Assessment of Fall Risk in Community‐Dwelling Older Adults Using the Stopping Elderly Accidents, Deaths, and Injuries Algorithm

ABSTRACT

Aim

To identify individuals at risk of falls and the factors contributing to their risk, we screened community‐dwelling older adults using the Centers for Disease Control and Prevention's Stopping Elderly Accidents, Deaths, and Injuries (STEADI) Assessments.

Design

A descriptive correlational study design.

Methods

Fall risk screenings with community‐dwelling older adults aged 65 or older were conducted during a virtual interprofessional education event (IPE) for fall risk screening. The screening included demographic questions, perception of fall risks, medication questions and physical assessments (Timed Up and Go test, Single Leg test, 30‐Second Sit to Stand) using the STEADI algorithm. Screening data were collected via Qualtrics, and descriptive data analyses were performed using SPSS.

Results

In total, 114 community volunteers aged 65 or older were screened for fall risk. Using the STEADI Fall Risk questionnaire, 84 participants (73.7%) exhibited at least one clinically proven risk factor for falls, with 39 (34.2%) having four or more risk factors. The physical assessments identified 37 participants (32.5%) with functional leg weakness, 47 (41.2%) had poor mobility and 32 (28.1%) had poor balance. As a result, the modified STEADI algorithm identified 68 (59.6%) with fall risk and the most frequently discussed SMART objectives were related to physical assessment data issues (34.5%).

Patient or Public Contribution

Our study confirmed the effectiveness of a multifaceted STEADI assessment in identifying community individuals at risk for falls who may not be detected through the normal standard of care. Educating nurses on performing comprehensive fall risk assessments and creating corresponding action plans with SMART objectives is essential to ensure thorough screening and care of their patients. A collaborative, interprofessional education programme can help train health professional students to gain valuable skills in conducting comprehensive fall risk screenings and developing objectives for future care plans based on those findings.

1. Introduction

Among adults 65 and older, falls have emerged as a critical public health concern in the United States. Approximately 28% of adults aged 65 and older fall each year, and age‐adjusted fall percentages per state showed a range between 19.9% (Illinois) and 38% (Alaska) in 2020 (the Centers for Disease Control and Prevention [CDC] 2024). Moreover, a person's history of falls has been reported to increase the risk of falls by three times (Li et al. 2023). Falls have both physical and financial impacts, making fall risk in the older adult population a crucial issue for healthcare providers, researchers and policymakers. In 2021, the CDC reported that 14 million older adults reported falling during the previous year in 2020, and 38,742 deaths were attributed to unintentional falls in 2021 (Kakara et al. 2023). Falls can result in devastating injuries, such as hip fractures and traumatic brain injuries (Komisar et al. 2022). In fact, the age‐adjusted fall death rate among older adults increased by 41% from 2012 to 2021 (CDC 2024). Additionally, there is a significant economic impact attributable to falls, with total spending in 2015 estimated to be $50 billion (Florence et al. 2018). However, falls are multifactorial, preventable and have identifiable risks. Some risk factors include age, chronic disease, gait and balance, functional ability, cognitive ability, medications, fall hazards in and around the home and hazardous activities (Moncada and Mire 2017).

The American Geriatrics society suggests yearly screening of adults 65 and older for falls (Eckstrom et al. 2024; Montero‐Odasso et al. 2022). There are multiple screening tools that focus on identifying the various risk factors for falls. By identifying these risks, the risk of falls and the associated financial costs may be reduced through performing medication reviews, referrals to exercise programmes, referrals to other health care professionals, addressing home hazards and correcting visual issues (Stevens and Lee 2018). Stopping Elderly Accidents, Deaths, and Injuries (STEADI) is an evidence‐based multifactorial risk assessment which includes questionnaires, physical assessments and intervention plans (CDC 2019). However, most primary care providers indicated not being aware of the STEADI (Howland et al. 2018) and most older adults do not have access to healthcare providers that have significant geriatric training (Eckstrom et al. 2024). Among all primary care providers (PCPs), 56.4% reported screening for fall risk during wellness visits, and 45.6% used a standardised test for gait and balance (Mark et al. 2020). The most common test (26.6%) utilised was the Timed Up and Go (TUG) (Mark et al. 2020) as it is included in the annual Medicare wellness exam. To increase standardised screening and frequency, it is imperative to train all health care professionals about fall screening guidelines regardless of healthcare discipline or settings. Interprofessional education (IPE) programmes would help healthcare professionals acquire knowledge of fall risk screening methods and practice proper assessments with their interdisciplinary peers and facilitators. This study's purpose was to use a standardised multifaceted screening tool to identify fall risks and risk factors among community‐dwelling older adults using the CDC's STEADI algorithm as part of an IPE training event.

