Presented at the Society for Academic Emergency Medicine’s Annual Meeting (Boston, MA), 2003; The Pennsylvania Chapter–American College of Emergency Physician’s annual meeting (Pittsburgh, PA), 2003; and The American College of Emergency Physician’s Scientific Assembly (Boston, MA), 2003.
Identification of Fall Risk Factors in Older Adult Emergency Department Patients
Article first published online: 4 MAR 2009
© 2009 by the Society for Academic Emergency Medicine
Academic Emergency Medicine
Volume 16, Issue 3, pages 211–219, March 2009
How to Cite
Carpenter, C. R., Scheatzle, M. D., D’Antonio, J. A., Ricci, P. T. and Coben, J. H. (2009), Identification of Fall Risk Factors in Older Adult Emergency Department Patients. Academic Emergency Medicine, 16: 211–219. doi: 10.1111/j.1553-2712.2009.00351.x
This work was funded in part by a grant from the Emergency Medicine Foundation.
- Issue published online: 4 MAR 2009
- Article first published online: 4 MAR 2009
- Received June 17, 2008; revisions received September 2 and October 14, 2008; accepted October 19, 2008.
- emergency medicine;
- injury prevention
Objectives: Falls represent an increasingly frequent source of injury among older adults. Identification of fall risk factors in geriatric patients may permit the effective utilization of scarce preventative resources. The objective of this study was to identify independent risk factors associated with an increased 6-month fall risk in community-dwelling older adults discharged from the emergency department (ED).
Methods: This was a prospective observational study with a convenience sampling of noninstitutionalized elders presenting to an urban teaching hospital ED who did not require hospital admission. Interviews were conducted to determine the presence of fall risk factors previously described in non-ED populations. Subjects were followed monthly for 6 months through postcard or telephone contact to identify subsequent falls. Univariate and Cox regression analysis were used to determine the association of risk factors with 6-month fall incidence.
Results: A total of 263 patients completed the survey, and 161 (61%) completed the entire 6 months of follow-up. Among the 263 enrolled, 39% reported a fall in the preceding year, including 15% with more than one fall and 22% with injurious falls. Among those completing the 6 months of follow-up, 14% reported at least one fall. Cox regression analysis identified four factors associated with falls during the 6-month follow-up: nonhealing foot sores (hazard ratio [HR] = 3.71, 95% confidence interval [CI] = 1.73 to 7.95), a prior fall history (HR = 2.62, 95% CI = 1.32 to 5.18), inability to cut one’s own toenails (HR = 2.04, 95% CI = 1.04 to 4.01), and self-reported depression (HR = 1.72, 95% CI = 0.83 to 3.55).
Conclusions: Falls, recurrent falls, and injurious falls in community-dwelling elder ED patients being evaluated for non–fall-related complaints occur at least as frequently as in previously described outpatient cohorts. Nonhealing foot sores, self-reported depression, not clipping one’s own toenails, and previous falls are all associated with falls after ED discharge.
Falls are a potentially preventable cause of geriatric injury, functional decline, and traumatic death.1–4 Unfortunately, falling is quite common because 27% of community-dwelling persons over age 65 years and 50% of those over 80 years of age will fall each year.5,6 As fall incidence is directly related to age, the numbers of falls and fall injuries presenting to the emergency department (ED) can only be expected to increase with the aging of our population.7,8 In an attempt to mitigate this increase, numerous fall screening instruments have been developed for use in outpatient settings.9–11 However, these instruments have not been adopted for ED use, as they are often too time-consuming and require equipment not readily available in the ED. Additionally, the risk factors used in these screening tools have not been evaluated on ED patient populations. While guidelines have previously suggested a role for screening elder fall patients to prevent recurrent falls, risk factors unique to ED patients have not been identified, nor has primary prevention been a focus of prior research.12 Perhaps because ED-specific risk factors and prevention effectiveness have not yet been identified, fall-related presentations often do not receive guideline-recommended diagnostic and preventative interventions in the ED.13,14
While the role of prevention within emergency medicine (EM) is debated in an increasingly crowded, time-deprived ED environment, the potential benefits include improving access to care for a vulnerable segment of society, optimizing a teachable moment, and reducing future ED visits via a proactive stance.15 The potential impact of ED-initiated falls prevention was highlighted by the Prevention of Falls in the Elderly Trial (PROFET) study, a randomized controlled trial of an interdisciplinary tertiary falls prevention program in the United Kingdom. This ED-based program demonstrated a marked reduction in recurrent falls, from 52% in the control group to 32% in the intervention group.16 As this study enrolled only those patients who presented to the ED with a fall, their intervention was applied to a cohort definitively known to be at high risk for falling.17,18
Obviously, prevention programs are most efficient when applied to those at greatest risk for a given outcome, and thus it is imperative that methods be developed to accurately identify those at highest risk. To date, fall risk assessment on ED patients has only been performed on those presenting with a fall. The risk factors identified by this ED-based study include prior falls, inability to arise following a fall, and indoor falls.16,19 Additionally, a small Australian ED-based case–control study demonstrated a significant association between falls and gait speed, balance, and polypharmacy.20 However, fall risk assessment has not been performed on those elders presenting to the ED for non–fall-related complaints. Older adults presenting to the ED may have increased overall risk of falling compared with the general community-dwelling elderly population, reflected by the 60% 1-year fall rate in PROFET, as opposed to the 27% point estimate in a recent systematic review noted in other populations.16,17 Identification of those at highest risk among these ED patients may provide a rich opportunity for primary preventive measures.
