Transitional care from skilled nursing facilities to home: study protocol for a stepped wedge cluster randomized trial

Life-Space of Older Adults after Discharge from Skilled Nursing Facilities

OBJECTIVES

Describe (1) patient or caregiver perceptions of physical function in 30 days after skilled nursing facility (SNF) discharge indicated by Life-Space Assessment (LSA) scores, and (2) patient and caregiver factors associated with LSA scores.

DESIGN

Secondary analysis of baseline and outcomes data from the cluster randomized trial of the Connect-Home transitional care intervention.

SETTING AND PARTICIPANTS

Six SNFs in North Carolina. Patient and caregiver dyads with LSA scores (N = 245).

METHODS

SNF patients or their caregivers serving as proxy reported the life-space of the SNF patient using the LSA tool, a measure of environmental and social factors that influence physical mobility. Simple scores for highest life-space attained depending on equipment and/or caregiver support range from 0 to 5, with higher scores indicating greater mobility. Multiple linear regression models for simple LSA scores and Composite Life-Space (0-120), adjusted for treatment, time via a COVID pandemic indicator, and treatment × COVID effect as fixed effects, were used to estimate the association of patient and caregiver variables and life-space.

RESULTS

Patients had a mean age of 76.3 years, 62.6% were female, and 74.7% were white. Caregivers were commonly female (73.9%) and adult children of the patient (46.5%). The mean Composite Life-Space score was 22.6 (16.09). The mean Assisted Life-Space score (range: 0-5) was 1.6 (1.47), and 76.3% of patients could not move beyond their bedroom, house, and yard without assistance of another person. Higher Composite Life-Space scores were associated with lower levels of cognitive impairment and shorter SNF length of stay.

CONCLUSIONS AND IMPLICATIONS

SNF patients and their caregivers reported very low LSA scores in 30 days after SNF care. Findings indicate the need for care redesign to promote recovery of physical function of older adults after SNF discharge, such as optimizing SNF rehabilitative therapy and adding postdischarge rehabilitative supports at home.

Coordinated-Transitional Care (C-TraC) for Veterans from Subacute Rehabilitation to Home

OBJECTIVES

To adapt a successful acute care transitional model to meet the needs of veterans transitioning from post-acute care to home.

DESIGN

Quality improvement intervention.

SETTING AND PARTICIPANTS

Veterans discharged from a subacute care unit in the VA Boston Healthcare System's skilled nursing facility.

METHODS

We used the Replicating Effective Programs framework and Plan-Do-Study-Act cycles to adapt the Coordinated-Transitional Care (C-TraC) program to the context of transitions from a VA subacute care unit to home. The major adaptation of this registered nurse-driven, telephone-based intervention was combining the roles of discharge coordinator and transitional care case manager. We report the details of the implementation, its feasibility, and results of process measures, and describe its preliminary impact.

RESULTS

Between October 2021 and April 2022, all 35 veterans who met eligibility criteria in the VA Boston Community Living Center (CLC) participated; none were lost to follow-up. The nurse case manager delivered core components of the calls with high fidelity-review of red flags, detailed medication reconciliation, follow-up with primary care physician, and discharge services were discussed and documented in 97.9%, 95.9%, 86.8%, and 95.9%, respectively. CLC C-TraC interventions included care coordination, patient and caregiver education, connecting patients to resources, and addressing medication discrepancies. Nine medication discrepancies were discovered in 8 patients (22.9%; average of 1.1 discrepancies per patient). Compared with a historical cohort of 84 veterans, more CLC C-TraC patients received a post-discharge call within 7 days (82.9% vs 61.9%; P = .03). There was no difference between rates of attendance to appointments and acute care admissions post-discharge.

CONCLUSIONS AND IMPLICATIONS

We successfully adapted the C-TraC transitional care protocol to the VA subacute care setting. CLC C-TraC resulted in increased post-discharge follow-up and intensive case management. Evaluation of a larger cohort to determine its impact on clinical outcomes such as readmissions is warranted.

