Group Title: BMC Geriatrics
Title: Falls following discharge after an in-hospital fall
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Title: Falls following discharge after an in-hospital fall
Physical Description: Book
Language: English
Creator: Davenport, Rick
Vaidean, Georgeta
Jones, Carol
Chandler, A. M.
Kessler, Lori
Mion, Lorraine
Shorr, Ronald
Publisher: BMC Geriatrics
Publication Date: 2009
 Notes
Abstract: BACKGROUND:Falls are among the most common adverse events reported in hospitalized patients. While there is a growing body of literature on fall prevention in the hospital, the data examining the fall rate and risk factors for falls in the immediate post-hospitalization period has not been well described. The objectives of the present study were to determine the fall rate of in-hospital fallers at home and to explore the risk factors for falls during the immediate post-hospitalization period.METHODS:We identified patients who sustained a fall on one of 16 medical/surgical nursing units during an inpatient admission to an urban community teaching hospital. After discharge, falls were ascertained using weekly telephone surveillance for 4 weeks post-discharge. Patients were followed until death, loss to follow up or end of study (four weeks). Time spent rehospitalized or institutionalized was censored in rate calculations.RESULTS:Of 95 hospitalized patients who fell during recruitment, 65 (68%) met inclusion criteria and agreed to participate. These subjects contributed 1498 person-days to the study (mean duration of follow-up = 23 days). Seventy-five percent were African-American and 43% were women. Sixteen patients (25%) had multiple falls during hospitalization and 23 patients (35%) suffered a fall-related injury during hospitalization. Nineteen patients (29%) experienced 38 falls at their homes, yielding a fall rate of 25.4/1,000 person-days (95% CI: 17.3-33.4). Twenty-three patients (35%) were readmitted and 3(5%) died. One patient experienced a hip fracture. In exploratory univariate analysis, persons who were likely to fall at home were those who sustained multiple falls in the hospital (p = 0.008).CONCLUSION:Patients who fall during hospitalization, especially on more than one occasion, are at high risk for falling at home following hospital discharge. Interventions to reduce falls would be appropriate to test in this high-risk population.
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Research article

Falls following discharge after an in-hospital fall
Rick D Davenport', Georgeta D Vaidean2, Carol B Jones3, A
Michelle Chandler3, Lori A Kessler3, Lorraine C Mion4 and Ronald I Shorr*5,6


Address: 1HSR&D/RR&D Center of Excellence, James A. HaleyVAMC, 8900 Grand Oak Circle, Tampa, FL, 33637, USA, 2Department of Pharmacy
and Health Outcomes, Touro College of Pharmacy, 230 West 125th Street, Suite 430, New York, NY, 10027, USA, 3Methodist Healthcare
Foundation, 1211 Union Avenue, Suite 450, Memphis, TN, 38104, USA, 4School of Nursing, Vanderbilt University, 461 21st Avenue South,
Nashville, TN, 37240, USA, 5Geriatric Research, Education, and Clinical Center (GRECC), Malcom Randall VAMC (182), 1601 SW Archer Road,
Gainesville, FL, 32608, USA and 6Department of Aging and Geriatric Research, University of Florida, 1329 SW 16th Street, Gainesville, FL, 32611,
USA
Email: Rick D Davenport Rick.Davenportl@va.gov; Georgeta D Vaidean georgeta.vaidean@touro.edu;
Carol B Jones jonesca@methodisthealth.org; A Michelle Chandler chandlea@methodisthealth.org;
Lori A Kessler kesslerl@methodisthealth.org; Lorraine C Mion lorraine.c.mion@vanderbilt.edu; Ronald I Shorr* ronald.shorr@va.gov
* Corresponding author



Published: I December 2009 Received: 13 March 2009
BMC Geriatrics 2009, 9:53 doi: 10. 1186/1471-2318-9-53 Accepted: I December 2009
This article is available from: http://www.biomedcentral.com/1471-2318/9/53
2009 Davenport et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.



