1. Marianjoy Rehabilitation Hospital Fall Risk Assessment Tool Project
Donna Pilkington, RN, MSML, CRRN
Kathleen Ruroede, PhD, MEd, RN
Nancy Cutler, RN, MS, CRRN

2. Fall Risk Assessment Literature
Morse Fall Scale
Marianjoy Fall Risk Assessment

3. Morse Fall Scale
The Morse Fall Scale (MFS) is a rapid and simple method of assessing a patient’s likelihood of falling.
The MFS is used widely in acute care settings, both in the hospital and long term care inpatient settings.
It consists of six variables that are quick and easy to score, and it has been shown to have predictive validity and interrater reliability.
A large majority of nurses (82.9%) rate the scale as “quick and easy to use,” and
54% estimated that it took less than 3 minutes to rate a patient.

4. Morse Fall Scale Indicators
1. History of falling with in three months
No = Yes = 25
2. Secondary Diagnosis No = Yes = 15
3. Ambulatory Aid
Bed rest/nurse assist = 0
Crutches/cane/walker =15
Furniture = 30
IV/Heparin Lock No = Yes = 20
5. Gait/Transferring
Normal/bedrest/immobile = 0
Weak = 10
Impaired = 20
6. Mental Status
Oriented to own ability = 0
Forgets limitations = 15

5. Scoring the Morse Fall Scale
Risk Level MFS score Action
________________________________________
No Risk – Basic Care
Low Risk – Standard Fall Precautions
High Risk > High Risk
Precautions

6. Marianjoy Fall Risk Assessment
Altered elimination patterns 10
Unilateral neglect
Impaired cognition
Sensory deficits (hearing,
sight, touch)
Agitation
Impaired mobility
History of previous falls
Impulsiveness
Communication deficits
Lower extremity hemiparesis
Activity intolerance
Episodes of dizziness/seizures 10
Special medications (narcotics, psychotropic, hypnotic, antidepressants etc.)
Diuretics, and drugs that
increase GI motility
Upper extremity paresis
Age greater that 65 or less
than
High Risk: >60 points Place Patient in Caution Club

7. Guiding Question?
Is the Marianjoy Fall Risk Assessment a valid and reliable method for predicting rehabilitation patient fall events if it is properly scored at admission?

8. Description of Research Study
Pilot study of 50 patients
25 patients who had fallen
25 matched patients who had not fallen
Dependent variable fall status
Independent variables
Caution Club status
Admission FIM total score
Modified admission Berg Balance total score
Admission fall risk assessment

9. Pilot Study Results
Patients significantly differed on Berg, FIM, and fall risk assessment scale
Five items found to separate fall groups
History of falls
Unilateral neglect
Episodes of dizziness / seizures
Special medications
Diuretics and drugs that increase GI motility
Sensory deficits

10. Always be alert for a new and creative idea
Always be alert for a new and creative idea... You never know what’s in your grasp

11. Replicated Study with a Larger Sample
2005 data used
Total N = 450 patients included
125 patients with documented fall status
325 patients who had not fallen were randomly selected from dataset
232 patients were on caution club status
218 patients not on caution club status

12. Replicated Study with a Larger Sample
Hypotheses tested
Patients did not significantly differ on fall status for:
Fall assessment
Admission FIM Score
Modified Berg Balance Score
Age

13. Replicated Study with a Larger Sample
Statistical Procedures
Descriptive statistics
Sensitivity and specificity on original scale
Sensitivity and specificity on converted dichotomous scale
Item analysis on dichotomous scale that separate fallers from non-fallers
Total of 9 items discriminate groups

14. Replicated Study with a Larger Sample
Statistical Procedures
Validity procedures using factor analysis (component analysis)
Reliability analysis using Cronbach’s Alpha
Logistic regression to develop predictive model of fall status
Development of new “Caution Club” threshold value – New Threshold Cut Score = > 4

15. Always be ready for any surprises while working on the project

16. Results – Descriptive Statistics

17. Results – Inferential Statistics

18. Results – Inferential Statistics

19. Results – Inferential Statistics
Berg and FIM Significantly Differ, but Age does not significantly differ

20. Results from Item Analysis
Nine items found to discriminate fall groups
History of Falls (Weight 2)
Impulsiveness (Weight 2)
Communication Deficits
Altered Elimination Patterns
Unilateral Neglect
Lower Extremity Hemiparesis
Upper Extremity Hemiparesis
Special Medications
Diuretics and Drugs that Increase GI Mobility

21. Factor Analysis and Reliability
Three Components Extracted
55% Total Explained Variance in Model

22. Logistic Regression Model
R Square Value .253

23. Results from Crosstabulations

24. Sensitivity and Specificity
191 c 23 b
134 a
102
Fall + -
Caution
Club
236 (
a+b )
214
c+d
125
a+c
325
b+d
Sensitivity = a / (a + c) = 102 / 125 = .82
Specificity = d / (b + d) = 191 / 325= .59
False Negative = c / (a + c) = 23 / 125 = .18
False Positive = b / (b + d) = 134 / 325 = .41
PPV = a / (a + b) = 102 / 236 = .43
NPV = d / (c + d) = 191 / 214 = .89

25. Odds and Odds Ratio True Odds Ratio = 6.25
This can be interpreted to mean that a patient who is on caution club status was 6.2 times more likely to incur a fall than a patient who was not on caution club status.

26. Odds and Odds Ratio Relative Risk of a Fall = 3.9
This can be interpreted to mean that the risk of patients on caution club status are 3.9 times more likely to occur than those patients who were not on caution club status.

27. Don't get off strategy and stay focused

28. Conclusions and Recommendations