1. Evidence-based Practice Fall Risk Assessment Tool Validation
Figure 1: slip and fall warning signs (SaferAmerica, 2015)
Presented by the 7th floor EBP Team: Penny Amornvut, Tracey-Anne Anacleto, Johnathan Avilar, Chris Bower-Fjellstrom, Leo Castelo, Stephanie Ferrero, Jaye Galiza, Tony Ingkiriwang,
Casey King, Megan Lang, Antora Majumder, Steven Watson, Monique Yoeliko

2. Objectives
At the conclusion of this discussion, the participant will be able to:
Utilize evidence based practice to validate which fall risk assessment tool is a better predictor of falls for the acute adult inpatient care setting

3. EBP Journey Team Selection Training session
ICU ( 7100 and 7200)
Acute Intermediate (7300)
Training session
8 hour EBP Education Session
Scheduled meetings every 6 weeks
Nurses from the Environment and equipment QI group were asked to volunteer to participate in this project
When the team was formed, two 4-hour meetings were dedicated to educating the RNs about EBP literature review and protocol development
Team met every 6 weeks

4. EBP Team Nurse led Interprofessional team Multidisciplinary Support
CTICU RN
CCU RN
Cardiac Acute/Intermediate Inpatient RN
Clinical nurse educator-Clinical Nurse Specialist
Director of Nursing Research
Multidisciplinary Support
Physical therapists
Occupational therapists
Patient Care Assistants
Cardiac Service Line Director

5. Asking the Clinical Question

6. PICO Question Population: All adult inpatients
Intervention: Compare multiple fall risk assessment scales
Comparison: Morse fall risk assessment tool with Hester-Davis fall risk assessment tool
Outcome: Validating a more effective tool for the assessment of an inpatient’s fall risk and developing nursing interventions associated to the assessed fall risk

7. Adult Inpatient Population
Patient Diagnoses
S/p cardiac, pulmonary and vascular surgery
CHF, STEMI, heart transplant
Cardiac observation, general surgery
Patient Demographics
Adult > 18 years of age

8. Current Practice Findings
We are currently using Morse fall risk assessment tool, which is completed once a shift
Patients are highly variable and the Morse fall risk assessment tool is a static assessment that does not capture change in patient condition/treatment
This lack of variability that occurs with the use of the Morse scale decreases nursing sensitivity to changes in patients’ conditions, that may change their fall risk

9. Current Practice Findings
The Morse scale is not designed for the inpatient population
The Morse scale does not address many fall risk factors that inpatient populations are associated with
There is also an issue with the current education regarding a patient’s potential fall risk
Patients are not aware they are a fall risk and there is little communication/education of their fall risk to patient / patient families

10. Current Practice Findings
Survey question asked: Do you feel that the Morse Fall Scores accurately predicts fall risk? With 1 (not accurate at all) to 5 (very accurate)

11. Current Practice Findings
Survey question asked: When speaking to your patients and families, do you use the phrase "you are at RISK for falling“?

12. What Did the Literature Tell Us?

13. Critically Appraise the Evidence
Individual Review
Group review
Assess level of evidence
Narrow focus
Articles were searched for through (???? Ask patti)
- Each group member was asked to read each article and complete LLUMC Evidence-based tools appendix forms A-I
- We had group discussions about article findings and compiled all individual completed appendix forms to group the information

14. Fall Risk Factors
Intrinsic factors are factors related to the patient’s physiology. These can include age- related changes (Pearson et. Al, 2011).
Examples include: decreased vision and mobility/gait issues
urinary incontinence
chronic illness
confusion
Extrinsic factors are related to the physical environments.
These can include poor conditions of floor surfaces or the inappropriate use, or lack of, assistive devices (Pearson et. Al, 2011).
Falls can occur due to both intrinsic factors and extrinsic factors

15. Types of Falls
Unanticipated physiological falls (8% of fall occurrence):
Unanticipated physiological falls are physiological falls that cannot be predicted before their first occurrence (Feil et. Al, 2012)
Anticipated physiological falls (78% of fall occurrence):
Anticipated physiological falls are physiological falls that can be predicted in patients who display clinical signs that contribute to increased fall risk (Feil et. Al, 2012)
Accidental falls: (14% of fall occurrence):
Accidental falls are falls that occur due to accidents that are often attributed to environmental cause (e. g. wet floor, cables, cords) (Feil et. Al, 2012).