2. Materials and Methods

2.1. Design and Participants

A descriptive correlational study design was employed. Since 2020, a virtual IPE event has been held in October for fall risk screening. Students from the Nursing, Physical Therapy and Pharmacy programmes participated in the event and conducted the risk assessments. As part of the training, the students reviewed the pre‐event materials and attended an orientation session to learn the screening methods and practise proper assessments with their interdisciplinary peers and facilitators. Students were then tasked with identifying a community volunteer willing to participate in the screening process. Volunteers provided their consent by signing a volunteer form. A total of 114 students from the nursing undergraduate programme (n = 59), Doctor of Physical Therapist (PT) programme (n = 37), and Pharm D programme (n = 18) completed the risk assessments for older adults aged 65 or older in 2022 and 2023. De‐identified data were entered into Qualtrics and used for evaluating the quality of the screening process. The study received approval from the University's Institutional Review Board (Pro2023002069) before enrolling participants in the programme. All study participants provided informed written consent.

2.2. Measures

Based on CDC recommendations, a screening tool was compiled by a team of faculty members from pharmacy, physical therapy and nursing. The tool includes demographic questions (age, gender and race), perception of fall risks (e.g., concerned about falling, perceiving having healthy bones), medication questions (e.g., the number of medications increasing fall risk, vitamin supplements including calcium and vitamin D) and physical assessments (The TUG test, Single Leg Balance [SLB] test, 30‐Second Chair Stand Test, orthostatic hypotension). This screening tool also included standardised questionnaires for fall risk (the STEADI ‘Stay Independent’ Fall Risk Instrument) and home safety checklists (Check for Safety: A Home Fall Prevention Checklist for Older Adults).

For this study, we used a modified STEADI algorithm (excluding eye exam, foot exam and comorbidities) for the screening, assessment and intervention phases (see Figure 1 for modified STEADI algorithm). Screening involves the initial assessment of fall risk using the 12‐item STEADI ‘Stay Independent’ fall risk self‐assessment instrument (CDC 2023) and three key questions. Items in the 12‐item assessment include ‘I often have to rush to the toilet’ and ‘I need to push with my hands to stand up from a chair’. Each item was coded as either yes (1) or no (0), except for two items (i.e., fallen in the past year and used or advised to use a cane or walker) having 2 points for yes. The number of risk factors were counted, and the total score was reported to assess their risk. Additionally, fall risk is evaluated using three key questions (yes or no): ‘Do you feel unsteady when standing or walking?’ ‘Do you worry about falling?’ ‘Have you fallen in the past year?’

FIGURE 1.

Modified STEADI algorithm displayed in three phases: Screening, assessment and intervention, along with the corresponding measures used in each phase.

Assessment, the second phase, involves evaluating individuals' fall risk factors through physical assessments (e.g., TUG, SLB, 30‐Second Chair Stand Test, orthostatic hypotension), assessing medications associated with falls, and identifying home hazards. The TUG test, which assesses functional mobility (CDC 2017b) involves measuring the time in seconds it takes an individual to stand up from a chair, walk 3 m (10 ft), turn around, walk back to the chair and sit down. Reference values based on age (e.g., 12 s for 60 or older vs. 8.86 s for 40–49 years old) are used to determine increased fall risk due to mobility issues. In the SLB test, the duration in seconds that an individual can maintain a single leg stand is recorded. Balance is considered normal if the time exceeds 5 s on either leg (Blodgett et al. 2022). If the time does not exceed 5 s, it indicates an increased risk of injurious falls. In the 30‐Second Chair Stand Test, which measures leg strength and endurance (CDC 2017a), a timer is set for 30 seconds and the number of times a client can fully sit and stand is recorded. Lower extremity weakness is determined based on the normative data considering gender and age (e.g., 14 for men and 12 for women aged 60–64 years vs. 20 for men and women younger than 60) indicating increased functional weakness.