Abstract
Background: Falls are among the most common adverse events reported in hospitalized patients.
While there is a growing body of literature on fall prevention in the hospital, the data examining
the fall rate and risk factors for falls in the immediate post-hospitalization period has not been well
described. The objectives of the present study were to determine the fall rate of in-hospital fallers
at home and to explore the risk factors for falls during the immediate post-hospitalization period.
Methods: We identified patients who sustained a fall on one of 16 medical/surgical nursing units
during an inpatient admission to an urban community teaching hospital. After discharge, falls were
ascertained using weekly telephone surveillance for 4 weeks post-discharge. Patients were followed
until death, loss to follow up or end of study (four weeks). Time spent rehospitalized or
institutionalized was censored in rate calculations.
Results: Of 95 hospitalized patients who fell during recruitment, 65 (68%) met inclusion criteria
and agreed to participate. These subjects contributed 1498 person-days to the study (mean
duration of follow-up = 23 days). Seventy-five percent were African-American and 43% were
women. Sixteen patients (25%) had multiple falls during hospitalization and 23 patients (35%)
suffered a fall-related injury during hospitalization. Nineteen patients (29%) experienced 38 falls at
their homes, yielding a fall rate of 25.4/1,000 person-days (95% Cl: 17.3-33.4). Twenty-three
patients (35%) were readmitted and 3(5%) died. One patient experienced a hip fracture. In
exploratory univariate analysis, persons who were likely to fall at home were those who sustained
multiple falls in the hospital (p = 0.008).
Conclusion: Patients who fall during hospitalization, especially on more than one occasion, are at
high risk for falling at home following hospital discharge. Interventions to reduce falls would be
appropriate to test in this high-risk population.





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Background
Patient falls represent over one-third of incidents reported
in hospitals [1,2], and they are the largest single category
of reported hospital adverse events [1-3]. Patient falls are
more frequently reported than medication errors, equip-
ment related incidents, and documentation errors [1].
There are significant costs associated with patient falls,
including patient care costs [4], liability [5], and increased
length of stay [4]. With approximately 2% to 7% of acute-
care hospitalized patients experiencing at least one fall
during their stay [3,6,7], researchers and health care insti-
tutions have placed prioritization on the development
and implementation of in-hospital fall prevention strate-
gies and programs. As a result numerous fall risk assess-
ment tools have been developed to identify patients at risk
of falling in hospitals [8,9], as well as the implementation
of a wide range of hospital-based fall prevention pro-
grams [7,10,11]. While there is a growing body of litera-
ture on fall prevention in the hospital, the data examining
the fall rate and risk factors for falls in the immediate post-
hospitalization period has not been well described [12-
141.

While there is very little data examining the fall rate and
risk factors for falls in the immediate post-hospitalization
period of the older adult [12-14], there are almost no data
regarding the fall rate and risk factors for falls in the
immediate post-hospitalization period among hospital-
ized patients who fall a potentially vulnerable popula-
tion. Therefore, the aims of the present study were to
determine the fall rate of in-hospital fallers at home and
to explore the risk factors for falls during the immediate
post-hospitalization period of patients who had fallen
during their hospital stay.

Methods
Study population
Methodist Health University Hospital (MHUH) has an
ongoing Fall Evaluation Service as part of a quality
improvement project. MHUH is a 652-bed urban commu-
nity hospital in Memphis, Tennessee. The hospital pro-
vides primary to tertiary care to a diverse adult patient
population. As previously described [15], MHUH uses a
Fall Evaluation Service, which provides 24-hours/day, 7-
days/week coverage of 16 medical/surgical nursing units
and it allows for a greater detection of falls during hospi-
talization, than by incident reports. The Fall Evaluation
Service consists of trained healthcare professionals (fall
evaluators), who assess patients sustaining a potential fall
event using a standardized data collection tool.

The Fall Evaluation Service team maintains a log of all
hospitalized patient falls, which was used to identify
potential participants for the present study. A prospective
cohort of subjects who sustained a fall during an inpatient


admission to MHUH between February and June 2006
were recruited. Inclusion criteria were: English speaking
subjects who had fallen during this hospitalization, had
not been a nursing home resident prior to hospitalization
or would not be discharged to a nursing home, had a life
expectancy of greater than 3 months, were alive at the time
of hospital discharge, had a home phone, and had a next
of kin available as a backup contact person. Because this
study was used as a pilot/feasibility study to develop a
home-based intervention to prevent falls in this popula-
tion, we only included patients who lived 30 miles or less
from the hospital. We did not restrict our study to older
patients because in our experience, many younger hospi-
talized patients also exhibit falls due to frailty and would
potentially benefit from a home based fall prevention
intervention. Informed consent was obtained in accord-
ance with the guidelines from the Methodist Healthcare
Institutional Review Board, which approved the study.

