Hospital Fall Prevention: A Systematic Review of Implementation, Components, Adherence, and Effectiveness

RAND Corporation, Santa Monica, California.
Journal of the American Geriatrics Society (Impact Factor: 4.57). 03/2013; 61(4). DOI: 10.1111/jgs.12169
Source: PubMed
ABSTRACT
To systematically document the implementation, components, comparators, adherence, and effectiveness of published fall prevention approaches in U.S. acute care hospitals.
Systematic review. Studies were identified through existing reviews, searching five electronic databases, screening reference lists, and contacting topic experts for studies published through August 2011.
U.S. acute care hospitals.
Studies reporting in-hospital falls for intervention groups and concurrent (e.g., controlled trials) or historic comparators (e.g., before–after studies).
Fall prevention interventions.
Incidence rate ratios (IRR, ratio of fall rate postintervention or treatment group to the fall rate preintervention or control group) and ratings of study details.
Fifty-nine studies met inclusion criteria. Implementation strategies were sparsely documented (17% not at all) and included staff education, establishing committees, seeking leadership support, and occasionally continuous quality improvement techniques. Most interventions (81%) included multiple components (e.g., risk assessments (often not validated), visual risk alerts, patient education, care rounds, bed-exit alarms, and postfall evaluations). Fifty-four percent did not report on fall prevention measures applied in the comparison group, and 39% neither reported fidelity data nor described adherence strategies such as regular audits and feedback to ensure completion of care processes. Only 45% of concurrent and 15% of historic control studies reported sufficient data to compare fall rates. The pooled postintervention incidence rate ratio (IRR) was 0.77 (95% confidence interval = 0.52–1.12, P = .17; eight studies; I2: 94%). Meta-regressions showed no systematic association between implementation intensity, intervention complexity, comparator information, or adherence levels and IRR.
Promising approaches exist, but better reporting of outcomes, implementation, adherence, intervention components, and comparison group information is necessary to establish evidence on how hospitals can successfully prevent falls.

Full-text

Available from: Susanne Hempel
CLINICAL INVESTIGATIONS
Hospital Fall Prevention: A Systematic Review of
Implementation, Components, Adherence, and Effectiveness
Susanne Hempel, PhD,* Sydne Newberry, PhD,* Zhen Wang, PhD,* Marika Booth, MS,*
Roberta Shanman, MS,* Breanne Johnsen, BS,* Victoria Shier, MPA,* Debra Saliba, MD, MPH,*
†‡
William D. Spector, PhD,
§
and David A. Ganz, MD, PhD*
OBJECTIVES: To systematically document the implemen-
tation, components, comparators, adherence, and effective-
ness of published fall prevention approaches in U.S. acute
care hospitals.
DESIGN: Systematic review. Studies were identified
through existing reviews, searching five electronic databas-
es, screening reference lists, and contacting topic experts
for studies published through August 2011.
SETTING: U.S. acute care hospitals.
PARTICIPANTS: Studies reporting in-hospital falls for
intervention groups and concurrent (e.g., controlled trials)
or historic comparators (e.g., beforeafter studies).
INTERVENTION: Fall prevention interventions.
MEASUREMENTS: Incidence rate ratios (IRR, ratio of
fall rate postintervention or treatment group to the fall
rate preintervention or control group) and ratings of study
details.
RESULTS: Fifty-nine studies met inclusion criteria. Imple-
mentation strategies were sparsely documented (17% not
at all) and included staff education, establishing commit-
tees, seeking leadership support, and occasionally continu-
ous quality improvement techniques. Most interventions
(81%) included multiple components (e.g., risk assessments
(often not validated), visual risk alerts, patient education,
care rounds, bed-exit alarms, and postfall evaluations).
Fifty-four percent did not report on fall prevention mea-
sures applied in the comparison group, and 39% neither
reported fidelity data nor described adherence strategies
such as regular audits and feedback to ensure completion
of care processes. Only 45% of concurrent and 15% of his-
toric control studies reported sufficient data to compare fall
rates. The pooled postintervention incidence rate ratio
(IRR) was 0.77 (95% confidence interval = 0.521.12,
P = .17; eight studies; I
2
: 94%). Meta-regressions showed
no systematic association between implementation inten-
sity, intervention complexity, comparator information, or
adherence levels and IRR.
