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NUR702 Review of Literature: Fall Prevention in Older Adults

Review of Literature: Fall Prevention in Older Adults

Falls may cause injuries and death. In patients aged 65 years and older, falls are prevalent in many health care environments (Soffin et al., 2019). Many falls in patients aged 65 and older are due to a lack of proper assessments that identify gait and balance deficiencies, muscle weakness due to the aging process, poor vision, physical decline, environmental hazards, polypharmacy, and other medical conditions (Centers for Disease Control and Prevention [CDC], 2020). When a patient falls, there are economic, social, and health consequences to the patient, the patients’ family, and the health care institution (Burns et al., 2016). Falls have been reported to increase morbidity, mortality, and hospitalizations and falls remain the leading cause of death in the elderly patient aged 65 years and older with an average of 62 deaths per 100,000 older adults (Agency for Healthcare Research and Quality [AHRQ], 2019). 

The Joint Commission’s (TJC, 2015) sentinel event database reports the most common contributing factors to injurious falls in a health care institution is related to inadequate assessment, poor communication, failure to adhere to fall prevention protocols and safe practices: poor staff training, support, staffing skills, lack of leadership and environmental deficiencies. The purpose of this paper is to describe the review of current literature that supports the implementation of a fall prevention education program with the use of a fall assessment tool to reduce falls in older adults.

Literature Search Methods

The literature was  extensively reviewed to answer the clinical question: Does implementing a structured staff educational program using an evidence-based fall screening tool, as part of a multifactorial fall prevention program, reduce falls in patients aged 65 and older residing in an assisted living home compared to pre-implementation fall rates? The literature review included basic and advance search techniques. The techniques used the following criteria for inclusion: Studies within 10 years, English language, and full text.

Sampling Strategies

Numerous databases were searched including the Cumulative Index to Nursing and Allied Health Literature plus (CINAHLPlus), Google Scholar, PubMed, Medline (through EBSCO), and the Cochrane Database of Systematic Reviews. The search terms and phrases included assisted living facilities, fall prevention, falls in older adults, resident falls, falls in adults 65and older, fall risk tool,  “Morse Fall Scale”, “STEADI toolkit”, staff education, fall assessment, and fall prevention strategies. The Boolean terms AND and OR were also used for the literature selection. Using MeSH, the terms assisted living home(s), community dwelling(s), and elderly residential home(s) were used (Melnyk & Fineout-Overholt, 2019).

Inclusion and Exclusion Criteria

The literature was appraised to yield high-level publications including evidence levels I-VI. Articles related to the clinical problem were kept, and studies that were not in English, were on pediatric falls, or falls in patient less than 65 years old were excluded as that is not the focus of this project’s population. Peer-reviewed publications published between 2012-2022, including primary original research, were included to ensure relevance to the clinical problem (see Appendix A)

Literature Review Findings

A good fall prevention program requires the participation and collaboration of a multidisciplinary team (AHRQ, 2019). For clinical evaluation, treatment, and prevention of falls, the US Preventative Services Task Force (USPSTF, 2018) also advocated a multi-factor team approach. Most  fall events happen in elderly patients who are on multiple psychoactive medications, such as benzodiazepines, or are frail due to poor balance, limited mobility, and/or weakness  (Nguyen et al., 2020; USPSTF, 2018). Fall prevention has been significantly researched  which led to multiple organizations developing fall prevention tools and algorithms. For instance, the Centers for Disease Control and Prevention (CDC, 2021) have created tools/algorithms that healthcare clinicians may implement into their regular practices to assist in detecting individuals at risk of falling.

Study One: Spano-Szekely et al. 

                 Spano-Szekely et al. (2019) performed a study to investigate the efficacy of an intervention for preventing falls in elderly individuals in an acute care setting. The researchers collected data on patient falls that occurred in a 245-bed Magnet-designated and Planetree community hospital over a six-month timeframe to determine the efficacy of applying a new fall risk assessment. The hospital’s falls rates were higher than the national benchmark of 3.5-5.0. By incorporating a multifactorial approach, the program effectively reduced falls rates in this hospital by 54% and the cost of sitter usage was reduced by 72%. 

Study Two: Stevens et al.