Baseline data collection
Data were collected using the fall evaluation service and
medical record review. Initial assessment consisted of
recording clinical and demographic characteristics, pre-
hospitalization falls history, number of in-hospital falls,
and whether any injuries were sustained during the in-
hospital fall. Additional data included whether an ambu-
latory assistive device (e.g. walker, cane, and wheelchair)
was utilized at home prior to hospitalization and whether
participants were seen by physical and/or occupational
therapy during their hospital stay.

Follow-up and outcomes ascertainment
The main outcome was the occurrence of a self- or car-
egiver-reported fall at home during the 4 weeks after hos-
pital discharge, a high risk time for a fall post-
hospitalization [12]. Participants were contacted weekly
by telephone beginning the participant's arrival to their
home--either after being discharged from the hospital or
after a short stay in a rehabilitation center or skilled nurs-
ing facility. Weekly phone calls consisted of a semi-struc-
tured interview conducted by health professional staff,
trained in falls assessment and telephone interviewing
techniques. To minimize participant burden, the content
of the calls was limited to whether the subject remained at
home, the number of falls, and the utilization of rehabil-
itation services during the seven day interval. The primary
source of information was the participant, followed by the
caregiver, if necessary.

Additionally all participants were provided a flyer on 'Pre-
venting falls and fractures' as part of usual care services
from the Fall Evaluation Services Program. The flyer out-
lined fall prevention tips, such as: having their vision and
hearing checked, wearing rubber-soled shoes, and keep-
ing pathways in their home cleared.


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Statistical analysis
Falls during the follow-up were assessed in two ways: 1)
proportion of patients who fell, and 2) rate of falls per
patient-day of follow up. Patient-days of follow-up began
on the day of the participant's arrival home and ended at
the first date of either death, admission to a nursing
home, loss to follow-up, refusal to participate or end of
study. Days rehospitalized were excluded from person-
time.

We evaluated the effect of exposure variables on the pro-
portion of persons who sustained a fall during the follow
up using Chi-Square or the Fisher's exact test where appro-
priate. We estimated the effect of exposure variables on
the rate of falling using the test for incidence rate ratio
assuming a Poisson distribution and used Poisson regres-
sion for exploratory multivariate analysis with correction
for overdispersion. All statistics were performed using
SAS, version 9.1 (SAS Institute, Inc., Cary, NC) and all p-
values were two-sided.

Results
Study population
During the study period, 171 fallers were identified by the
Fall Evaluation Service. Among these, 75 patients were not
eligible for this study, 11 refused, and 20 not enrolled for
other reasons (16 patients were discharged before screen-
ing, 2 patients the hospital staff asked not to approach due
to risk management issues/hostile patient, 2 screens were
missed) (Figure 1). Sixty-five patients agreed to participate
and were enrolled in our study. Those who refused to par-


In-hospital fallers assessed
for eligibility (n = 171)

Excluded (n = 106)
Not meeting inclusion criteria (n = 75)
Residence >30 miles from
hospital (n = 30)
S* Residence in a nursing home
D d (n = 26)
Life expectancy < 3 months
(n = 4)
No next of kin to contact
(n = 9)
Not alive at discharge (n = 6)
Refused to participate (n = 11)
Other reasons (n= 20)

&Enrolled (N = 65)
Discharged directly home (n = 46)
Discharged to skilled nursing facility/
S rehabilitation hospital and then home (n = 19)

.4 Analyzed 4 weeks of home surveillance
data Initiated upon patient's arrival
home (n = 65)

Figure I
Flow chart of enrollment, follow-up, and analysis.


ticipate (n = 11) were similar in age (mean 62 years, stand-
ard deviation + 15), and race (64% African American), but
were more likely to be male (82%).

The participating 65 patients had a mean age of 62.5 years
(range 22-97), 43% were female, 75% were African Amer-
ican, and average hospital stay was 13.8 days. Of these, 46
(71%) were discharged immediately to home and 19
(29%) were discharge to a skilled nursing facility/rehabil-
itation hospital and then discharged home. Most partici-
pants (65%) had a history of falls prior to this hospital
admission, with 32% reporting a history of multiple falls.
All participants experienced a fall during their hospital
stay (an inclusion criterion); additionally 16 (25%) of
participants suffered multiple falls during their hospital
stay, with 23 (35%) experiencing an injury secondary to
the hospital fall (Table 1).

Falls following discharge
Phone calls made each week to all the 65 participants.
Information was obtained directly from the patient; in the
circumstance when the participant was unavailable the
next of kin was contacted regarding hospitalizations, nurs-
ing home placement, or mortality. All 65 participants ini-
tially consented to receive phone calls; only three (4.6%)
participants refused phone contact at home after 1, 2 and
3 weeks respectively. These three participants never expe-
rienced a fall at home up to the point of their study dis-
continuation. Fifty three out of 58 respondents (91%)
expressed a willingness to participate in future trials that
involved a phone surveillance system to track their fall
rates.

