Talk to the Veterans Crisis Line now
U.S. flag
An official website of the United States government

Health Services Research & Development

Go to the ORD website
Go to the QUERI website
HSRD Conference Logo



2023 HSR&D/QUERI National Conference Abstract

Printable View

1170 — Nursing Unit Design and Hospital Falls

Lead/Presenter: Stephen Luther,  Research Service, James A. Haley Veterans Hospital
All Authors: Luther SL (Research Service, James A. Haley Veterans Hospital), Ahrentzen S (Shimberg Center for Housing Studies, College of Design, Construction and Planning, University of Florida, Gainesville, FL) Kazemzadeh M (Shimberg Center for Housing Studies, College of Design, Construction and Planning, University of Florida, Gainesville, FL) Alliance S (Research Service, North Florida/South Georgia Veterans Health System, Gainesville, FL) Hahm B (Research Service, James A Haley Veterans Hospital, Tampa, FL) Powell-Cope G (Research Service, North Florida/South Georgia Veterans Health System, Gainesville, FL) Radwan C (Research Service, James A Haley Veterans Hospital, Tampa, FL) Fischer GM (Office of Facilities Standards Service/Office of Facilities Planning, Office of Construction and Facilities Management, Department of Veterans Affairs, Washington, DC) Shorr RI (Geriatric Research Education and Clinical Centers, North Florida/South Georgia Veterans Health System, Gainesville, FL)

Objectives:
1) Identify Veterans Health Administration’s (VHA) hospital medical/surgical units with higher- versus lower- than expected risk adjusted fall rates. 2) Quantify associations between hospital unit design factors and risk adjusted fall rates.

Methods:
Fall rates for medical/surgical units with average daily censes > 5 from 125 facilities were obtained from VHA’s Inpatient Evaluation Center between fiscal years (FY) 2013-2017 and matched to cooperate data warehouse (CDW) data. Units with fewer than 48 months of data available (n = 30) or more that 5 months with missing fall rates (n = 11) were eliminated resulting in a total of 201 units from 108 facilities for analysis. Distribution of fall rates across the study period were found to be highly stable, therefore monthly values were collapsed to a single mean value across all the five years for each unit. Mixed model regression analyses were conducted with facility treated as a random effect and fixed effects including patient bed days of care per month (patients age >75, male, Nosos percentile > = 25, Nosos percentile > = 75, surgical admissions, and CNS medication use), nursing hours of care per month and Facility Complexity level. After excluding outliers the final regression results were based on data from 184 units. Facility and nursing managers in the 25 units with the highest and lowest (n = 50) risk-adjusted fall rates were surveyed to obtain information about the units. The facility manager survey included questions about interior of individual rooms, types of flooring, etc. The nursing manager survey included the actual floor plan of the unit for reference and questions about factors that might not be evident in the floor plans including the location of temporary equipment and which room(s) were most and least preferred for high fall risk patients.. Floor plans were analyzed using Depthmap, a software program to quantify spatial relationships such as accessibility and visibility.

Results:
The mean fall rate for the higher- than- expected (higher) group was 6.56 (SD = 1.33) falls and for the lower-than-expected (lower) group was 3.62 (SD = 0.86). Nursing manager surveys were collected from 47 facilities (25 higher and 23 lower). Most nurse managers (41, 87.2%) reported having preferred rooms on the unit for high risk fall patients. The most common characteristics of the preferred room included location near nursing station (n = 31, 65.9%) and visibility into the room (8.5%). Comparison of survey and Depthmap analysis results comparing high and low fall risk groups will be provided.

Implications:
Combining the data obtained from the combination of big data, surveys and the Depthmap analyses of unit floor plans provide new information about the impact unit design factors on hospital falls.

Impacts:
This study represents the first time that the components of unit design were examined as contributors to fall rates across a large hospitals system. Results provide insights upon which to build improved hospital fall prevention programs and improved hospital design as the VA continues to expand, renovate, and improve its overall infrastructure.