   Stevens et al. (2017) conducted a study on fall interventions. The STEADI toolkit was used in a study in Broome County in New York which has a population of 200,600 due to its  high falls rates in adults aged 65 years and older. The trial included 500 doctors and took place in 60 locations, including 29 clinical sites. The intervention was to incorporate the STEADI tool into routine practice assessments using the electronic health record (EHR). Nurses screened all patients by first determining whether the individual had two or more falls in the preceding twelve months, or had one fall in the preceding twelve months, had one fall in the preceding twelve months with gait or balance impairments, or was presenting with an acute injury following a recent fall. If this screening was positive, the person was deemed at risk of falling, then the nurse would evaluate the patient using the Time Up and Go (TUG) Test.  The individuals aged  65 to  85 who took 12 or more seconds, and  those aged  85 and older who took 15 or more seconds, failed the TUG and were considered to be high risk for falling.  The practices saw a total of 10,702 older patients, of which 8457 patients (79%) were screened for fall risk with 1534 (18.1%) screening positive. Of the  1534 patients who screened positive, 791 (51.6%) completed a TUG test and 359 (45.4%) received a failing score. Of note, 385 (25.1%) were not screened due to mobility  limitations. This study is pertinent to this proposed project as it used a validated tool for screening individuals within an age group that matches the population of interest in this project. . This project’s intervention will use an evidence-based fall reduction tool and staff education to screen patient at risk for falling as part of a multidisciplinary fall reduction program. This study demonstrated that  using an evidence-based fall screening tool can identify patients at risk for falling.

Study Three: Lohman et al.

Lohman et al. (2017) conducted a cohort study that evaluated the predictive validity of the STEADI toolkit by estimating mortality due to falls and the fall risk category. The population studied were adults aged 65 and older living in the U.S. The sample size was 7,392 adults who were categorized as having low, moderate, or high fall risk according to the STEADI algorithm. As individuals were classified as having a high or moderate risk of falling, their risk of falling increased by roughly 2.62 and 4.76, respectively, when compared to those classified as having a low risk of falling. Additionally, those at high risk were recognized as being at risk for numerous falls. The research established that the STEADI tool is a reliable predictor of future falls. 

Study Four: Strini et al.

Strini et al. (2021) performed a comprehensive assessment of numerous evidence-based fall risk measures from multiple studies with most being prospective cohort studies examining an instruments' validity across different environments. Additionally, retrospective, descriptive, and methodological studies, and systematic reviews were considered. The scales were examined using a variety of demographic characteristics. The authors assessed 38 fall screening instruments, but for the sake of this project, those considered will use patients aged 65 years and older, as well as those that are utilized in community or assisted living facilities, as well as inpatient settings. International Falls Efficacy Scale (FES-I). In the literature, the FES-I scale is the most often used measure for assessing fear of falling in persons aged 65 and older. This instrument has 16 daily living activities, and the individual rates their level of fear of falling when performing them. The Timed Up and Go (TUG) test is a simple and effective method for determining a patient's mobility capability, dynamic balance, and strength. The tools have been used in a variety of contexts, including acute care hospitals, the community, and with persons who have Parkinson's disease or other mental disorders. It accurately predicts falls in fragile patients, but its usefulness diminishes when applied on those with strong functional mobility. The tool is relevant to the proposed project since the majority of persons residing in assisted living facilities are frail. A multidisciplinary team developed and validated the Falls Risk for Older People-Community Setting Screening Tool (FRHOP Com Screen). The Thai version of the scale revealed a sensitivity of 57% and a specificity of 68%, respectively. The research is significant to the proposed project since it used an evidence-based screening tool to accurately identify people at risk of falling.

Chosen Intervention: Reinoso et al. 

Reinoso et al. (2018) conducted a study on adults aged 65 years and older who were community dwellers. The aim was to reduce falls by implementing a multifactorial fall reduction program using the Stopping, Elderly, Accidents, Death, Injuries (STEADI) toolkit. Evidence suggests that most fall reduction programs are focused on risk assessment and intervention that reduce fall risk (cite sources). As part of the study, 27 older adults were selected: 18 females and nine males. The mean age of the participants was  74 with a range of 65-95 years of age years. The screening process included a Timed Get Up and Go test, a visual acuity using the Snellen eye chart, and a baseline blood pressure reading. The screening categorized patients according to risk factors such as gait and balance and whether they had more than two falls, or one fall with injury. Fall risk categories were high, moderate, or low-risk. The fall risk assessment results  are as follows:

Table 1

Fall Risk Category and Scoring

Category

High risk 

Number/%

Moderate risk

Number/%

Low risk

Number %

Full Group

3

11%

8

30%

16

59%

Males

1

11%

2

22%

12

67%

Females

2

11%

4

44%

4

44%

The multidisciplinary students who participated in the project reported that they learned about falls while working collaboratively with students in other disciplines and they better understand the role of other disciplines such as physical therapy and public health professionals in screening, assessing, identifying risks, and providing treatment. The patients who participated also reported that they would take the falls risk assessment to their primary care providers. 