To our knowledge, no primary fall risk factor assessments have been described in the EM literature. A systematic review of the EM literature yielded 26 fall-related articles, of which none included ED-based primary falls prevention in geriatric patients.21 Our goal was to determine independent risk factors of a 6-month fall risk among discharged community-dwelling older adults who used the ED for non–fall-related complaints. We therefore analyzed ambulatory, community-dwelling elder patients evaluated in the ED and discharged home for any condition except a fall or a fall-related complaint. We chose to identify nonfallers for two reasons. First, those presenting with a fall have already defined themselves at higher risk for future falls22 and therefore already merit the allocation of fall prevention services.17 Second, a portion of elder ED patients are likely unrecognized past fallers or at increased risk of falls in the near future and might therefore benefit from fall prevention services.
This was a prospective observational study. To ensure standardized data collection, all research staff had a 6-hour training and observation period prior to independently enrolling patients. The hospital’s institutional review board approved this study. Written informed consent was obtained from all participants.
Study Setting and Population
This study was performed at an urban, academic medical center ED that cares for 48,000 patients each year, including 18% aged 65 years and older. This was a convenience sampling of these community-dwelling patients presenting to and discharged from the ED for any chief complaint except a fall or fall-related injury. Inclusion criteria included only age and lack of any exclusion criteria. Exclusion criteria included any of the following: non–English speaking, unable to complete the initial survey, preexisting nonambulatory status (i.e., wheelchair or bed-confined), institutionalized, failure to consent, or previous enrollment into the study. We define ambulatory as self-reported ability to walk greater than 10 steps with or without an assist device. The research team enrolled eligible patients once the treating physician made the decision to discharge the patient back to home.
Research staff enrolled patients in the ED from January 2002 through August 2002 during research shifts that included evenly distributed day, night, and weekend hours. Participants completed a 10-minute survey (Data Supplement S1, available as supporting information in the online version of this paper) administered by the research assistant (RA) to obtain key historical and physical exam fall risk factors. Survey questions were read to patients by research staff who answered any queries about individual item intent or meaning. The survey was derived from previously reported outpatient cohort studies and included those variables demonstrating significant association with falling, although it has not been validated in ED populations. The historical risk factors included demographics; whether the subject lived alone or with someone; whether the subject used a cane or walker to assist with ambulation;23–26 and comorbidities previously associated with falls including a prior diagnosis of dementia,22,23,27–32 depression,22,23,26,33,34 diabetes,35–41 strokes,42–44 and foot or leg problems.22,45 Additionally, measures of self-sufficiency were obtained, such as whether one cut his or her own toenails or climbs stairs.11,24 We also inquired about any history of incontinence within the preceding 6 months,11,25 previous falls within the preceding 12 months,11,19 ED utilization in the preceding 6 months, and self-reported driving status. Finally, we asked subjects to rate their overall health, as well as the occurrence of near falls and sense of imbalance, a simplification of the “Balance Self-Perceptions Test” previously used by Shumway-Cook and colleagues to identify high-risk fallers.46
On physical exam we assessed visual acuity using a pocket Snellen eye chart.47,48 Auditory acuity was assessed using a prerecorded whispered voice test as previously described by Macphee et al.49 In addition, we performed a brief functional assessment that involved the observation of four tasks: 1) getting up from an armless chair, 2) sitting down in an armless chair, 3) raising feet while walking, and 4) turning 180 degrees.50 Each task was scored as normal, completed with difficulty, or unable to complete. Subjects were categorized as having a normal mobility exam (normal on all four items), a borderline exam (normal on three items, difficulty in one), or an abnormal mobility exam (difficulty on two or more items or unable to do one or more items).50 The first 30 consenting subjects enrolled were videotaped during their functional assessment testing. The video performance was then assessed independently by five trained RAs to assess the interobserver reliability of the functional assessment tool. These were the same five RAs who recruited subjects into the study.