Connect-Home transitional care from skilled nursing facilities to home: A stepped wedge, cluster randomized trial

BACKGROUND

Skilled nursing facility (SNF) patients and their caregivers who transition to home experience complications and frequently return to acute care. We tested the efficacy of the Connect-Home transitional care intervention on patient and caregiver preparedness for care at home, and other patient and caregiver-reported outcomes.

METHODS

We used a stepped wedge, cluster-randomized trial design to test the intervention against standard discharge planning (control). The setting was six SNFs and six home health offices in one agency. Participants were 327 dyads of patients discharged from SNF to home and their caregivers; 11.1% of dyads in the control condition and 81.2% in the intervention condition were enrolled after onset of COVID-19. Patients were 63.9% female and mean age was 76.5 years. Caregivers were 73.7% female and mean age was 59.5 years. The Connect-Home intervention includes tools, training, and technical assistance to deliver transitional care in SNFs and patients' homes. Primary outcomes measured at 7 days included patient and caregiver measures of preparedness for care at home, the Care Transitions Measure-15 (patient) and the Preparedness for Caregiving Scale (caregiver). Secondary outcomes measured at 30 and 60 days included the McGill Quality of Life Questionnaire, Life Space Assessment, Zarit Caregiver Burden Scale, Distress Thermometer, and self-reported number of patient days in the ED or hospital in 30 and 60 days following SNF discharge.

RESULTS

The intervention was not associated with improvement in patient or caregiver outcomes in the planned analyses. Post-hoc analyses that distinguished between pre- and post-pandemic effects suggest the intervention may be associated with increased patient preparedness for discharge and decreased number of acute care days.

CONCLUSIONS

Connect-Home transitional care did not improve outcomes in the planned statistical analysis. Post-hoc findings accounting for COVID-19 impact suggest SNF transitional care has potential to increase patient preparedness and decrease return to acute care.

GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials

BACKGROUND AND OBJECTIVES

Generalized estimating equations (GEE) are used to analyze correlated outcomes in marginal regression models with population-averaged interpretations of exposure effects. Limitations of popular software for GEE include: (i) user choice is restricted to a small set of within-cluster pairwise correlation (intra-class correlation; ICC) structures; and (ii) inference on ICC parameters is usually not possible because the precision of their estimates is not quantified. This is important because ICC values inform the design of cluster randomized trials. Beyond the standard GEE implementation, use of paired estimating equations (Prentice 1988) provides: (i) flexible specification of models for pairwise correlations and (ii) standard errors for ICC estimates. However, most GEEs give biased estimates of standard errors and correlations when the number of clusters is small (roughly, ≤40). Consequently, there is a need for software to provide GEE analysis with finite-sample bias-corrections.

METHODS

The SAS macro GEEMAEE implements paired estimating equations to simultaneously estimate parameters in marginal mean and ICC models. It provides bias-corrected standard errors and uses matrix-adjusted estimating equations (MAEE) for bias-corrected estimation of correlations. Several built-in correlation matrix options, rarely found in software, are offered for multi-period, cluster randomized trials and similarly structured longitudinal observational data structures. Additional options include user-specified correlation structures and deletion diagnostics, namely Cooks' Distance and DBETA statistics that estimate the influence of observations, cluster-periods (when applicable) and clusters.

RESULTS

GEEMAEE is illustrated for a binary and a count outcome in two stepped wedge cluster randomized trials and a binary outcome in a longitudinal study of disease surveillance. Use of MAEE resulted in larger values of correlation estimates compared to uncorrected estimating equations. Use of bias-corrected variance estimators resulted in (appropriately) larger values of standard errors compared to the usual sandwich estimators. Deletion diagnostics identified the clusters and cluster-periods having the most influence.

CONCLUSIONS

The SAS macro GEEMAEE provides regression analysis for clustered or longitudinal responses, and is particularly useful when the number of clusters is small. Flexible specification and bias-corrected estimation of pairwise correlation parameters and standard errors are key features of the software to provide valid inference in real-world settings.

