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About
This project will evaluate three different strategies to get research findings back to managers of care units in nursing homes. Feedback will be provided in a timely and effective way so that it results in improvements in organizational context (modifiable features of the care unit work environment, such as Formal Interactions, Informal Interactions, Social Capital or Slack Time), quality of care providers' work life (e.g., burnout, job satisfaction, general health) and quality of care. Three feedback packages will be tested to determine the strategy that is most effective at fostering improvements and is also cost-effective. The project will be carried out in nursing homes in Alberta and British Columbia. The information developed will contribute to better care for Canadian seniors who spend their final years in a nursing home.
Full description
Background:
The purpose of this project is to systematically evaluate a tailored intervention targeting the leaders of clinical microsystems (care units) in residential long term care (nursing home - NH) settings. The intervention is designed to feedback performance data for improvement. This project is a key element of a long term program of research (Translating Research in Elder Care - TREC) focused on advancing knowledge translation science. TREC's goal is to improve quality of care, and in so doing, improve quality of life for older adults in NHs and work life for their care providers. TREC specifically focuses on the important role of organizational context (modifiable elements of the work environment) at the clinical microsystem (clinical unit) level in NHs.
Aims:
Design: Pragmatic, three-arm, parallel, cluster-randomized trial; stratified permuted block randomization; baseline assessment, 1-year intervention period, post-intervention assessment and 1-year long-term follow up. NHs will be randomly assigned to Standard Feedback (SF), Basic Assisted Feedback (BAF) or Enhanced Assisted Feedback (EAF).
Setting: Stratified (region by size by operator) random sample of 67 eligible NHs from four regions in two provinces: Alberta (Edmonton, Calgary) and British Columbia (Fraser Health, Interior Health). Facilities participate in a longitudinal observational study (part of TREC) that generates a rich resident, staff, unit, and facility level database.
Random assignment: The cohort of 67 NHs is recruited. All sites have agreed to and expect standard feedback. 22 facilities (60 eligible units) were randomly assigned to SF, 22 facilities (70 eligible units) to BAF, and 23 facilities (73 eligible units) to EAF. Facilities assigned to BAF or EAF will be approached and offered additional feedback. Managers will be explained the specific extra feedback (treatment) they will receive, but they will be blinded to group allocation.
Sample: Target of the intervention are managers of the care units within the NHs. To avoid contamination effects, randomization will be done at the facility level, with all included unit managers of the same facility receiving the same feedback intervention. To determine sample size a computer simulation-based sample size approach was adapted that accounted for multiple repeated measures in three study arms, and the complex nested structure (time points nested within each care unit, and units clustered within facilities). Power and sample size were estimated based on a mixed-effects regression model. Using data from the previous phase of TREC (2007-2012) the required parameters to be entered into the model were estimated. Assumptions were that SF will increase the primary outcome (Formal Interactions [FI] score) by 0.2, BAF will increase the FI score by 0.4, and EAF will increase the FI score by 0.6. With an assumed power of 0.90, a significance level of 0.05 and an attrition rate of 25%, a total of 144 care units will be needed (48 NHs with an average number of three units or 72 NHs with an average number of two units).
Intervention:
All three groups will receive a face-to-face Dissemination Workshop (feedback of research data on modifiable aspects of the care unit context). The SF group will receive no additional intervention. The BAF and EAF arms will receive an additional face-to-face Goal Setting Workshop and two Support Workshops at six month intervals. Support Workshops will be virtual in the BAF arm and face-to-face in the EAF arm. In addition the EAF arm will receive on-demand email and phone support. Feedback will include data about four aspects of organizational context that are routinely measured in TREC with the validated Alberta Context Tool (ACT). Four of ten ACT concepts were selected for specific focus: 1) the number of Formal Interactions (FIs) care aides have with other providers and with patients/families; 2) the amount of Slack Time care aides have; 3) Evaluation (unit feedback) Practices, and 4) Social Capital. The intervention is designed to improve performance on these aspects of context. Intervention target is the clinical microsystem (clinical unit) managerial team within NHs: unit care managers and the director of care.
Primary outcome: Formal Interactions (FI), defined as formal exchanges through scheduled activities that can promote the transfer of knowledge (details see outcomes section). Previous research in TREC (2007-2012) clearly suggested that some context areas on the ACT have the potential to exert greater impact on quality of care and implementation of change. Of these, FI has the greatest single impact. At the microsystem level no unit scored above 1.9 (max. possible score is 4) and the mean was 1.3, leaving substantial room for improvement. The correlation of FI with the overall ACT context score is .5, and combinations of FI plus three additional ACT concepts (Evaluation, Social Capital, Slack Time) increased the correlation to .8. Field surveys suggested that care managers are interested in FI as an actionable concept of facility context and consider it a prime accessible target for action and change. FI constitutes the most actionable, cost-effective, and easy-to-improve context for enhancing quality, since the mechanisms for improvement are readily available. FI makes use of existing resources and requires little investment beyond organizational adaptations (scheduling training or meeting sessions, developing educational materials to disseminate research findings, etc.). Finally and importantly, FI is also a proximal goal. The organizational behavior literature is clear that the goal set cannot be too distal.
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Process evaluations:
Statistical Analysis:
Primary Analysis: To compare the effectiveness of the three feedback interventions in improving the FI score, mixed-effects regression models will be used. The models will account for multiple measures within each unit and clustering of units within facilities. All analyses will be adjusted for the three stratification variables of the TREC facility sample (region, owner-operator model and facility size). Characteristics of units and facilities will be compared using descriptive statistics at baseline. Based on this, models will be adjusted for baseline variables that differ significantly between treatment groups. Data will be assessed whether they meet the assumptions of this model (multivariate normality, linearity, normally distributed, uncorrelated residuals, random effects with mean zero) and models will be adjusted accordingly. Intention-to-treat analysis will be conducted, as this best reflects the pragmatic nature of the study. These results will be compared to an as-treated analysis, which better reflects adherence/non-adherence with the intervention. Reporting of these findings will follow the Consolidated Standards of Reporting Trials (CONSORT) guidelines.
Secondary Analyses: Change of secondary outcomes (resident outcomes, i.e., RAI quality indicators, staff outcomes and organizational variables) will be monitored over time in each study arm, and outcomes will be compared between the three study arms using descriptive statistics, Statistical Process Control methods, and appropriate significance tests (t tests for normally distributed, linear, continuous outcomes; non-parametric tests for variables that don't meet these assumptions; chi tests for categorical outcomes). A dichotomous variable (improved/not improved) will be assigned to each unit in the intervention. Then, using logistic regression with improvement as the outcome the effects of context (using ACT scales), best practice use, and staff characteristics on improvement will be investigated. To this end a reliable classification system for individual control charts was developed.
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119 participants in 3 patient groups
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Data sourced from clinicaltrials.gov
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