CONCLUSION: Promising approaches exist, but better
reporting of outcomes, implementation, adherence, inter-
vention components, and comparison group information is
necessary to establish evidence on how hospitals can suc-
cessfully prevent falls. J Am Geriatr Soc 61:483–494, 2013.
Key words: fall prevention; implementation; hospital;
systematic review
I
n-hospital falls are a significant clinical, legal, and regu-
latory problem, but information on effective fall reduc-
tion is lacking. The Centers for Medicare and Medicaid
Services no longer reimburses hospitals for in-hospital falls
with trauma.
1
As the U.S. population ages, fall prevention
is more relevant than ever; older, frail individuals are more
prone to falls, and the consequences of falls are more
severe.
2,3
Preventing falls in U.S. acute care hospitals poses par-
ticular challenges, given that patients are acutely ill and
average only 4.9 days in the hospital.
4
This compressed
acuity places a greater burden on staff to keep patients
safe, so results from fall prevention interventions in long-
term care facilities may not apply to acute care settings.
Similarly, results from the international literature, where
hospital stays are longer, may not generalize to U.S. hospi-
tals.
Fall prevention programs are typically complex,
involving multiple components that depend on leadership
involvement and the cooperation of frontline staff from
multiple disciplines. Programs may require potent monitor-
ing strategies to ensure that staff adhere to implemented
From *RAND Corporation, Santa Monica, California ;
Veterans Affairs
Greater Los Angeles Healthcare System, Los Angeles, California;
University
of California at Los Angeles/JH Borun Center, Los Angeles, California;
§
Agency for Healthcare Research and Quality, Rockville, Maryland; and
David Geffen School of Medicine, University of California at Los Angeles,
Los Angeles, California.
Address correspondence to Susanne Hempel, RAND Corporation,
Southern California Evidence-based Practice Center, 1776 Main Street,
Santa Monica, CA 90407. E-mail: susanne_hempel@rand.org
DOI: 10.1111/jgs.12169
JAGS 61:483–494, 2013
© 2013, Copyright the Authors
Journal compilation © 2013, The American Geriatrics Society 0002-8614/13/$15.00
Page 1
care protocols. Recent reviews provide limited evidence for
acute care settings.
3,57
It was hypothesized that the con-
fluence of an effective strategy to implement interventions
into clinical practice in acute care settings, the intervention
components chosen, the type of monitoring strategies used
to ensure adherence, and the baseline level of care intensity
provided in the comparison group would determine a fall
prevention program’s success.
A systematic review was performed documenting
implementation strategies, intervention components and
comparators, adherence information, and the effectiveness
of published fall prevention approaches in U.S. acute care
hospitals.
METHODS
Studies were identified through existing reviews and an
update search for original studies. The Database of
Abstracts of Reviews of Effects (DARE), the Cochrane
Database of Systematic Reviews, PubMed (applying a sys-
tematic review search filter), and existing fall prevention
toolkits or guidelines were searched to identify reviews.
PubMed, Cumulative Index to Nursing and Allied Health
Literature (CINAHL), and Web of Science from January
2005 were searched to August 2011 for studies that exist-
ing reviews had not yet captured.
3,5,6,8,9
A combination of
free text words and the Medical Subject Heading term
“accidental falls” restricted to hospital settings and
English-language publications was used. The search was
not limited to a set of known interventions, so diverse
approaches were identified; the strategy is documented in
detail elsewhere.
10
Additional studies were identified
through reference mining of included studies and consulta-
tion with experts in hospital-based fall prevention. Separate
searches were performed for psychometric properties of risk
assessment scales applied in included studies.