After the completion of the enrollment procedure, each participant was given a packet containing six stamped, addressed, postcard questionnaires regarding the occurrence of a fall or repeat ED visit during that respective month. The postcards were to be returned on the first of each month. Additionally, this packet contained a calendar to record a fall and to provide a mailing reminder. To minimize missing data, we attempted a phone interview with each participant whose card was not received by the 10th of each month.
The major dependent variable was the occurrence of a reported fall, which was defined as “when you suddenly find yourself on the ground, without intending to get there, after you were in either a lying, sitting, or standing position.”51
We analyzed all data using SPSS software (Version 11.0, SPSS Inc., Chicago, IL). To assess the interrater reliability of the functional assessment test categorization, an ordinal measure, we used the intraclass correlation coefficient (ICC). A Cox regression analysis was used in the univariate analysis to describe the relationship between fall and risk factor. To identify risk factors independently associated with falls during the 6-month follow-up and to reduce the bias due to patients being lost to follow-up, we used a Cox regression analysis with an automated backward stepwise selection using the likelihood ratio procedure with an entry p-value of 0.05 and an exclusion p-value of 0.10 in the final model. The largest p-values were sequentially removed until all p-values were less than the cutoff of 0.10. Some variables were excluded from the selection because of large numbers of missing data. Interaction terms were entered into the model after the backward stepwise regression. The selected main effects were forced into the model while all possible two-way interactions among these main effects were entered into the backward stepwise selection algorithm. We also used this Cox regression analysis to identify predictors unique to the subsets of past fallers or non–past fallers.
A total of 263 patients were enrolled, but 102 (39%) were lost to the full 6 months of follow-up. Among the 102 who did not complete the entire 6 months of follow-up, 8 were admitted to a long-term care facility; 2 were admitted to a hospital at a subsequent ED visit; 12 died; 39 could not be contacted by phone, multiple postcards, or alternate contact phone numbers; 36 declined further participation because of “lack of interest”; and 5 declined further participation for unstated reasons. Therefore, a total of 161 patients were analyzed with 6 months of follow-up. The cohort demographics were representative of our hospital’s geriatric ED population: 80% white and 63% female, with a mean age of 76 years (Table 1).
|Total||Sample, n (%)||Age (years), n (%)|
|Gender-female||1,188||167 (63)||76 (61)||71 (63)||20 (74)|
|African American||328||47 (18)||29 (23)||11(10)||7 (26)|
|Asian American||3||3 (1)||1 (<1)||1 (<1)||1 (4)|
|White||1,607||211 (80)||92 (74)||100 (89)||19 (70)|
|Hispanic||16||2 (1)||2 (2)||0 (0)||0 (0)|
|Lives alone||N/A||91 (35)||37 (30)||41 (37)||13 (48)|
|Ambulates||N/A||263 (100)||124 (100)||112 (100)||27 (100)|
|Cane-assisted ambulation||N/A||75 (29)||29 (23)||33 (29)||13 (48)|
|Can climb stairs||N/A||197 (75)||96 (77)||83 (74)||18 (67)|
|Does cut own toenails||N/A||165 (63)||89 (72)||62 (55)||14 (52)|
|Does drive a car||N/A||135 (51)||79 (64)||50 (45)||6 (22)|
|Drives only in daytime||N/A||39 (15)||21 (17)||17 (15)||1 (4)|
|Wears glasses||N/A||241 (92)||114 (92)||102 (91)||25 (93)|
|Has glasses||N/A||182 (69)||87 (70)||78 (70)||17 (63)|
|Urine incontinence||N/A||65 (25)||26 (21)||32 (29)||7 (26)|
|Excellent/very good||N/A||150 (57)||72 (58)||68 (61)||10 (37)|
|Fair/poor||113 (43)||52 (42)||44 (39)||17 (63)|
|Divorced||N/A||1 (<1)||0 (0)||1 (<1)||0 (0)|
|Married||116 (44)||66 (53)||43 (38)||7 (26)|
|Widowed||19 (7)||9 (7)||10 (9)||0 (0)|
|Single||127 (48)||49 (40)||58 (52)||20 (74)|