Individuals' medications are also assessed for any association with fall risk. The presence of orthostatic hypotension is additionally determined by measuring blood pressure manually while sitting and standing (CDC 2017d). A decrease of 20 mmHg in systolic BP or 10 mmHg in diastolic BP within 1–5 min of standing, as compared to the sitting BP, indicates the presence of orthostatic hypotension. The CDC's Home safety checklist is utilised to identify hazards in different areas of the home, including floors, stairs, kitchen, bathrooms and bedrooms (CDC 2017c). Although there is no specific threshold for fall risk, this tool helps identify potential hazards and provides opportunities to mitigate them. In the final phase, Intervention, an individualised care plan is developed based on the results of the screening and assessment phases. For this study, students identified an area for improvement and developed an objective for a future care plan based on the screening results. Students collaborated with their client to prioritise one problem identified on the screening and then create a specific, measurable, achievable, relevant and time bound (SMART) objective (CDC 2022) that the client was confident in achieving within a month.

2.3. Statistical Analyses

All data were collected via Qualtrics and analysed using IBM SPSS Statistics, version 29 (IBM Corp. Armonk, NY, USA). Descriptive statistics (mean, standard deviations and frequencies) were used to present the study variables. Normality assumptions for continuous variables were assessed using the Shapiro–Wilk test. The Mann–Whitney U test (a non‐parametric alternative to independent t‐tests) and chi‐squared tests (with Cramer's V to estimate effect sizes) were conducted to examine the association between risk status and risk factors. A two‐tailed p value of < 0.05 was considered statistically significant.

3. Results

In total, 114 community volunteers aged 65 or older underwent screening for fall risk (Table 1). The average age of the volunteers was 74.43 years old, ranging from 65 to 91 (median: 74 years old), and 70% of them were female (n = 79). The sample consisted of 43.9% Non‐Hispanic White (n = 50), 19.3% Hispanics (n = 22), 21.1% Asians (n = 24) and 11.4% Non‐Hispanic Black (n = 13). About 78% were taking at least one medication increasing fall risk (n = 89) and 56.1% were taking vitamin D (n = 64). On average, the community volunteer participants had 2.9 home safety issues. The three most frequently reported hazards were having throw rugs on the floor (n = 54), having to walk around furniture (n = 43), and having objects on the floor (n = 37).

TABLE 1.

Summary of the sample and risk assessments (N = 114).

		n	%	Mean ± SD	Range
Age				74.4 ± 6.9	65–91
Gender	Male	34	29.8
	Female	79	69.3
	Prefer not to say	1	0.9
Race	NH White	50	43.9
	NH Black	13	11.4
	Hispanics	22	19.3
	Asians	24	21.1
	Other	5	4.4
Feeling unsteady	Yes	43	37.7
	No	71	62.3
Concerned about falling	Yes	50	43.9
	No	64	56.1
Fallen in the past year	Yes	27	23.7
	No	87	76.3
Orthostatic hypotension	Yes	3	2.6
	No	110	96.5
TUG (in seconds)				17.9 ± 18.2	5–124
	Poor mobility	47	41.2
30‐Second Chair Stand (in number)				11.6 ± 5.4	1–31
	Functional leg weakness	37	32.5
Single Leg Balance—Left (seconds)				13.8 ± 9.6	0–30
Single Leg Balance—Right (seconds)				15.9 ± 10.5	0–30
	Poor balance	32	28.1
Home safety issues				2.9 ± 2.1	0–9
Medications increasing fall risk	0	25	21.9
	1	42	36.8
	2	24	21.1
	3	11	9.6
	4	11	9.6
Taking vitamin D	Yes	64	56.1
	No	50	34.0