During the 4 weeks of surveillance, 19 (29%) participants
suffered 38 falls at their homes. The 65 participants
enrolled contributed 1498 person-days of follow-up
(mean = 23 days/person), yielding a fall rate of 25.4 falls/
1,000 person-days (95% CI: 17.3-33.4), for our full sam-
ple (age range 22-97). Fall rates were similar between age
groups: 25.5 falls/1,000 person-days for our < 64 year-old
subsample, and 25.2 falls/1,000 person-days for our > 65
year-old subsample. Sixty-three percent of the falls
occurred during the initial 2 weeks after hospital dis-
charge, with only 14 (37%) falls occurring during the final
two weeks after discharge. One participant suffered a hip
fracture. Twenty-three (35%) participants were readmit-
ted to the hospital. There were 3 deaths (5%), and 4 (6%)
nursing home placements. Fifteen participants (23%)
received physical and/or occupational therapy at home
during the 4 weeks of follow up.

Comparison of fallers and non-fallers
Data examining the risk factors for falls in the immediate
post-hospitalization period revealed no significant differ-
ences between the group of fallers and non-fallers in



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Table I: Baseline characteristics of study participants


Characteristic


N (%)


Age, mean SD*, (range)
Women
Race/ethnicity
African American
Caucasian
Number hospitalizations previous year
0
I
2
>3
History of falls prior to hospital admission
Ambulatory assistive device utilized at home prior to hospital admission (e.g. walker, cane, and wheelchair)
Diagnosis
Hypertension
Diabetes mellitus
CHF
Stroke
Dementia
Parkinson's Disease
Multiple falls during current hospital stay
Injury due to fall during current hospital stay
PT/OTt received during current hospital stay
Duration of hospital stay
< 7 days
7-14 days
> 15 days
Discharged home
Immediately
After a short term skilled nursing facility/rehab hospital stay


62.5 13, (22-97)
28 (43%)

49 (75%)
16 (25%)

27 (42%)
14 (22%)
10(15%)
14 (22%)
42 (65%)
30 (46%)

56 (86%)
34 (52%)
19 (29%)
12 (19%)
7(1 1%)
1 (1.5%)
16 (25%)
23 (35%)
44 (68%)

15 (23%)
25 (38%)
25 (38%)

46(71%)
19 (29%)


*SD = standard deviation.
tPT/OT = physical therapy/occupational therapy.


nearly all categories, including: age, use of ambulatory
assistive device, previous hospitalizations, previous fall
history, injury due to fall during hospital stay, and the
duration of the index hospitalization. Additionally there
were no significant differences found if participants were
discharged to a skilled care facility prior to arriving home
or if they received therapy (i.e., physical/occupational)
services during or after their hospitalization. Males were
not more likely to fall (p = 0.1), but sustained more falls
once discharged (p = 0.033). Persons who suffered multi-
ple falls during their current hospitalization were more
likely to fall (p = 0.056) and sustained a much higher rate
of falls once discharged (p = .008) (Table 2). After control-
ling for gender, the rate of falls following discharge
remained higher among persons who fell more than once
during hospitalization (p = 0.001).

Discussion
The immediate post-hospitalization period represents a
particularly high-risk time for adverse events [16,17],
including a high risk for falls [12,13]. One study reported


older adults who are discharged home after a medical ill-
ness have an increased fall rate in the first 2 weeks (8.0
falls per 1000 person-days) to 1 month (6.7 falls per 1000
person-days) [12], which is approximately two-fold
higher than rates (range 3.7 to 4.2 per 1,000 person-days)
seen for older adults in a hospitalized setting [3,6,18]. An
additional study revealed that older adults who were dis-
charged home with skilled-care (i.e., nursing or physical
therapy) had a higher incidence (20% vs. 8%) of falls
(compared with those who were not receiving skilled-
care) within the first 30-days after hospitalization [13].
These two studies also prospectively defined the pre and
post hospital discharge risk factors for falling in the imme-
diate post-hospitalization period [12,13]. Pre-hospital
discharge risk factors included: use of a walker, decline in
mobility, dependency in activities of daily living (ADL),
multiple falls during hospital stay, cognitive impairment,
multiple hospitalization in the year prior, and post hospi-
talization risk factors include: self report of confusion, use
of antidepressants, delirium, and poorer balance [12,13].