|Nonhealing footsore||N/A||22 (8)||13 (10)||9 (8)||0 (0)|
|Leg injury||N/A||6 (2)||3 (2)||2 (2)||1 (4)|
|Known diabetes||N/A||56 (21)||31 (25)||23 (21)||2 (7)|
|Prior stroke||N/A||47 (18)||18 (14)||19 (17)||10 (37)|
|Irregular heartbeat||N/A||114 (43)||57 (46)||44 (39)||13 (48)|
|Reported dementia||N/A||13 (5)||4 (3)||7 (6)||2 (7)|
|Reported depression||N/A||46 (17)||25 (20)||15 (13)||6 (22)|
|Fallen in last 1 year||N/A||102 (39)||41 (33)||50 (45)||11 (41)|
|Reported injury with previous falls||N/A||58 (22)||25 (20)||28 (25)||5 (19)|
|Reported frequent/occasional near falls||N/A||103 (39)||42 (34)||48 (43)||13 (48)|
|Self-perceived frequent/occasional imbalance||N/A||110 (42)||48 (39)||47 (42)||15 (56)|
|Previous ED use||N/A||90 (34)||42 (34)||38 (34)||10 (37)|
|Abnormal hearing||N/A||87 (33)||28 (23)||42 (38)||17 (63)|
|Abnormal||N/A||70 (27)||26 (21)||28 (25)||16 (59)|
|Borderline||29 (11)||10 (8)||15 (13)||4 (15)|
|Normal||127 (48)||66 (53)||56 (50)||5 (19)|
|Discharged nonambulatory||14 (5)||7 (6)||7 (6)||0 (0)|
|Refused||22 (8)||14 (11)||6 (5)||2 (7)|
Thirty-nine percent (102/263, 95% confidence interval [CI] = 33% to 45%) of the subjects reported a fall in the year preceding their enrollment with 15% (39/263, 95% CI = 11% to 19%) of them reporting more than one fall during that period. Among these past fallers, 22% (58/263, 95% CI = 17% to 27%) reported having sustained an injury, with fractures and contusions representing the most frequent injuries. Among the entire study cohort, during the 6 months of follow-up, 14% of patients (38/263, 95% CI = 10% to 19%) reported at least one fall. The reliability analysis of the functional assessment demonstrated an ICC of 0.77 (95% CI = 0.66 to 0.87) for single measures and 0.95 (95% CI = 0.91 to 0.97) for classification measures indicating excellent interrater reliability.
In those subjects followed for 6 months after the index ED visit, the univariate Cox hazard analysis identified 10 risk factors associated with falls: fall in the preceding year, nonhealing foot sores, ambulation with a cane, borderline functional assessment, reported near falls, increasing number of previous falls, failure to cut one’s own toenails, ED evaluation during the previous 12 months, depression, and occasional self-perception of imbalance (Table 2).
|Variable||HR||p-Value*||95% CI for HR|
|Number of medications||1.077||0.119||0.987||1.176|
|Does not climb stairs||0.846||0.645||0.420||1.706|
|Does not cut own toenails||2.740||0.002||1.429||5.253|
|Does not drive a car||1.195||0.583||0.632||2.260|
|Drives only in day||1.698||0.187||0.803||3.590|
|Does wear glasses||1.689||0.610||0.407||7.014|
|Does have glasses||1.155||0.693||0.560||2.378|
|Number of falls in previous year||1.230||0.004||1.100||1.376|
|Reported near falls||2.083||0.024||1.098||3.952|
|Previous ED use||2.173||0.018||1.148||4.112|
|Abnormal hearing OD||1.184||0.634||0.587||2.386|
|Abnormal hearing OS||1.281||0.494||0.622||2.637|
|Functional category abnormal||1.392||0.068||0.978||1.983|
|Functional category borderline||1.988||0.044||1.010||3.910|
|Race (nonwhite vs. white)||0.343||0.039||0.106||1.116|
|Stand in chair||1.025||0.960||0.400||2.624|
|Sit in chair||1.554||0.321||0.650||3.718|
|Visual acuity category||1.122||0.622||0.713||1.766|
These 10 risk factors were then analyzed using a Cox regression method, and 4 independent risk factors were identified: nonhealing foot sores, depression, falls in the preceding year, and failure to cut one’s own toenails (Table 3). During the 6-month follow-up period the mean probability of falling was 42% if all 4 risk factors were present, and 4% if none of the risk factors were present (Table 4). All possible two-way interaction terms were added to the model. The interaction between nonhealing foot wounds and past falls had a hazards ratio (HR) of 7.36 (95% CI = 2.91 to 18.64), indicating that those with both risk factors were more likely than those with one or neither risk factor to suffer a fall in the subsequent 6 months.