10
Two independent reviewers screened titles and abstracts
and full text publications. One reviewer abstracted study
details, and a second checked them. Two indepen-
dent reviewers rated implementation strategy intensity,
intervention complexity, comparator information, and
adherence levels. A statistician extracted study outcomes.
Discrepancies were resolved through team discussion. The
review protocol has been registered in PROSPERO, an
international register of systematic reviews (ID
CRD42011001593).
Inclusion Criteria
Studies had to meet the following criteria:
Participants
Studies evaluating fall reduction interventions in hospital-
ized individuals were eligible for inclusion. Studies to
reduce falls among staff, community-dwelling individuals
visiting the hospital for treatments (outpatients), or day-
hospital patients were excluded.
Interventions
Eligible interventions had to be aimed at reducing falls in
the hospital. Studies evaluating discharge planning
interventions focusing on the time after the hospital stay
and outpatient programs were excluded. Studies evaluating
interventions to reduce restraints, the risk of injuries from
falls, or the effect of falls were excluded unless combined
with other interventions aiming to reduce falls.
Design
Studies that reported on patient falls in the hospital for an
intervention group and a concurrent or historic compara-
tor (randomized controlled trials, controlled clinical trials,
cohort studies comparing two cohorts, beforeafter stud-
ies, time series) were eligible for inclusion in the review.
Descriptions of interventions without data or without
comparators and case studies of individual patients were
excluded.
Outcome
Studies had to report on the outcome of inpatient falls.
Only studies reporting numerical data on the intervention
and a comparison group or data on reduction in the num-
ber of falls or rate of falls relative to the comparator were
considered. Publications were excluded if they plotted fall
events on graphs without reporting numerical data,
reported only a range of reductions across departments
without exact incidence data for intervention and control
groups, reported only descriptive and nonnumerical assess-
ments (“fall rates improved”), or reported only on falls
after discharge and other long-term effects.
Setting
Eligible studies were restricted to acute care U.S. hospital
settings. Studies aimed at nursing homes, residential care
facilities, and other long-term nonhospital care facilities
were excluded. Facilities that reported average lengths of
stay of more than 30 days were deemed not to be acute
care and were excluded.
Data Abstraction and Analysis
Information on study design, setting, participant character-
istics, implementation strategies, intervention target, inter-
vention components and comparators, information on
adherence to care processes, and study results were
extracted, as were type of hospital and wards and the
description of the participant sample. Information on all
descriptions of how the intervention was introduced into
clinical practice (implementation strategies) were extracted.
The main target of the intervention (staff, equipment,
patients) was classified, and information on all reported
intervention components (care processes used in the inter-
vention group), context information relevant to fall pre-
vention (existing fall prevention measures also present in
the control group or before the intervention), and which
tools were used was extracted. Intervention components
aimed at all patients were differentiated from care pro-
cesses for individuals identified as being at high risk of fall-
ing. Information on strategies fostering adherence to the
implemented care processes was documented, and data on
the intervention fidelity was extracted.
To broadly categorize the included studies, the inten-
sity of the implementation strategy, the complexity of the
484 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
Page 2
intervention, the information on fall prevention activities
in the comparison group, and the level of adherence to the
intervention were rated as low, medium, or high. The rat-
ings and further details of the rating criteria are docu-
mented in Table S1. Intraclass correlations (ICCs) were
used to estimate rater agreement.
Information on number of fallers, number of falls, fall
rate (per 1,000 patient days), and number eligible to fall in
both groups was extracted. To evaluate the fall rate, an
incidence rate ratio (IRR) was estimated for each study.
The IRR is the ratio of the postintervention (or treatment
group) fall rate to the preintervention (or control group)
fall rate. An IRR less than 1 indicates a lower postinter-
vention (or treatment group) fall rate than the preinterven-
tion (or control group) rate. The number of falls was used
to estimate the standard deviation of the IRR.
Studies were pooled in a random effects model
estimating the IRR and 95% confidence interval (CI).
Meta-regressions were used to investigate the effect of
implementation, intervention complexity, comparator
information, and adherence. Heterogeneity was assessed
using the I
2
statistic. Potential for publication bias was
assessed using the Egger regression and the Begg rank test.