Power analyses for stepped wedge designs with multivariate continuous outcomes

Multivariate outcomes are common in pragmatic cluster randomized trials. While sample size calculation procedures for multivariate outcomes exist under parallel assignment, none have been developed for a stepped wedge design. In this article, we present computationally efficient power and sample size procedures for stepped wedge cluster randomized trials (SW-CRTs) with multivariate outcomes that differentiate the within-period and between-period intracluster correlation coefficients (ICCs). Under a multivariate linear mixed model, we derive the joint distribution of the intervention test statistics which can be used for determining power under different hypotheses and provide an example using the commonly utilized intersection-union test for co-primary outcomes. Simplifications under a common treatment effect and common ICCs across endpoints and an extension to closed-cohort designs are also provided. Finally, under the common ICC across endpoints assumption, we formally prove that the multivariate linear mixed model leads to a more efficient treatment effect estimator compared to the univariate linear mixed model, providing a rigorous justification on the use of the former with multivariate outcomes. We illustrate application of the proposed methods using data from an existing SW-CRT and present extensive simulations to validate the methods.

A general method for calculating power for GEE analysis of complete and incomplete stepped wedge cluster randomized trials

Stepped wedge designs have uni-directional crossovers at randomly assigned time points (steps) where clusters switch from control to intervention condition. Incomplete stepped wedge designs are increasingly used in cluster randomized trials of health care interventions and have periods without data collection due to logistical, resource and patient-centered considerations. The development of sample size formulae for stepped wedge trials has primarily focused on complete designs and continuous responses. Addressing this gap, a general, fast, non-simulation based power procedure is proposed for generalized estimating equations analysis of complete and incomplete stepped wedge designs and its predicted power is compared to simulated power for binary and continuous responses. An extensive set of simulations for six and twelve clusters is based upon the Connect-Home trial with an incomplete stepped wedge design. Results show that empirical test size is well controlled using a t-test with bias-corrected sandwich variance estimator for as few as six clusters. Analytical power agrees well with a simulated power in scenarios with twelve clusters. For six clusters, analytical power is similar to simulated power with estimation using the correctly specified model-based variance estimator. To explore the impact of study design choice on power, the proposed fast GEE power method is applied to the Connect-Home trial design, four alternative incomplete stepped wedge designs and one complete design.

Adapting the Connect-Home transitional care intervention for the unique needs of people with dementia and their caregivers: A feasibility study

AIMS

After leaving skilled nursing facilities (SNF), 20% of people with dementia (PWD) are re-hospitalized within 30 days. We assessed fidelity, acceptability, preliminary outcomes, and mechanisms of the Connect-Home ADRD transitional care intervention.

DESIGN

A feasibility study of Connect-Home ADRD.

METHODS

The Connect-Home intervention was adapted for dementia-specific needs. PWD and caregiver dyads in 2 SNFs received transitional care. Data sources included interviews with PWD and caregivers and a review of health records.

RESULTS

19 of 34 eligible dyads (56%) were enrolled. The intervention was feasible (components delivered for >84% of dyads) and acceptable (dyads rated it very helpful and not difficult to use). Connect-Home ADRD adaptations included in-home support to manage symptoms of dementia and unplanned events, such as transition to hospice.

IMPACT

Connect-Home ADRD is feasible, acceptable, and merits future research as an intervention to reduce rapid return to acute care following SNF stays.

Unique Care Needs of People with Dementia and Their Caregivers during Transitions from Skilled Nursing Facilities to Home and Assisted Living: A Qualitative Study

OBJECTIVES

The purpose of the study was to describe unique care needs of people with dementia (PWD) and their caregivers during transitions from skilled nursing facilities (SNF) to home.

DESIGN

A qualitative study using focus groups, semistructured interviews, and descriptive qualitative analysis.

SETTING AND PARTICIPANTS

The study was set in one state, in 4 SNFs where staff had experience using a standardized transitional care protocol. The sample included 22 SNF staff, 4 home health nurses, 10 older adults with dementia, and their 10 family caregivers of whom 39 participated in focus groups and/or interviews.