|Nonhealing foot sore||3.710||1.731, 7.952|
|Reported past falls||2.621||1.325, 5.185|
|Failure to cut own toenails||2.038||1.036, 4.011|
|Self-reported depression||1.721||0.834, 3.553|
|Number of Risk Factors||Number of Subjects||Mean Probability of Falling in 6 Months|
Patients with previous falls may differ from those who have not, so in a stratified analysis those reporting past falls were compared with those not reporting past falls to identify predictors unique to each group. The current study was not powered to detect fall risk factor differences between ambulatory ED patients with past falls from those without, so these potential differences are only hypotheses for future research efforts. For those who had reported a past fall, not cutting one’s own toenails (HR = 2.22, 95% CI = 0.85 to 5.75; p < 0.1) and the presence of nonhealing foot sores (HR = 7.36, 95% CI = 2.91 to 18.64; p < 0.001) were the only variables selected by the backward stepwise procedure. Therefore, there was an interaction (synergy) between nonhealing foot sores and past falls, as well as between not cutting one’s own toenails and past falls. Similarly, for those who had not reported a past fall, depression (HR = 3.95, 95% CI = 1.35 to 11.59; p = 0.012), and previous ED utilization (HR 2.63, 95% CI = 0.95 to 7.28; p = 0.061) were selected.
The prevalence rates of falls and injurious falls among our ED population are higher than those reported from outpatient community settings. The proportion of ambulatory, community-dwelling elders who report a fall in the preceding year in our study was 39%, while previous reports have reported a 27% prevalence.17 Similarly, in our patient population the prospective 6-month fall rate was 14%. This moderately higher fall rate may be explained by a lower general health status, and thus greater prevalence of fall risk factors, in our elder ED population than that of those visiting outpatient settings.52 Recurrent fallers were 15% of our cohort reporting more than one fall in the preceding year. In our cohort, 22% reported sustaining an injury with their past fall compared with previous reports ranging from 5% to 15% in the general geriatric population, although previous studies have shown that the vigorous elders are more prone to injurious falls when compared to frail elders (22% vs. 6%).53 We selected out the frail elders by excluding admitted and institutionalized patients.
We identified four independent risk factors for future falling in our ED cohort. These included nonhealing foot sores, self-reported depression, falls in the preceding year, and failure to cut one’s own toenails. The risk of falling was directly related to the number of these factors present. Of these factors, foot sores and past falls interacted to provide a highly significant risk for falling. Although these factors have been previously reported in non-ED patient populations,11,22,24,26,33,34,45 only prior falls has specifically been identified as a risk for falling in the ED population.19
Two risk factors increased 6-month fall risk among past fallers in community-dwelling older adults discharged from the ED: failure to cut one’s own toenails and the presence of nonhealing foot sores. Clipping one’s own toenails is likely a measure of functional ability, although other assessments of ambulation and balance were not independently associated with falls. The presence of nonhealing foot sores are a source of imbalance and antalgic gait. Among ED patients without past falls, two different risk factors independently identified those at higher fall risk over 6 months: depression and recent ED utilization. ED recidivism represents a compelling fall risk predictor, because this factor provides repeat interventional opportunities by recurrent patient–physician exposure. None of these risk factors have been previously described in elder ED populations. As each of these factors could be simply and quickly obtained by the ED physician or nursing staff, they make potentially attractive components of a practical geriatric ED fall risk stratification tool.
Many risk factors described previously in outpatient primary care settings did not independently predict falls in this cohort, including age, living situation, diabetes, incontinence, impaired vision, auditory deficits, and a functional assessment test. One explanation might be different self-reporting of various factors among acutely ill, distracted, elder ED patients compared with otherwise well outpatient populations. Alternatively, our small sample size and limited number of documented falls may have led to a Type II error.