RESULTS
Figure 1 shows the study flow. The searches identified
3,180 publications. The electronic update search for fall
prevention interventions retrieved 2,473 publications. The
full text of 766 publications was obtained and screened
against the inclusion criteria. Table S1 summarizes the
details of the 59 studies meeting inclusion criteria. Interr-
ater agreements (ICCs) were 0.87 (implementation inten-
sity), 0.62 (intervention complexity), 0.69 (comparator
information), and 0.75 (adherence levels).
Study Characteristics
Studies were published over a period of 28 years. Studies
with concurrent controls and historic controls were strati-
fied. Four randomized controlled trials (RCTs) and seven
nonrandomized studies reporting on an intervention and a
concurrent control group were identified. Two RCTs were
randomized at the patient level; two were cluster RCTs
randomizing hospital wards or entire hospitals to the inter-
vention or the control group. Forty-eight studies evaluated
the success of interventions by comparing the number of
falls or fall rates with those from a historic period before
implementation of the intervention. The historic-control
studies included a small number of time series reporting
on three or more time points before and after the introduc-
tion of the intervention.
Studies varied in the reach of the intervention; 39 tar-
geted selected hospital wards or units, 16 evaluated
changes in an entire hospital, and four evaluated more
than one hospital. Consequently, the number of included
patients varied widely, ranging from fewer than 50 to
more than 10,000 eligible participants per study.
Implementation
Table 1 shows the employed implementation strategies
(efforts to introduce the intervention into clinical practice),
including staff education, establishing teams, piloting the
intervention with input from front-line personnel to refine
the intervention, leadership support, and continuous qual-
ity improvement procedures such as Plan-Do-Study-Act or
the Institute for Healthcare Improvement Framework for
Spread to promote unit-level buy-in. Ten studies (17%)
reported no information on how the intervention
was implemented. Twenty-nine studies (49%) reported
Update search in electronic databases
(n = 2,473)
Additional publications identified
through other sources
(n = 707)
Records screened
(n = 3,180)
Records excluded
(n = 2,414)
Full-text obtained and
assessed for eligibility
(n = 766)
Full-text articles excluded,
with reasons
(n = 396)
Setting – 169
Intervention – 96
Outcome – 54
Design – 45
Duplicates – 18
Language – 6
Participants – 5
Not Available – 3
Studies included in the
review
(n = 59)
Background
(reviews, guidelines,
toolkits, multiple
publications on
included studies)
(n =308)
Figure 1. Flow diagram.
JAGS APRIL 2013–VOL. 61, NO. 4 FALL PREVENTION INTERVENTIONS IN HOSPITALS 485
Page 3
Table 1. Implementation, Intervention Components, Comparator, and Adherence in Included Studies
Implementation Strategies
Intervention Components
for All Patients
Intervention Components for
High-Risk Patients Only Comparator Information
Adherence Strategies
and Fidelity
Staff education to raise awareness of fall
prevention or training for specific tools
37,
1215,1719,2132,34,35,3845,4749,51,53,55,57,58
Fall risk assessment
24,6,13,14,1621,
23,26,2934,3640,4345,4751,53,5559
Alert signs placed on beds, doors,
patients’ records
26,13,1721,26,29,31,32,
36,38,40,41,4345,48,49,5153,55,56,59
Risk assessment
2,4,6,10,14,15,29,
33,34,48,50,56
Audit and feedback on
adherence to processes
of care
19,11,12,15,17,19,21,27,
28,31,34,37,39,4244,49,51,57