The STEADI algorithm was used after the screening as part of a multifactorial fall reduction program. This study is relevant to the project as it mimics the intended intervention and mirrors the population of interest          

Discussion

In summary, the presented evidence-based literature supports the use of a screening tool to identify patients at high risk of falling. The publications included in this review all convey the same message: when patients are tested using the appropriate fall risk measure for their age and setting, the screening tool may identify those who are at an increased risk of falling.

Limitations

Fall prevention has been the focus of extensive research and quality improvement initiatives which have helped identify the critical components of effective fall prevention programs (World Health Organization, 2017). Screening tools are one component of a multifaceted fall prevention program and cannot prevent falls on their own. Prevention measures begin with an assessment of each patient's fall risk. Additionally, there was limited literature that specifically used a fall risk screening tool in the assisted living setting, as most studies were conducted in the hospital and primary care settings. 

Conclusion of Findings

Falls are a common and occasionally deadly occurrence, especially among the elderly. Falls occur at a rate of 3-5 per 1000 bed-days, and according to the Soffin et al. (2019), between 700,000 and 1 million hospitalized patients fall each year. Patients staying in long-term care facilities are also more likely to fall, requiring the implementation of an evidence-based fall screening tool (Mayo Clinic, 2018). Lohman et al. (2017) used the STEADI technique. The STEADI clinical fall instrument has been shown to be valid and reliable in predicting future falls. Additionally, Steven et al. (2017) analyzed patients aged 65 years and older in Broome County, New York, using the STEADI Tool, which is intended to identify persons at risk of falling as part of a multifactorial fall prevention program.

Potential Practice Change

Based on the  literature, a potential practice changes to reduce falls  in the assisted living population would be staff education and the introduction of an evidence-based screening tool using the STEADI toolkit and  algorithm. This intervention is intended to increase staff knowledge, improve patient safety, and reduce falls rates amongst the  facility’s older adult residents. During the resident’s initial visit, they will be screened for falls using a validated tool, and if at risk for falling, a multifactorial fall prevention plan will be initiated to prevent or reduce falls.

Conclusion

The review of the literature supports using a fall risk screening tool as part of a multifaceted fall prevention program may help minimize falls by identifying patients who are at higher risk of falling. When it comes to screening, assessment, risk identification, and treatment, it is critical that various disciplines, such as physical therapy and public health, are involved. For example, the students who worked on the fall reduction project learned about the dangers of falling through collaboration with other students. In order to prevent falls in the senior population, it is vital to collaborate across disciplines, to provide systematic rather than ad hoc patient and staff education, and to develop a customized treatment plan for each individual.

References

Burns, E. R., Stevens, J. A., & Lee, R. (2016). The direct costs of fatal and non-fatal falls among older adults—United States. Journal of safety research, 58, 99-103.

Centers for Disease Control and Prevention. (2020, July 9). Morbidity and Mortality Weekly Report (MMWR) : Trends in Nonfatal Falls and Falls-Related Injuries Among Adults Aged>65 Years- United States, 2012-2018.http://www.cdc.gov Morbidity and Mortality Weeekly Report Trends in Nonfatal Falls and Fall-Related Injuries Among Adults Aged >65 Years- United States, 2012-2018

Centers for Disease Control and Prevention. (2021). Older adult fall prevention: Falls Data. http://www.cdc.gov Older Adult Fall Prevention Falls Data

Gimm, G., & Kitsantas, P. (2016). Falls, depression, and other hospitalization risk factors for adults in residental care facilities. The International Journal of Aging and Human Development, 83(1), 44-62.

Guirguis-Blake, J. M., Michael, Y. L., Perdue, L. A., Coppola, E. L., & Beil , T. L. (2018). Interventions to prevent falls in older adults: Updated evidence report and systematic review for the US preventative task force. Journal of American Medical Association, 316(16), 1705-1716. doi:10.1001/jama.2017.21962

Lohman, M., Crow, R., DiMilia, P., Nicklett, E., Bruce, M., & Batsis, J. (2017). Operationalization and Validation of the Stopping Elderly Accidents, Deaths, and Injuries ( STEADI) Ffall Rrisk Aalgorithm in a Nnationally Rrepresentative Ssample. Journal Epidemiol Community Health, 71(12), 1191-1197. doi:10.1136/jec-2017-209769

Mayo Clinic. (2018, August 21). Mayo Clinic. Physical Mmedicine and Rrehabilitation: Eevaluating patient for fall risk. https://www.mayoclinic.org Physical Medicine and Rehabilitation Evaluating patients for fall risk

Melnyk, B., & Fineout-Overholt, E. (2019). Evidence-Based Practice in Nursing and Healthcare: A Guide to Best Practice (4th ed.). Philadelphia, PA: Wolters Kluwer Health.

