 2026. Full trial results are planned to be published by 2027. Secondary analyses of baseline data will be subsequently published. CONCLUSIONS: This randomized controlled trial tests NiteCAPP CARES, a web-based CBT-I for rural caregivers. The knowledge obtained will address not only what outcomes improve but also how and why they improve and for how long, which will help us to modify NiteCAPP CARES to optimize treatment potency and support future pragmatic testing and dissemination. TRIAL REGISTRATION: ClinicalTrials.gov NCT04896775; https://clinicaltrials.gov/ct2/show/NCT04896775. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37874.

Explainable Fall Risk Prediction in Older Adults Using Gait and Geriatric Assessments.

Older adults aged 65 and above are at higher risk of falls. Predicting fall risk early can provide caregivers time to provide interventions, which could reduce the risk, potentially avoiding a possible fall. In this paper, we present an analysis of 6-month fall risk prediction in older adults using geriatric assessments, GAITRite measurements, and fall history. The geriatric assessments included were Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). These geriatric assessments are collected by staff nurses regularly in senior care facilities. From the GAITRite assessments on the residents, we included the Functional Ambulatory Profile (FAP) scores and gait speed to predict fall risk. We used the SHAP (SHapley Additive exPlanations) approach to explain our model predictions to understand which predictor variables contributed to increase or decrease the fall risk for an individual prediction. In case of a high fall risk prediction, predictor variables that contributed the most to elevate the risk could be further examined by the health providers for more personalized health interventions. We used the geriatric assessments, GAITRite measurements, and fall history data collected from 92 older adult residents (age = 86.2 ± 6.4, female = 57) to train machine learning models to predict 6-month fall risk. Our models predicted a 6-month fall with an AUC of 0.80 (95% CI of 0.76-0.85), sensitivity of 0.82 (95% CI of 0.74-0.89), specificity of 0.72 (95% CI of 0.67-0.76), F1 score of 0.76 (95% CI of 0.72-0.79), and accuracy of 0.75 (95% CI of 0.72-0.79). These results show that our early fall risk prediction method performs well in identifying residents who are at higher fall risk, which offers care providers and family members valuable time to perform preventive actions.

Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity.

BACKGROUND: Nursing home residents are at increased risk for hospital transfers resulting in emergency department visits, observation stays, and hospital admissions; transfers that can also result in adverse resident outcomes. Many nursing home to hospital transfers are potentially avoidable. Residents who experience repeat transfers are particularly vulnerable to adverse outcomes, yet characteristics of nursing home residents who experience repeat transfers are poorly understood. Understanding these characteristics more fully will help identify appropriate intervention efforts needed to reduce repeat transfers. METHODS: This is a mixed-methods study using hospital transfer data, collected between 2017 and 2019, from long-stay nursing home residents residing in 16 Midwestern nursing homes who transferred four or more times within a 12-month timeframe. Data were obtained from an acute care transfer tool used in the Missouri Quality Initiative containing closed- and open-ended questions regarding hospital transfers. The Missouri Quality Initiative was a Centers for Medicare and Medicaid demonstration project focused on reducing avoidable hospital transfers for long stay nursing home residents. The purpose of the analysis presented here is to describe characteristics of residents from that project who experienced repeat transfers including resident age, race, and code status. Clinical, resident/family, and organizational factors that influenced transfers were also described. RESULTS: Findings indicate that younger residents (less than 65 years of age), those who were full-code status, and those who were Black were statistically more likely to experience repeat transfers. Clinical complexity, resident/family requests to transfer, and lack of nursing home resources to manage complex clinical conditions underlie repeat transfers, many of which were considered potentially avoidable. CONCLUSIONS: Improved nursing home resources are needed to manage complex conditions in the NH and to help residents and families set realistic goals of care and plan for end of life thus reducing potentially avoidable transfers.

Longitudinal analysis of aging in place at TigerPlace: Resident function and well-being.

This paper reports on a longitudinal eight-year analysis (2011-2019) of trajectory of function and well-being residents of TigerPlace Aging in Place (AIP) model of care. Residents were routinely assessed using standard health assessment instruments. Average scores from each measure were examined for changes or trends in resident function; decline over time was calculated. Scores for depression, mental health subscale Short Form Health Survey-12 (SF-12) remained stable over time. Mini Mental State Exam declined to mild dementia range (21-24). Physical measures SF-12 physical health subscale, ADLs, and IADLs declined slightly, while fall risk increased over time. When yearly trends in AIP were modeled with a referent group there was no significant worsening of functioning. The length of stay for TigerPlace residents continued to remain stable at nearly 30 months. Residents maintained function in the environment of their choice longer at cost less than nursing homes, and just above residential care cost.