METHODS

Data collection included 4 focus groups with SNF staff and semistructured interviews with home health nurses, SNF staff, PWD, and their family caregivers. Standardized focus group and interview guides were used to elicit participant perceptions of transitional care. We used the framework analytic approach to qualitative analysis. A steering committee participated in interpretation of findings.

RESULTS

Participants described 4 unique care needs: (1) PWD and caregivers may not be ready to fully engage in dementia care planning while in the SNF, (2) caregivers are not prepared to manage dementia symptoms at home, (3) SNF staff have difficulty connecting PWD and caregivers to community supports, and (4) caregivers receive little support to address their own needs.

CONCLUSIONS AND IMPLICATIONS

Based on findings, recommendations are offered for adapting transitional care to address the needs of PWD and their caregivers. Further research is needed (1) to confirm these findings in larger, more diverse samples and (2) to adapt and test interventions to support successful community discharge of PWD and their caregivers.

El papel de la evaluación en la enfermería de práctica avanzada gerontológica basada en competencias

RESUMEN El envejecimiento de la población es un desafío a los sistemas de salud y requiere que los profesionales de enfermería en gerontología de práctica avanzada (EGPA) aborden los requisitos específicos y complejos del cuidado de los adultos mayores. La EGPA pone en ejecución prácticas basadas en evidencia dirigidas a pacientes y familiares para la promoción y protección de la salud, prevención de enfermedades, así como su recuperación y rehabilitación. En la gerontología de práctica avanzada basada en competencias, la evaluación integral es esencial para la puesta en práctica de un plan de cuidados. En este ensayo teórico reflexionamos sobre el papel de la evaluación en la enfermería en gerontología de práctica avanzada basada en competencias. Desde nuestro punto de vista, la valoración gerontológica hacia una práctica excelente debe ser integral, multidimensional, interdisciplinar y planificada. La EGPA debe abarcar competencias efectivas en habilidades clínicas y prácticas del cuidado; alfabetización en salud; cuidado colaborativo; gestión de sistemas para la continuidad del cuidado; ética, defensa y agencia moral; y la práctica a través de la investigación basada en la evidencia. Los modelos gerontológicos de cuidado y las competencias de la EGPA sirven como marco de su práctica, mientras que la evaluación es fundamental para un cuidado accesible a los adultos mayores.

The role of assessment in competence-based gerontological advanced practice nursing

ABSTRACT Population aging challenges healthcare systems, requiring gerontological advanced practice nurses (GAPN) to address specific and complex care requirements of older adults. GAPN implement evidence-based practices directed to patients and families, focusing on health promotion and protection, disease prevention, recovery, and rehabilitation. In competence-based gerontological advanced practice, comprehensive geriatric assessment is essential for implementing the care plan. In this theoretical essay we reflect about the role of assessment in competence-based advanced nursing practice directed to the care of older adults. From our perspective, geriatric assessment for a high-quality practice must be comprehensive, multidimensional, interdisciplinary, and planned. GAPN must have solid competencies for clinical skills and caring practices; education for health literacy; collaborative care; system management for continuity of care; ethics, advocacy, and moral agency; and evidenced-based practice inquiry. Gerontological models of care and GAPN competencies serve as frameworks to guide practice while assessment is fundamental for providing age-friendly care to older adults.

Implementing transitional care in skilled nursing facilities: Evaluation of a learning collaborative

Proctor's Framework for Implementation Research describes the role of implementation strategies and outcomes in the pathway from evidence-based interventions to service and client outcomes. This report describes the evaluation of a learning collaborative to implement a transitional care intervention in skilled nursing facilities (SNF). The collaborative protocol included implementation strategies to promote uptake of a transitional care intervention in SNFs. Using RE-AIM to evaluate outcomes, the main findings were intervention reach to 550 SNF patients, adoption in three of four SNFs that expressed interest in participation, and high fidelity to the implementation strategies. Fidelity to the transitional care intervention was moderate to high; SNF staff provided the five key components of the transitional care intervention for 64-93% of eligible patients. The evaluation was completed during the COVID-19 pandemic, which suggests the protocol was valued by staff and feasible to use amid serious internal and external challenges.