1. Implications for Nursing Practice Design and Methodology
The Influence of Cancer on Falls in Community Dwelling Elderly
Sandra Spoelstra, MSN, RN 1; Charles Given, PhD 2; Barbara Given, PhD, RN, FAAN 1, Alexander von Eye, PhD 3.
Affiliations: Michigan State University of Nursing, 1 College of Nursing, 2 College of Human Medicine , 3 Department of Psychology
Problem Statement
Falls place older adults at risk leading to:
serious injury and functional decline,
hospitalization and institutionalization,
higher healthcare costs, and
decreased quality of life.
-Need: to better understand if the disease or treatment of cancer may contribute to disability, and falls.
-Objective: to examine community dwelling elderly to identify if individuals with a history of cancer fall at a higher rate than those without cancer, and if the occurrence of falls was related to characteristics, symptoms, or functional status data.
Data Analysis
Hierarchical linear modeling :
-within-subjects effects & between-subjects effects,
-with time-independent & dependent co-variables.
2125 or 29%
Results
The mean age was years old & 76.4% were females.
74.3% white and 22% African American.
363 (4.9%) individuals with Cancer had a fall.
The final model predicting falls included: race, gender, ADLs, incontinence, depression, and pain.
Cancer was not a predictor of falls in this population.
5325 or 71%
Conclusion
This study found a high frequency of falls, and suggests a predictive model for fall risk in the vulnerable, community dwelling elderly.
Sample
Community dwelling elderly age >65.
Using the Minimum Data Set for Home Care.
State of Michigan in the year of 2007.
Implications for Nursing Practice
To provide useful approaches for nursing practice to assess those who are at risk for falls,
To allocate valuable nursing time towards those patients who “need” more intense management of preventive measures.
To design effective models of care that will assist elderly cancer survivors.
Design and Methodology
Retrospective, longitudinal cohort study. Secondary data analysis.
Fallers were identified based on:
Diagnosis of cancer,
Age, gender, race and ethnicity,
ADLs and IADLs,
Poor vision, cognitive skill, incontinence, pain, or depression.
967 or 13%
6381 or 87%