16. Available Options for Fall Risk Assessment Tools
Morse Fall Risk Scale (MFRS)
St. Thomas Risk Assessment Tool in Falling Elderly In-patient (STRATIFY),
Hendrich II Fall Risk Model comparison,
Johns Hopkins Fall Scale
Hester Davis Scale (HDS)
Through the literature search, we found evidence based information on these 5 different fall risk tools.
Based on the literature and what we found regarding fall risks and the other tools, we chose to evaluate the effectiveness of the HDS in determining fall risks

17. Fall Risk Assessment Tool Selection
Which tool should we choose?
How will we know it’s the right tool for our hospital?
What fall risk factors is the tool assessing?
In searching for the evidence for the tool, we looked into the sensitivity and specificity. Sensitivity
Tells you how well the tool to correctly assess the risk of patient for falling
Specificity
Tells you how well the tool to correctly assess the risk of patient for not falling down
We need a tool that has high sensitivity and specificity
There’s no a perfect tool exist. No tool with 100% sensitivity and 100% specificity
How adaptable and personalized the tool is to our population?

18. Why Hester Davis Scale?

19. Hdnursing.com

21. Hester Davis Scale (HDS)
9 factor scale with scores ranging from (Hester et. Al, 2013).
Each factor is scored 0-4, except for Age (0-3)
Age
Last known fall
Mobility
Toileting
Mental status / LOC / awareness
Communication / sensory
Behavior
Medication
Volume / electrolyte status

22. Hester Davis Scale (cont.)
Each factor/Sub-category has multiple items to choose from
More than 1 item can be chosen from each category.
Then a total score is calculated.
A high score in any Sub-category may also trigger interventions , even if the total score is low.

23. Fall Prevention Measures/Interventions
- Based on the literature, we chose several interventions to utilize depending on which category of fall risk a patient was scored under

24. Low Risk Fall Prevention Measures
Ensure a clutter free room
Re-orient patient as needed to time and place
Place in bed designed to prevent falls
Keep side rails up
Make sure bed brakes on
Place call light and frequently needed items in reach
Encourage patient and family to call for assistance
Provide non-skid footwear
Communicate fall risk with staff with every handoff
Answer call light promptly
Ensure there is adequate lighting especially at night
These are the low fall risk fall prevention. Majority of them are already in LLEAP

25. Moderate Risk Fall Prevention Measures
Offer frequent toileting
Monitor / assist patient in ADL
Ensure correct fall risk (for patient) on patient whiteboard
All measures included under low fall risk measures
These are the moderate fall risk fall prevention. Majority of them are already in LLEAP

26. High Risk Fall Prevention Measures
Observe closely when using wheelchair or when patient out of bed
Complete hourly rounds
All measures included under both moderate and low fall risk prevention measures
These are the high fall risk fall prevention. Majority of them are already in LLEAP

27. Integrating Evidence With Clinical Practice

28. Protocol Development Identified the problem
Observed and gathered information about the current clinical state and practice
Found the focus of the problem and narrowed down a purpose
Formed assessment bundles that included the use of the HDS
Created a paper tool of the HDS

29. Developed HDS Paper Tool
Suggested interventions by score
Suggested interventions by sub- category
Morse fall risk assessment score comparison

30. Fall Protocol in Practice

31. Protocol in practice Staff education HDS paper tool
Bedside RN roles & responsibilities
Data collection
HDS paper tool revision
Provided inter-shift education presented at pre-shift huddles to 7th floor leadership, RNs, PCAs, and PT/OTs
Created an educational video and more detailed education given during Professional governance meetings.
Integrated the paper tool into the units current practice of assessing patient fall risks
Distributed HDS paper tool at the beginning of the shift (both day and noc)
Bedside RN instructed to complete Morse Fall scale and HDS tool by noon and midnight, for each patient
Completed tool was sent to educator at the end of each shift
Completed tools were compiled into data collection for later analysis
HDS paper tool was revised multiple times during data collection

32. Fall Data Analysis Findings

33. Findings Risk Level according to HDS
% of Patients Morse Fall Risk level vs. HDS Risk level
Low
9% HDS & Morse same score
39% Morse scored Moderate
52% Morse scored as High Risk
Moderate
5% Morse was lower than HDS
65% Morse scored High risk
30 % Morse and HDS scored the same
High
3 % Morse scored lower than HDS (Low risk)
9 % Morse scored lower than HDS (moderate risk)
88% Morse and HDS scored the same
All the fall occurrences data were reviewed. We found that there is a relationship between MFRS and HDS when patients are at high risk for fall; where there is a variation when it comes to low and moderate score. The team validated that the HDS provides a more specific fall risk assessment comparing to MFRS.

