Although efficacy trials have identified interventions that reduce adverse outcomes such as falls in nursing home (NH) residents, attempts to translate those interventions into practice using current standard of care quality improvement (QI) techniques have not been successful. Using a complexity science framework, our previous RO1 has shown that low connection, information flow, and cognitive diversity among NH staff explains much of the poor quality of care delivered for complex problems such as falls. Our pilot test of """"""""CONNECT"""""""", a multi-component intervention that encourages staff use simple strategies to make new connections with others, enhance information flow, and use cognitive diversity, demonstrated that staff can learn to improve the density and quality of their interactions, and that this change in behavior is associated with a trend to lower fall rates. We hypothesize that higher levels of connection, information flow and cognitive diversity fostered in the CONNECT Intervention are necessary before any QI intervention for a complex geriatric problem such as falls can be successful. This 5-year study will use a prospective, cluster-randomized, outcome assessment blinded design, with NHs (n=16) randomized to either CONNECT and a standard falls QI program (CONNECT + FALLS) or FALLS alone. We estimate that 800 residents and 576 staff members will participate.
Specific aims are to, in nursing homes: 1) Compare the impact of the CONNECT intervention plus a falls reduction QI intervention (CONNECT+FALLS) to a falls reduction QI intervention (FALLS) on fall risk reduction indicators (orthostatic blood pressure, sensory impairment, footwear appropriateness, gait;assistive device;toileting needs, environment, and psychotropic medication);2) Compare the impact of CONNECT+FALLS to FALLS alone on fall rates and injurious falls, and determine whether these are mediated by the change in fall risk reduction indicators;3) Compare the impact of CONNECT+FALLS to FALLS alone on complexity science measures (communication, participation in decision making, local interactions, safety climate, staff perceptions of quality) and determine whether these mediate the impact on fall risk reduction indicators and fall rates and injurious falls. Cross-sectional observations of complexity science measures are taken at baseline, at 3 months, at 6 months, and at 9 months. Resident fall risk reduction indicators, fall rates, and injurious falls are measured for the 6 months prior to the first intervention and the 6 months after the final intervention is completed. Fall risk reduction indicators are the primary outcome. Secondary outcome measures include fall rates, injurious falls, and complexity science measures (communication, participation in decision making, local interactions, safety climate, staff perceptions of quality). Analysis will use a 3-level mixed model to account for the complex nesting of patients and staff within nursing homes, and to control for covariates associated with fall risk, including baseline facility fall rates and staff turnover rates.

Public Health Relevance

In order to promote the health of the frail NH population, it is essential to identify interventions to improve the translation of research advances into actual practice. The CONNECT intervention integrates behavioral and complexity science with principles of health services research, and has the potential to improve care in NHs for many complex medical and psycho-social problems among frail older adults.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Research Project (R01)
Project #
3R01NR003178-11S1
Application #
8732815
Study Section
Health Services Organization and Delivery Study Section (HSOD)
Program Officer
Mccloskey, Donna J
Project Start
1994-09-01
Project End
2016-06-30
Budget Start
2013-09-26
Budget End
2014-06-30
Support Year
11
Fiscal Year
2013
Total Cost
$74,831
Indirect Cost
$27,168
Name
Duke University
Department
Type
Schools of Nursing
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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