Previous attempts to implement ED-initiated falls prevention in the United States have yielded disappointing results.54,55 As opposed to the indiscriminate application of fall prevention to all elder patients, the utilization of these interventions to a targeted population may have a greater impact on fall-related injury prevention, while maintaining reasonable ED lengths of stay and resource consumption. Ultimately, the development of a fall risk tool based on significant independent risk factors would enable busy EM providers to rapidly identify a subset of geriatric patients at high risk of falls and thereby permit the cost-effective utilization of limited preventative resources.21,56
A convenience sampling of ambulatory, English-speaking patients was used, although the study population was representative of our institution’s general geriatric ED population. Convenience sampling leaves open the possibility of selection bias, but in our study we would expect those who are in less acute distress and perhaps healthier to be overrepresented and thereby underestimate the true fall risk.
We cannot be certain of our study’s reproducibility between institutions because only one institution’s population was evaluated. The reliability of our study depended upon self-reported falls as the primary outcome. Previous research has suggested a significant recall bias among aging adults reporting falls.57 Our falls calendar, monthly fall assessment interval, and follow-up phone surveys should have minimized this anticipated recall bias. Also, our study had no a priori power calculation.
Previously validated instruments that might have been used in our data collection to more accurately define the presence or absence of certain target conditions such as dementia58,59 and depression60,61 were not used, although in simply inquiring about previously diagnosed conditions without any further diagnostic testing, we most closely approximated how events actually transpire in busy EDs. While only 5% of our population reported a past diagnosis of dementia, previous studies have indicated the prevalence of cognitive dysfunction for elder ED patients to be 25%–40%.62,63 The recognition and documentation of impaired mental status in elder ED patients is poor, and our results probably support that conclusion.63 Our lower rate may also be the result of selecting out those with greater impairments by only including those that lived in the community and were being discharged to their home.
Our data collection survey was not validated on ED populations. We did not differentiate between premorbid and acute medical crisis health self-perceptions. A number of risk factors were not surveyed, such as tobacco and alcohol use, cause of the falls, inability to rise after the fall, type of medications used at the time of the ED visit and upon which the patient was discharged home, or the type of housing in which the patient resided. The evidence supporting some of these risk factors was felt to be insufficient, while other variables were simply not surveyed. Additionally, an automated model-building process was used rather than a nonautomated analysis-driven process using a priori information. However, each of the candidate variables selected had been described as independent fall risk factors in non-ED populations before inclusion in our survey instrument.
Finally, the results and conclusions are limited by the incomplete 6 months of follow-up on a substantial portion of enrolled subjects. Our analysis suggests underrepresentation of elder ED patient fall risk, because past fallers and those with worse health assessment were more likely to be lost to follow-up. Previous research has suggested that retention of older adults in longitudinal studies may be motivated by subject curiosity, self-interest, or altruism, although optimal follow-up ultimately depends upon positive staff–recruit relationships.64 Such relationships may be difficult to foster in the overcrowded, single-exposure ED environment.65
Falls and injurious falls in community-dwelling elder ED patients who are discharged home occur frequently. In our overall cohort, four independent risk factors are associated with increased 6-month fall risk: nonhealing foot sores, self-reported depression, falls in the preceding year, and inability to cut one’s own toenails. The identification of risk factors for future falls among ambulatory elder ED patients could optimize the effective utilization of primary and secondary fall injury prevention measures.
- 4Centers for Disease Control and Prevention. Fatalities and injuries from falls among older adults–United States, 1993-2003 and 2001-2005. MMWR Morb Mortal Wkly Rep. 2006; 55:1222–4.
- 9Fall risk assessment measures: an analytic review. J Gerontol Med Sci. 2001; 56A:M761–6., , .
- 29Why do they fall? Monitoring risk factors in nursing homes. J Gerontol Nurs. 1990; 16:20–25., , , .
- 50History and mobility exam index to identify community-dwelling elderly persons at risk of falling. J Gerontol Med Sci. 2001; 56A:M253–9., , , , , .
- 51Prevention of falls in later life. Danish Med Bull. 1987; 34:1–24., , .
- 56Geriatric emergency medicine. In: LoCiceroJ, RosenthalRA, KaticM, et al., eds. New Frontiers in Geriatrics Research: An Agenda for Surgical and Related Medical Specialties, 2nd ed. New York, NY: The American Geriatrics Society, 2008, pp 45–72., .
Data Supplement S1. Patient assessment form.
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