34. Findings
In regards to fall occurrences data collecting from July to October 2016 versus 2017, there are no significant findings in the reduction of overall fall occurrences. However, there is a reduction of unanticipated fall as evidenced by RNs were able to use HDS to predict the fall risk and plan for preventative measures. At the beginning of the data collection, RNs were focusing only on how to fill out the form and not using the HDS to make clinical judgment in planning for the preventative measures.

35. Challenges/Barriers Knowledge on Tool Completion
A lot of Data Entry (+ 2,900)
Inconsistency on Tool Completion
Some staff only filled out the form and not consistently implement the preventative measures.

36. Next Steps Present protocol to Adult Quality and Safety
Use data to support use HDS to assess fall risk of patients and make it available to document on LLEAP

37. Questions

38. References
Hester, A. L., & Davis, D. M. (2013). Validation of the Hester Davis scale for fall risk assessment in a neurosciences population. Journal of Neuroscience Nursing, 45,
Michelle Feil, Lae Anne Gardner.(2012) Fall risk assessment: A foundational element of falls prevention programs. Pennsylvania Patient Safety Advisory, 9 (3), p
RUHS. Loma Linda University Medical Center. Retrieved from professionals/medical-education/general-surgery-residency/surgical- services/PublishingImages/hospital%20exteriors/lomaLinda.jpg
SaferAmerica. (2015). How to Prevent Slip and Fall Accidents. Retrieved from content/uploads/2017/11/trip_slip_fall.png
Staggs, V. S., Mion, L. C., & Shorr, R. I. (2014). Assisted and Unassisted Falls: Different Events, Different Outcomes, Different Implications for Quality of Hospital Care. Joint Commission Journal on Quality and Patient Safety / Joint Commission Resources, 40(8), 358–364.
Stephanie S Poe, Maria Cvach, Patricia B. Dowson, Harriet Straus, Elizabeth E. Hill. (2007). The johns Hopkins fall risk assessment tool post implementation evaluation. J Nurse Care Qual, 22 (4), p
Pearson, Karen & Phd, Andrew. (2011). Evidence-based falls prevention in Critical Access Hospitals.

39. References
Chia-Ming Chang, Ming-jen Chen, Chun-yu Tsai, Lun-Hui Ho, Hsing-Ling Hsieh, Yeuk-Lun Chau, Chia-Yih Liu. (2010). Medical conditions and medications as riskfactors of falls in the inpatient older people: A case-control study. Int J Geriatric Psychiatry, 26, p doi: /gps.2569
 Dustin D French, Thomas N. Chirikos, Andrea Spehar, Robert Campbell, Heidi Means, and Tatjana Bulat.(2005). Effect of concomitant use of benzodiazepines and other  drugs on the risk of injury in a veterans population. Drug safety 2005, 28 (12), p doi:
 Joanne Spetz, Diane S. Brown, Carolyn Aydin (2015). The economics of preventing hospital falls. JONA, 45(1), p doi: /nna
Annelies C. Ham. Karin M. A. Swart, Anke W. Eenneman, ET Al. (2014). Medication-related fall incidents in an older, ambulant population: The b-proof study. Drugs  aging, 31, p doi: /s x
 Stephanie S Poe, Maria M. Cvach, Denise G. Gartrell, Batya R. Radzik, Tameria L. Joy. (2005). An evidence-based approach to fall risk assessment, prevention, and management. J Nurs Care Qual, 20 (2), p doi
Jennifer R. Simpson, Laura D. Rosenthal, Ethan U. Cumbler, and David J.Likosky (2013) Inpatient falls: Defining the problem and identifying possible solutions. Part 1: An evidence-based review. The Neurohospitalist, 3(3), p Doi: /
Marta Aranda-Gallardo, Jose M Morales-Asencio, Jose C Canca-Sanchez, Et Al. (2013) Instruments for assessing the risk of falls in acute hospitalized patients: Asystemic review and meta-analysis. Aranda-Gallardo et al. BMC Health Services Research 13,(122), p.1-15
Ballokova A, Peel NM, Fialova D, Scott IA, Gray LC, Hubbard RE. (2014) Use of benzodiazepines and association with falls in older people admitted to hospital: A prospective cohort study. Drugs Aging, 31, (4), p doi: /s
Additional articles read used but not cited in powerpoint? Not sure if we’re supposed to include this