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Table 2: Characteristics of participants who suffered a fall compared to those who did not Four weeks post-hospital discharge


Variable


Non-Fallers Subjects who fell


< 65
>= 65
Gender
Male
Female
Multiple
hospitalizations
Yes
No
History of falls prior to
admission
Yes
No
Assistive ambulatory
devices at home
Yes
No
Multiple falls during
hospital stay
Yes
No
Injury due to fall during
hospital stay
Yes
No
PT/OTt during hospital
stay
Yes
No
Length of stay
< 14 days
>= 14 days
Discharge directly to
home
Yes
No
PT/OT after hospital
stay
Yes
No


(n = 46)
N (%)


24 (52%)
22 (48%)

23 (50%)
23 (50%)


19 (41%)
27 (59%)


28(61%)
18(39%)


20 (43%)
26 (57%)


8(17%)
38 (83%)


19 (41%)
27 (59%)


30 (65%)
16 (35%)

26 (57%)
20 (43%)


34 (74%)
12 (26%)


10(23%)
34 (77%)


(n = 19)
N (%)


12 (63%)
7(37%)

14(74%)
5 (26%)


5 (26%)
14(74%)


14(74%)
5 (26%)


10 (53%)
9 (47%)


8 (42%)
11 (58%)


4(21%)
15 (79%)


14(74%)
5 (26%)

13 (68%)
6 (32%)


12(63%)
7 (37%)


5 (26%)
14(74%)


P-value (fall)* Person Days Number of falls P-value (rate)t


0.102


0.397



0.40 I



0.589



0.056



0.159



0.572



0.417


0.389



0.751


0.98 I


0.033


0.766



0.148



0.087



0.008



0.184



0.352



0.107


0.72



0.208


*Chi-square or fisher's exact test.
tPoisson regression.
tPT/OT = physical therapy/occupational therapy.
Missing data with this characteristic: n = 63 subjects with 1477 days of follow up.


To our knowledge, this is the first study to specifically fol-
low hospital fallers at home. Previous studies [12,131
have followed hospitalized patients home after discharge,
however they did not identify whether the participant had
a fall in the hospital prior to their discharge home. Our
findings may have important clinical implications, as they
indicate that during the immediate 2-4 week post-hospi-
talization period there is a high risk of falls for patients
who sustained a fall during their hospital stay. Patients


who sustain a fall during their hospital stay represent a
considerable patient population as an estimated 2 to 7%
of all acute care hospital admissions are reported to suffer
a fall during their hospitalization [3,6,7].

Our findings are consistent with those of Mahoney who
examined falls in the 65 year and older population [12],
in that the number of falls were almost two-fold higher in
the first two weeks after hospital discharge then in later


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weeks. However even though our sample population
included middle-aged and younger participants, our rate
of falls was considerably higher. Mahoney, for example
reported 6.7 falls per 1000 person-days in the first 4 weeks
after hospitalization while our fall rate was 25.4 falls per
1000 person-days for the full sample (age range 22-97)
and 25.2 falls per 1000 person-days for our 65 year and
older subsample after the first 4 weeks. This nearly four-
fold higher fall rate may be attributed to our differing par-
ticipant inclusion criteria in which we only enrolled
patients who had fallen during their hospital stay. A
higher fall rate in this subpopulation of hospital fallers is
not unexpected given the numerous studies that have
shown a history of falling during the previous year is a
strong predictor of future falls [19-21].

The fall rate method is the most reliable method recom-
mended for measuring the incidence of falls [22], how-
ever the fall rate statistic may artificially be inflated if the
sample includes a small amount of participants who
repeatedly fall. However when compared to previous
studies our study had a considerably higher percentage of
overall participants who fell. For instance, previous stud-
ies have revealed incidence of falling in the first 4 weeks
after returning home as high as 15% in the 65 year and
older population [12] and 14% in the 70 year old and
older population [13]. While our incidence of falls was
29% for the full sample (age range 22-97) and 24% for
our > 65-year-old sub sample after the first 4 weeks. Again
this nearly two-fold higher percentage of overall partici-
pants who fell may be attributed to our differing partici-
pant inclusion criteria.

In our study, participants who had injured themselves
while falling in the hospital were no more likely to fall at
home. A possible interpretation of these results may be
that participants who had recently injured themselves
from a fall in the hospital may have become more cau-
tious of falling again. Previous studies have shown that
older adults who suffer an injury due to a fall are more
fearful of falling [23,24] which can lead to more cautious
protective behaviors that could contribute to the preven-
tion of further falls [24].