National Council on Aging. (2017). States policy toolkit for advancing fall prevntion. Retrieved from National Council on Aging: https://www.ncoa.org/wp-content/uploads/State-Policy-Toolkit-for-Advancing-Fall-Prevention-Select-Resources.pdf

Nguyen, T., Wong, E., & Ciummo, F. (2020, January 5). Polypharmacy in Older Adults: Practical Applications Alongside a Patient Case. The Journal for Nurse Practitioners, 16(3), 205-209. doi:10.1016/j.nurpra.2019.11.017

Reinoso, H., McCaffrey, R., & Taylor, D. (2017). Mitigating fall risk: A community fall reduction program. Geriatric Nursing, 39(2018), 199-203. doi:10.1016/j.gerinurse.2017.08.014

Robb, M., & Shellenbarger, T. (2014). Strategies for Search and Managing Evidence-Based Practice Resources. The Journal of Continuing Education in Nursing, 45(10), 461-466. doi:10.3928/00220124-20140916-01

Shakya, I., & Moreland, B. L. (2020, September ). Fall-related emergency department visits involving alohol among older adults. Journal of Safety Research , 74, 125-131. doi:10.1016/j.jsr.2020.06.001

Soffin, E. M., Gibbons, M. M., Ko, C. Y., Kates, S. L., Wick, E. C., Cannesson, M., ... & Wu, C. L. (2019). Evidence review conducted for the agency for healthcare research and quality safety program for improving surgical care and recovery: focus on anesthesiology for total hip arthroplasty. Anesthesia & Analgesia, 128(3), 454-465.

Spano-Szekely, L., Winkler, A., Waters, C., Dealmeida, S., Brandt, K., Williamson, M., & Wright , F. (2019). Individualized fall prevention program in an acute care setting: An evidence-based practice improvement. Journal of Nursing Care Quality, 34(2), 127-132. doi:10.1097/NCQ.0000000000000344

Stevens, J., Smith, M. L., Parker , E., Jiang, L., & Floyd, F. (2020). Implementing a Clinically Based Fall Prevention Program. American Journal of Lifestyle Medicine, 14(1), 71. doi:10.1177/1559827617716085

Strini, V., Schiavolin, R., & Prendin, A. (2021). Fall Risk Assessment Scales: A systematic literature Review. Nursing Reports, 11, 430-443. doi:10.3390/nursrep11020041

The American Geriatrics Society and British Geriatrics Society. (2011, January ). Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. American Geriatrics Society, 59(1), 2-54. doi:10.1111/j.1532-5415.201.03234.x.

World Health Organization. (2017). World Health Organization: Falls. Retrieved from World Health Organization: https://www.who.int/mediacemtre/factsheets/fs344/en/

Appendix A

Literature Search Strategy Log __________________________________________________________________________________________________________

PICO question:  Does implementing a structured staff educational program using an evidence-based fall screening tool as part of a multifactorial fall prevention program reduce falls in patients aged 65 and older residing in an assisted living home compared to pre-implementation fall rates?

Database

Key Word 

Searches

Limits

# of Citations

Found / Kept

Rationale for  Inclusion 

CINAHL Plus

Falls in the Older adults

10 year period

26 found 3 kept

kept articles directly related to clinical question, excluded 17 articles were on pediatrics population, 3 articles were on post -op  hospitalized patients 

Google Scholar

Fall prevention

10 year period

150 found 1 kept


kept articles directly related to clinical question,  excluded 130 were on post-op fall, 19 articles on pediatrics falls.

PubMed

Fall prevention AND Older Adults

10 year period

67 found kept 2

kept articles directly related to clinical question, excluded 20 articles were on pediatric falls, 32 articles on post -op falls in an orthopedic unit, 13 articles on falls at home in patients less than 65 years.