Value Propositions for Health Information Exchange Toward Improving Nursing Home Hospital Readmission Rates.

The importance of health information technology use in nursing home (NH) care delivery is a major topic in research exploring methods to improve resident care. Topics of interest include how technology investments, infrastructure, and work-force development lead to better methods of nursing care delivery and outcomes. Value propositions, including perceived benefits, incentives, and system changes recognized by end-users, are important resources to inform NH leaders, policymakers, and stakeholders about technology. The purpose of the current research was to identify and disseminate value propositions from a community of stakeholders using a health information exchange (HIE). Researchers used a nominal group process, including 49 individual stakeholders participating in a national demonstration project to reduce avoidable hospitalizations in NHs. Stakeholders identified 41 total anticipated changes from using HIE. Ten stakeholder types were perceived to have experienced the highest impact from HIE in areas related to resident admissions, communication, and efficiency of care delivery. [Journal of Gerontological Nursing, 48(1), 15-20.].

A Call to Address RN, Social Work, and Advanced Practice Registered Nurses in Nursing Homes: Solutions From the Missouri Quality Initiative.

BACKGROUND: US nursing homes (NHs) have struggled to overcome a historic pandemic that laid bare limitations in the number and clinical expertise of NH staff. PROBLEM: For nurse staffing, current regulations require only one registered nurse (RN) on duty 8 consecutive hours per day, 7 days per week, and one RN on call when a licensed practical/vocational nurse is on duty. There is no requirement for a degreed or licensed social worker, and advanced practice registered nurses (APRNs) in NHs cannot bill for services. APPROACH: It is time to establish regulation that mandates a 24-hour, 7-day-a-week, on-site RN presence at a minimum requirement of 1 hour per resident-day that is adjusted upward for greater resident acuity and complexity. Skilled social workers are needed to improve the quality of care, and barriers for APRN billing for services in NHs need to be removed. CONCLUSIONS: Coupling enhanced RN and social work requirements with access to APRNs can support staff and residents in NHs.

Social practices of nurse care coordination using sensor technologies - Challenges with an alert system adoption in assisted living communities for older adults.

OBJECTIVES: From the view of everyday practices and the socio-technical coordination lens, this study aimed to analyz the gap between creators' intention and the users' implementation (mainly nursing staff and social workers) of an alert system in assisted living communities. METHODS: Qualitative methods were employed by way of five user interviews and focus groups with six system developers. Modeling instruments were applied for data collection to analyze the different clinical workflows versus the expectations of the system development team. RESULTS: Results indicate that the clinical workflow changed over time, which led to a mismatch of nurse care coordination, social practices, and technology use. The results show different mental models of the socio-technical practice. Applying the coordination theory, the following recommendations could be developed to overcome the mismatch. First, it is recommended that nursing staff set goals together. Second, a communication rhythm with the nursing staff and developer teams should be established, with guided questions to facilitate the conversation, to shed light on the different workflows and the difference in social practices when using sensor technologies or alert systems. Third, a checklist for new employees should be created so they know how and on which devices to use the alert system. Fourth, the user experience with the alert system should be improved (e.g., an improved user interface). CONCLUSIONS: This work indicates recommendations to close the mental model gap to overcome the mismatch between optimal use of the alert system and how the nursing staff is actually using it.

Take it to the resident: A model for engaging long-term stay residents in advance care planning.

Advance care planning involves a meaningful conversation about residents' end of life goals with the health-care team and documenting these wishes in advance directives; however, these conversations are not taking place early enough or with strategies that allow nursing home residents' preferences to be meaningfully integrated into care plans. This article outlines a new model that nursing home social workers can use to initiate advance care planning discussions called Take it to the Resident. This model was tested with 11 long-term stay nursing home residents. Data were collected through structured memos and field notes. Summative content analysis was utilized to analyze the data. Take it to the Resident facilitated a discussion about advance care planning and allowed residents to consider their wishes before engaging family members. Although discussions took place, some residents were hesitant to document their wishes formally through advance directives. The results of this study support the utility of continued testing of this model. Having empirically supported tools for nursing home social workers is critical to increasing advance care planning conversations and empowering residents to document their wishes.