Twenty‐seven participants reported having fallen within the past year (23.7%), and those with a history of falls were more likely to be concerned about falling (66.7% vs. 36.8%, χ ² (1, N = 114) = 7.474, p = 0.006). Based on the STEADI Fall Risk questionnaire, 84 participants (73.7%) exhibited at least one clinically proven risk factor for falls, with 39 participants having four or more risk factors (34.2%). The most frequently reported risk factors were feeling unsteady (41.2%) and needing to push with their hands to stand up from a chair (41.2%), followed by worrying about falling (37.7%). When the total score was calculated, 45 participants (39.5%) had 4 points or more, indicating that they are at risk of falling.

The physical assessment tests identified that 37 participants (32.5%) displayed functional leg weakness (as assessed by the 30‐Second Chair Stand Test), 47 (41.2%) had poor mobility (according to the TUG test), and 32 (28.1%) had poor balance (determined by the SLB test). As a result, the STEADI algorithm identified 68 participants (59.6%) at risk for falls. This was about 23 individuals more (delta % change: 50.9%) than those identified by the STEADI Fall Risk questionnaire only.

Those with fall risk were more likely to perceive their bones as unhealthy than their counterparts (47.1% vs. 28.3%), and this association was statistically significant, χ ² (1, N = 114) = 4.058, p = 0.044. Mann–Whitney U tests showed significant differences between those with and without fall risk in age (z = −3.391, p < 0.001), the 30‐Second Chair Stand Test (z = −4.194, p < 0.001), SLB test (Right: z = −5.697, p < 0.001, Left: −5.177, p < 0.001) and the TUG test (z = −4.132, p < 0.001). In other words, those with fall risk were older (76.3 vs. 71.7 years) and performed worse on physical assessments of the 30‐Second Chair Stand Test (10.1 vs. 13.8 reps), SLB test (Right: 11.3 vs. 22.7 s; Left: 10.0 vs. 19.4 s) and the TUG test (19.7 vs. 15.2 s) than those without fall risk.

In addition, Chi‐squared test results are presented in Table 2. Those identified as having a fall risk from the screening showed significantly higher proportions of having risk factors than their counterparts, except for orthostatic hypotension and taking medication. Interestingly, the association between taking vitamin D and having a fall risk showed an opposite direction, with a higher proportion in the group taking vitamin D exhibiting a lower fall risk, but it was not statistically significant (p = 0.063).

TABLE 2.

Proportion of risk factors by identified risk group (N = 114).

	Identified as being at risk		p
	Yes	No
	68 (100%)	46 (100%)
Poor mobility	37 (55.2%)	10 (22.2%)	0.001
Functional leg weakness	31 (47.0%)	6 (13.0%)	< 0.001
Poor balance	28 (41.8%)	4 (8.7%)	< 0.001
Home hazards	62 (91.2%)	34 (73.9%)	0.013
Orthostatic hypotension	1 (1.5%)	2 (4.3%)	0.354
Taking medication increasing fall risk	53 (79.1%)	35 (76.1%)	0.704
Not taking vitamin D	25 (36.8%)	25 (54.3%)	0.063

Note: Column percentage was reported (% within ‘identified as being at risk’ Yes/No).

Based on the screening results, a SMART objective was developed and discussed with participants to address the identified issues. The most frequently discussed SMART objective was related to physical assessment data issues (n = 39), followed by the need for exercise (n = 32), home safety (n = 26) and wellness (n = 9). While a significant number of older adults are taking at least one medication increasing the risk of falls, only 6% of SMART objectives (n = 7) were related to medication. The focus of SMART objectives was not significantly associated with whether participants were at risk for falls or not (p = 0.293, Cramer's V = 0.193). However, those at risk discussed physical assessments and exercise/wellness more frequently than their counterparts (respectively 38.2% vs. 28.9% and 38.2% vs. 33.3%), while they discussed home safety less than their counterparts (26.7% vs. 20.6%).