Medline

Falls in the Older Adults AND Resident falls

10 year period 

15 found kept 1

kept articles directly related to clinical question, excluded 10 articles on post-op falls after a hip replacement, 2 articles on patients after abdominal surgery, 3 articles on pediatric falls

CINAHLPlus

Evidence -Based fall screening tool

10 year period

21 found kept 5

kept articles directly related to clinical question, excluded 14 articles that were on pediatric falls, 2 excluded on patient less than 65 years

CINAHL plus

Assisted Living Facilities  

10 year period

10 found kept 1

kept articles directly related to clinical question, excluded 6 articles on patient less than 65 years, excluded 3 articles on patient with falls at home

Cochrane Database

Fall risk tool*

10 year period 

15 found 2 kept

kept articles directly related to clinical question, excluded 10 articles on patient less than 65 years and 3 in patient with recent surgical procedures

Cochrane Database

Falls in adults 65 and older

10 year period

21 found1 keep

kept articles directly related to clinical question, excluded 18 articles on pediatric fall, 2 excluded in the home setting

CINAHL Plus

Fall assessment AND staff education

10 year period

17 found 2 kept

kept articles directly related to clinical question, excluded 13 articles in the home setting and 2 excluded in patient less than 65 years

Medline 

Fall prevention strategies

10 year period 

165 found 2 kept

kept articles directly related to clinical question, excluded 150 articles in patient less than 65 years, 10 excluded in pediatric patients and 3 excluded in patients after orthopedic surgery

Medline

Assisted Living home(s), Community dwelling(s)

10 year period

200 found 3 kept

kept articles directly related to clinical question, 65 excluded articles related to stroke, 19 excluded related to orthopedic surgery, 116 excluded articles in patient less than 65 years

Medline

“Morse Fall Scale”

10 year period

120 found 4 kept

Kept article within the last 10 years, excluded 100 article in patient with traumatic brain injury, excluded 5 on pediatric falls, excluded 1 on patients after a stroke

Medline

“STEADI” screening tool

10 year period

67 found 2 kept

Kept article within the last 10 years, excluded 40 articles on pediatric falls, 10 excluded patient after an orthopedic surgery, 4 excluded in patient in patient less than 65 years, 11 excluded on patients after traumatic brain injury.

Appendix B

Evidence Table-Matrix for Appendix in Review of the Literature Paper

NUR 702 Evidence as the Basis for Practice Change 

Article

Level of Evidence

 (I to VII)

Data/Evidence

Findings

Conclusion

Use of Evidence in EBP Project Plan

Reinoso, H., McCaffrey, R., & Taylor, D. (2017). Mitigating fall risk: A community fall reduction program. Geriatric Nursing, 39(2018), 199-203. 


Level II

Initiating an evidence-based fall screening tool allowed for the identification of patient at risk for fall. The patients were also placed in categories and ranking such as high, moderate, and low risk for falls. It also demonstrated that  that the students who were screeners in this study learned about falls  while working collaborative with other discipline

Initiating a fall screening tool helped in identifying patients at risk for falls as part of a multifaceted fall prevention program.

Include fall screening as part of a multifaceted fall reduction program.

Stevens, J. A., Smith, M. L., Parker, E. M., Jiang, L., & Floyd, F. D. (2017). Implementing a clinically based fall prevention program. American Journal of Lifestyle Medicine, 1559827617716085.

Level III

Initiating  the STEADI toolkit in patient aged 65 years and older helped in identifying patient at risk for falls.The practice saw 10,702 older patients, (79.0%) screened for fall risk, 18.1% screen positives, of patent screened positive, 51.6% complete TUG, 45.4% failed, and 25.1% was not screened due to mobility issues. The study allowed for the identification of  patients at risk for falls as part of a multifacted fall prevention program.

Initiating an evidence-based  fall screening tool helped in identifying patients at risk for falls as part of a multifaceted fall prevention program.

Include the STEADI toolkit as a multifaceted fall prevention kit.

Lohman, M. C., Crow, R. S., DiMilia, P. R., Nicklett, E. J., Bruce, M. L., & Batsis, J. A. (2017). Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample. J Epidemiol Community Health, 71(12), 1191-1197.

Level II

Initiated the STEADI toolkit in patient aged 65 years and older in the U.S. n=7,392 were categorized as high and moderated  risk has 2.62(95%CI: 2.29,2.99) and 4.76(95% CI: 3.51,647) times greater risk of falling when compared to participants who were identified as low fall risk. 

Initiating an evidence-based  fall screening tool helped in identifying patients at risk for falls as part of a multifaceted fall prevention program.

Include the STEADI toolkit as a multifaceted fall prevention kit.

Strini, V., Schiavolin, R., & Prendin, A. (2021). Fall risk assessment scales: a systematic literature review. Nursing Reports, 11(2), 430-443.

Level VI

Initiated a review of multiple fall risk screen the TUG identified patients strength, mobility capacity and dynamic balance, it predicts fall in patient who are frail. FRHOP tool demonstrated a sensitivity and specificity 57% and 68% respectively.

Demonstrated that the initiation of an evidence-based fall screening tool helped in identifying patients at risk for falls.

Included evidence- based fall screening tool as part a fall prevention program.














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