Interdisciplinary team, task
force or other hospital committee
established
13,17,18,26,28,29,31,33,34,36,38,41,
42,48,49,53,55,57,59
Postfall evaluations
12,13,17,2022,
26,29,34,38,47,49,51,5557
Care, safety, and toileting
rounds
6,7,12,13,16,1821,24,29,30,34,38,4043,
45,47,48,52,53,5557
Restraints
1012,24,31,48,51,54,58
Monitoring and disseminating
data on falls
5,6,12,14,19,28,32,
42,43,53,56,57,59
Piloting the intervention in selected
units
2,26,29,31,36,39,44,45,47,49,53,55,59
Patient and family education
4,6,26,
33,34,45,47,49,53,5557
Bed- or chair-exit
alarm systems
1,4,6,9,10,12,17,2123,26,27,
29,30,32,34,40,41,43,47,51,55,57,58
Alert signs placed on beds,
doors, patients’ records
2,4,6,
15,32,56
Fall prevention included in
electronic health
record
2,4,4547,49
Activities to raise leadership awareness
or gain support
3,12,13,42,44,57,59
Care, safety, and toileting
rounds
7,16,21,38,41,52
Patient and family education
2,13,14,17,
1921,2932,36,41,43,44,48,50
Other strategies
1,2,4,6,811,15,
22,27,29,32,41,4851,53,54,56,57
Other adherence-promoting
strategies
5,8,9,1517,19,21,22,
27,28,31,32,43,45,53,57,59
Continuous quality improvement techniques;
Plan-Do-Study-Act, Institute for Healthcare
Improvement spread framework
2,28,42,49,52,55,57
Awareness posters
5,26,33,56
Identification wrist
bands
3,6,17,21,26,29,34,41,44,47,49
No information on
existing fall prevention
measures
3,5,7,13,1621,23,25,26,
28,30,3540,4247,52,55,59
No specified adherence
strategy and no fidelity
data
10,13,14,18,20,2326,29,30,
33,35,36,38,40,41,48,50,52,54,55,58
Other implementation
strategies
8,14,17,2729,3436,47,49,53,57
Clutter-free, safe environment
efforts
6,45,50,53
Bed side rails
1,4,20,38,4345,48,50,54
No specified implementation
strategy
1,911,16,20,37,46,50,54
Medication review
14,16,33,35
Low beds
1,4,27,29,34,43,44,48
Low beds
45,50,53
Nonskid socks and footwear
1,20,26,36,43,44,47,48
Call lights within reach
enforcement
34,53
Use of sitters
21,40,50,5356,59
Nonskid socks and footwear
21,50
Care plan communicated at
change of shift report
5,13,17,18,38,49,51,55
Other intervention
components
4,8,15,17,19,26,27,
3335,41,42,45,47,50,5257
Moving high-risk patients close
to nurses’ station or cluster
6,12,13,29,30,42,47,59
Medication review
6,26,44,46,49,57
Call lights within reach
enforcement
4,7,20,43,48,50
Clutter-free, safe environment
efforts
18,26,38,44,50
Bedside commode
1,29,43
Other intervention
components
15,10,1215,1722,25,26,2934,3742,
44,45,4751,5357
References in this table are found in the online supporting information.
486 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
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Table 2. Psychometric Properties of Risk Assessment Tools Used in Included Studies
Published Tool
Psychometric
Performance
Source Tool Description
Acute
Care Data
a
U.S. Data
b
Reliability Across
Studies
Validity Across
Studies
ADAPT Fall Assessment
Tool
15
Individual study
15
ADAPT computerized information
system, fall risk embedded into
routine assessment documentation,
allows customized interventions
for specific patient risks,
risk information integrated into
care plan, report sheets,
care conferences
Yes Yes n/a Concurrent validity: risk
assessment correlates
0.96 with Hendrich
scale scores
Berryman Predisposition
for Falling scale
44
(applied
to at-risk patients)
Review, data from
1
study60
Assessed domains: age, mental
status, length of stay,
elimination, falling within
the past 6 months, visual
impairment, confined to
chair, blood pressure
No Yes n/a Face validity: most
falls (3 VA patient care
units observed for 3