4. Discussion

Our study confirmed that standardised screening was effective in identifying individuals at risk for falls who may not be identified through current standard of care (Mark et al. 2020). For example, after the STEADI Fall Risk questionnaire, about 51% were additionally identified with physical assessments in a delta % change (39.5% vs. 59.6%). Our screening showed about 24% of the participants (n = 27) having a history of falls within the year, which is slightly lower than CDC's fall estimate of 28% among adults aged 65 and older (CDC 2024). The current study demonstrated that about 60% of older adults screened in the community were identified as being at risk for falls based on the modified STEADI algorithm. Significant risk factors included age, poor physical performance and having home hazards, consistent with previous research (Li et al. 2023; Moncada and Mire 2017). Through the screening, an average of three home hazards per participant were detected. Home fall‐hazard reduction was an effective intervention, reducing falls by 26% (Lewis and Griffin 2023). Therefore, checking home hazards became an essential component of the screening.

Moreover, our study demonstrated how discussing screening results with participants led to the development of objectives for future client‐driven actions aimed at reducing fall risks. While issues with physical assessment data such as mobility, balance and weakness were a major focus of their objectives, the identified fall risk status did not show a statistically significant association with the focus area of the objectives. Unless immediate referral is needed, it is not uncommon for setting prevention and harm reduction objectives to rely on participants' preferences and feasibility in practice settings. Since the association showed a marginally moderate relationship (Cramer's V = 0.193), further research with a large sample size will be necessary to better understand the process from screening to client‐driven action objectives.

Screening for fall risk can occur in various settings, and it is vital that older individuals undergo screening at every interaction with healthcare providers. For example, fall guidelines could be implemented in ambulatory settings where older adults are seen. However, using the STEADI algorithm was often perceived as time‐consuming in primary care settings (Howland et al. 2018). Although evidence‐based screening tools for fall risk assessments are available, healthcare providers including nurses may have limited educational preparation and inadequate practice opportunities to conduct comprehensive screenings effectively. Therefore, educating healthcare professionals on performing comprehensive fall risk assessments is essential to ensure thorough screening. Student training events, via IPE's, are a good opportunity to increase knowledge about fall risk and increase screening opportunities for older adults in the community.

4.1. Limitations

Findings of the current study may not be generalisable due to the use of convenience sampling method, which includes a feature of networking sampling, and the limited sample size. Additionally, direct supervision was not possible during the screening, which could have affected the accuracy of the screening measures. However, the study results are still valuable as they enable the identification and early modification of fall risks. The screening also provided opportunities to enhance awareness of fall prevention and understand the utilisation of the STEADI algorithm in the community.

5. Conclusions

Our study confirmed the effectiveness of utilising a standardised multifaceted screening tool to identify individuals at risk for falls. While clinicians often work independently in community settings, they should be proficient in collaborating with other health care professionals to provide comprehensive, holistic care. In addition, our study design employing a collaborative, interprofessional education programme indicated nursing students gained valuable skills in conducting comprehensive fall risk screenings (that includes tests normally outside of their discipline), analysing results, and developing objectives for future care plans based on those findings. Furthermore, enhancing mechanisms for conducting follow‐up is critical because this will promote sustained engagement, support, and collaboration with older adults in the community.

Disclosure

The authors have nothing to report.

Ethics Statement

Rutgers University Institutional Review Board determined this study was exempt because it was conducted as part of quality improvement project without personal identifiers (IRB # Pro2023002069).

Conflicts of Interest

The authors declare no conflicts of interest.

Yang, K. , Wingerden A. V., Galagoza M., Soldevilla K., Lim E. A., and Wagner M. L.. 2025. “Assessment of Fall Risk in Community‐Dwelling Older Adults Using the Stopping Elderly Accidents, Deaths, and Injuries Algorithm.” Nursing Open 12, no. 9: e70299. 10.1002/nop2.70299.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.