Surprisingly, there was no difference in rate or proportion
of fallers among older and younger participants. It is plau-
sible that factors related to recovery from illness, rather
than baseline measures of frailty, determine fall risk after
hospitalization. Thus, interventions aimed at reducing
falls after hospitalization should not necessarily focus on
a specific age group.

Interestingly, those who went to a skilled nursing facility
or rehabilitation center prior to going home and those
who received physical and/or occupational therapy dur-


ing or after hospitalization were not less likely to fall.
However the participant's functional mobility level was
not fully assessed at hospital admission/discharge, at
skilled nursing facility/rehabilitation center, or upon
arrival home. Prior research suggests that 'new' and 'recur-
rent' fallers are likely to have functionally deteriorated
more during their hospital stay (i.e., bathing, dressing, toi-
leting, bed-chair transfers) and have a higher risk of falling
upon arriving home [13]. Additional research may help
differentiate the level of functional recovery needed to
prevent falls after hospital discharge.

Although this was a prospective study, it has several limi-
tations. First, although our response rate (86%) and with-
drawal rate (4.6%) in our study was very good, the
generalizability of our study is limited as only 65 patients
(38%) out of 171 in-hospital fallers were followed.
Extrapolation to other settings may also be limited due to
our small sample size (65) and our study taking place in a
single urban tertiary care medical center. Also, the assess-
ment of pre-hospitalization risk factors was based on self-
report and potentially subject to recall bias. However, in a
previous fall study [12], a comparison between partici-
pants' and proxies' recall of participants' pre-hospitaliza-
tion risk factors found no obvious reporting bias. Third,
the numbers of falls reported upon arrival home are self
reported and the circumstances are not well known. It is
possible that falls at home that do not result in injury are
less likely to be reported than falls that do result in injury.

Conclusion
As hospital length of stay has decreased, and transitions of
health care have become increasingly fragmented, the
post-hospitalization period represents a high-risk time.
Previous studies have found that older adults who are dis-
charged home after a medical illness have an increased fall
rate [12,13]. Our results suggest that a high risk for falls is
not limited to the 65 and older post-hospitalized popula-
tion. All adults who have fallen during their hospitaliza-
tion have a high rate of falls during their immediate post-
hospitalization period, especially patients who have
fallen on more than one occasion during their hospitali-
zation. Our study suggests that weekly phone calls are well
accepted by patients and may potentially be a feasible
hospital-based surveillance system to monitor post-dis-
charge fall risk factors and could be utilized to test future
interventions that reduce falls in this high-risk popula-
tion.

Competing interests
The authors declare that they have no competing interests.

Authors' contributions
RD contributed to the statistical analysis and interpreta-
tion of the data, and drafted and revised the manuscript.


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GV made substantial contributions to the conception and
design of the study, acquisition of the original data and
interpretation of the data. CJ lead in the acquisition of the
original data. MC made substantial contributions to the
conception and design of the study, acquisition of the
original data. LK made substantial contributions to the
conception and design of the study, acquisition of the
original data and interpretation of the data. LM made sub-
stantial contributions to the conception and design of the
study, and interpretation of the data. RS conceived and
designed the study, performed the statistical analyses,
drafted and revised the manuscript. RD, GV, LM, CJ, MC,
LK, and RS all critically revised the manuscript. All authors
read and approved the final manuscript.

Acknowledgements
Stephen T. Miller for his administrative input and to Linda Rosenblatt, Meth-
odist Healthcare Nurse Managers who performed the fall evaluations.

Funding sources and related paper presentations: The work was presented
in preliminary form at the 2007 Annual Scientific Meeting of the American
Geriatrics Society, and was supported in part by National Institute on Aging
grant RO I AG025285 and by the Department of Veterans Affairs, Veterans
Health Administration, Office of Research and Development, Health Serv-
ices Research & Development, and Office of Academic Affiliations Health
Fellowship Program.

The views expressed in this article are those of the authors and do not nec-
essarily reflect the position or policy of the Department of Veterans Affairs,
the National Institute on Aging, or the National Institutes of Health.

Sponsor's role: The sponsors had no role in the design, methods, subject
recruitment, data collections, analysis, or preparation of the manuscript.

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Pre-publication history
The pre-publication history for this paper can be accessed
here:

httn-//www hinmedrentral crnm/1 471 -91/ /I/qI/nrenih


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