months) were in patients
aged 70
Hendrich, Hendrich II Fall Risk Model /
Assessment
4,29,33,36,56
Review, data from
1 study
61
Assessed domains: mental
state, gait and mobility, fall
history, elimination, diagnosis,
continence, mood,
dizziness, weakness
Yes n/a n/a Predictive validity:
sensitivity 0.77,
specificity 0.72
I’M SAFE Fall Risk Assessment Tool,
Children’s Hospital Denver
45
Individual study
62
Assessed domains: environment,
history of falls, intravenous
medications, orthopedic and
muscular, rehabilitation and
occupational and physical therapy,
seizures andepilepsy
Yes Yes Internal
consistency
(a) 0.69
n/a
Innes Score; St Francis
Memorial Hospital
Standard Care Plan for the
High-Risk Patient
31,32,48
Systematic review,
data from 1 study
63
Assessed domains: previous trauma,
disorientation, impaired judgment,
sensory disorientation, muscle
weakness, multiple diagnoses,
language barrier
n/a No n/a Predictive validity:
sensitivity 0.89 (95%
CI = 0.780.96),
specificity 0.74 (95%
CI = 0.720.75);
PPV 0.07 (95%
CI = 0.050.10),
NPV 1.00
(95% CI = 0.991.00),
OR = 23 (95%
CI = 10.155.5)
Morse Falls Scale
1,2,6,16,28,39
Systematic review,
data from 4 studies
64
Assessed domains: history of
falling, presence of secondary
diagnosis, use of ambulatory
aids, administration of
intravenous therapy, type of
gait, mental status
Yes n/a n/a Predictive validity:
sensitivity 0.720.96,
specificity 0.510.83
JAGS APRIL 2013–VOL. 61, NO. 4 FALL PREVENTION INTERVENTIONS IN HOSPITALS 487
Page 5
Table 2 (Contd.)
Published Tool
Psychometric
Performance
Source Tool Description
Acute
Care Data
a
U.S. Data
b
Reliability Across
Studies
Validity Across
Studies
Systematic review, data
from 2 studies
63
Score of 45 used as cutoff Yes No Predictive validity: sensitivity
0.730.96, specificity
0.540.75, PPV 0.040.10,
NPV 0.991.00.
Systematic review, data
from 3 studies
65
6 items Yes n/a Interrater
agreement
0.960.98
Predictive validity:
sensitivity 0.720.83,
specificity 0.51 0.68
Schmid Fall Risk Assessment
Tool
49,51
Systematic review, data
from 1 study
63
Assessed domains: gait,
confusion, assisted toileting,
fall history, anticonvulsants;
5 items; score of 3 used
as cutoff
n/a Yes n/a Predictive validity:
sensitivity 0.93 (95%
CI = 0.800.98),
specificity 0.78 (95%
CI = 0.730.83),
PPV 0.37 (95%
CI = 0.270.47),
NPV 0.99 (95%
CI = 0.961.00),
OR = 44.3 (95%
CI = 13.2172.4)
Systematic review, data
from 2 studies
65
17 items; score 3 used
as cutoff
Yes Yes Interrater
agreement 0.88
Predictive validity:
sensitivity 0.910.93,
specificity 0.25 0.78
Timed Up & Go test
17
Systematic review, data
from 1 study
65
Score 1012 used as
cutoff
No n/a Interrater
agreement
0.560.99
Construct validity:
judged as “good”
Unpublished tool, tool shown
and risk factors
reported
3,13,14,18,20,21,23,26,30,34,37,38,43,47,50,53–55,57,58
n/a n/a n/a n/a n/a n/a
Tool not described
19,40,59
n/a n/a n/a n/a n/a n/a
No risk assessment
5,712,22,24,25,27,35,41,42,46,52
n/a n/a n/a n/a n/a n/a
References in this table are found in the online supporting information.
a
Tool tested in acute care setting.
b
Applied in U.S. organization.
n/a = not available, not applicable; VA = Veterans Affairs; ADAPT = Assess: Disorientation, Activity, Postmedication, and Toileting.
488 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
Page 6
primarily staff education, often to raise awareness of fall
prevention or provide training for tools. Twenty studies
(34%) described a comprehensive implementation strategy
using continuous quality improvement models and a multi-
faceted strategy to integrate the intervention into clinical
practice.
Intervention Components
Table 1 shows intervention components documented in the
literature, stratified according to care process aimed at all
admitted patients and components applied only to patients
classified as being at high risk for falls. Common compo-
nents targeting all patients included fall risk assessment,
patient and family education, and structured postfall
evaluations. Commonly applied components for patients
identified as being at at high risk of falling included alert
signs placed on beds, doors, patient records, and call but-
tons in the nurses’ station; care, safety, and toileting
rounds and ambulation assistance; bed-exit alarms; educa-
tion; identification wrist bands or other markers; bed side
rails; use of sitters; low beds; nonskid footwear; moving
high-risk patients closer to the nurses’ station; communi-
cating the care plan; medication review; and enforcing that
call lights are within reach. Several studies used additional
and less-common approaches, such as designating a specifi-
cally equipped fall prevention room on the ward.
11
Most identified studies addressed fall prevention using
multiple components but 11 of 59 (19%) described one-
dimensional interventions such as the introduction of a
bed-exit alarm with or without fall risk assessment.
Twenty-six of all included studies (44%) were classified as
intense interventions combining a large number of care
processes with pertinent technology (e.g., bed-exit alarms,
computerized decision support) or regular and resource-
intense components such as staff providing scheduled
toileting or the use of sitters to supervise patients continu-
ously. The remaining studies (22/59, 37%) described a
limited number of different intervention components.
Most interventions (48/59, 81%) targeted primarily
healthcare provider behavior (e.g., introducing a new risk
assessment or care protocol) rather than patients directly
(e.g., through patient education) or equipment (e.g., intro-
duction of a new bed-exit alarm). Several studies empha-
sized the introduction of a standardized care plan
specifying universal and mandatory care processes trig-
gered by a given risk score. Interventions were often aimed
at improving the documentation and use of existing fall
prevention measures rather than introducing new care pro-
cesses.
Fall Risk Assessment
Forty-three (83%) studies incorporated patient-level fall
risk assessment. This assessment determined which inter-
vention components patients received. Table 2 shows the
risk assessment tools together with published reliability
and validity characteristics where available in the litera-
ture. The most commonly used published tool was the
Morse Fall Scale (6/43 studies). More than half of stud-
ies (23/43) used a tool without known psychometric
properties.
Comparator
Thirty studies (51%) did not report on existing, routine
fall prevention measures already in place before the inter-
vention or in a control group (the comparator of the
study). Twenty-three studies (39%) reported some existing
care processes such as risk assessment, whereas six (10%)
were identified that already had an intense fall prevention
program in place before the new intervention was estab-
lished.
Adherence Strategies and Fidelity Data
Table 1 shows the employed strategies aimed at facilitat-
ing adherence to the intervention components, care pro-
cesses, and use of selected tools. These included audit and
feedback of adherence to processes of care, monitoring
and disseminating fall data, and integrating risk assess-
ments into an electronic health record. Fidelity data (evi-
dence of the uptake of intervention components) was
reported in only 13 studies (22%). Twenty-three studies
(39%) neither reported data nor described an adherence
strategy.
Outcomes and Effectiveness Results
The majority of authors reported positive changes (Table
S1), although of 17 publications reporting a statistical test,
only eight indicated significant improvement. Five of 11
studies with concurrent controls reported sufficient detail
to calculate a fall rate, and the pooled intervention effect
(IRR) was 0.92 (95% CI = 0.651.30; P = .64). There
was evidence of heterogeneity across studies (I
2
: 68%).
Seven of 48 studies with historic controls (15%) reported
sufficient data to compare the fall rate before and after the
intervention. Twenty studies neither reported the fall rate
nor provided sufficient data to compute it; 21 studies
reported the fall rate without the number of falls in both
groups. The intervention effect across historical control
studies (IRR) was 0.77 (95% CI = 0.501.18; P = .23; I
2
:
95%; seven studies).
Table 3 shows the fall prevention approaches for the
12 studies for which an IRR could be calculated. Five of
the eight successful approaches (IRR < 1) described an
implementation strategy such as staff education; combined
a number of intervention components such as fall risk
assessment, education, alert signs, and bed-exit alarms;
and with one exception, audited adherence to the care pro-
cesses,
1216
but other multifaceted approaches were not
successful,
17
there were other, less complex, successful
approaches,
18
and the number of reported strategies was
not significantly different between studies.
Across all studies that reported fall rates before and
after the intervention (historic and concurrent control
group studies), the pooled postintervention effect (IRR)
was 0.77 (95% CI = 0.521.12; P = .17; eight studies
14
21
), as shown in Figure 2. There was evidence of substan-
tial statistical heterogeneity (I
2
: 94%). Omitting each study
in turn from the analysis showed a statistically significant
postintervention effect when excluding one study
21
(IRR = 0.67, 95% CI = 0.580.77) and a substantial
reduction of heterogeneity (I
2
: 39%).
JAGS APRIL 2013–VOL. 61, NO. 4 FALL PREVENTION INTERVENTIONS IN HOSPITALS 489
Page 7
Table 3. Evidence Table of Included Studies Reporting Fall Incidence Rate Ratios
Study Setting
Implementation Strategies Intervention Components
Staff Education
Team,
Task
Force
Pilot
Intervention
Leadership
Support
Continuous
Quality
Improvement,
Spread
Techniques Other
None
Specified
Fall
Risk
Assessment
Alert
Signs Education Rounds
Bed-
Exit
Alarms
Postfall
Evaluation
Bed
Side
Rails
Low
Beds
Identification
Band
Concurrent
control
Dykes, 2010
2
8 units in 4 urban
hospitals
XX XXX
Hunderfund,
2011
4
Neurology unit and
6 medical units in
tertiary care
hospital
X XXX X XX
Krauss, 2008
6
4 general medicine
floors in urban,
1,300-bed tertiary
care academic
hospital
X XXXXX XX
Padula, 2011
8
3 medicalsurgical
units in teaching
hospital
X
Spetz, 2007
10
Postneurosurgery
unit in acute care
hospital
XX
Before-after
study design
Barker,
1993
13
2 psychiatric units
in acute care
hospital
XX X X X X X X
Dacenko-
Grawe,
2008
21
325-bed teaching
hospital
X XXXXXX X
Geffre,
2006
23
6 medical units
(medical, oncology,
surgical, telemetry,
transitional care,
rehabilitation)
X XX
Lane, 1999
37
Medicalsurgical and
critical care units
in metropolitan
community
hospital
XX
Peterson, 2005
46
Medical, surgical,
neurology, and
gynecology
services of urban
720-bed tertiary
care hospital
X
Rainville,
1984
48
Medical surgical
units in
248-bed facility
XX X X X X X X
Weinberg,
2011
57
714-bed tertiary
care teaching
hospital
XX X X X X X X X X
Note: References in this table are found in the online supporting information.
a
Compared with a concurrent control group.
490 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
Page 8
Comparator; Existing
Strategies in Control Group Adherence Strategies
Fall Rate
Log Scale Fall
Incidence
Rate Ratio (95%
Confidence
Interval)
Nonskid
Footwear
Clutter-Free
Environment
Medication
Review Sitters
High-Risk
Near
Nurses
Other
Components
Risk
Assessment
Other
Strategies
No
Information
Monitoring
Data on
Falls
Care Audit/
Feedback
Other
Strategies
None
Specified
Before
or
Control
After or
Intervention
X X X X X 4.64 3.48
a
0.75
a
(0.551.02)
X X X X 2.99
5.69
4.12 1.38
a
(1.051.82)
0.72 (0.540.98)
X X X X X X X X 6.85 5.09
a
0.74
a
(0.531.05)
X X X X 2.80 3.20
a
1.14
a
(0.542.42)
X X X X 6.12 2.79
a
0.46
a
(0.101.99)
X X X X 6.84 5.10 0.75 (0.590.94)
X X X X X X 4.04 2.77 0.69 (0.560.84)
X X 2.04 1.52 0.75 (0.50. 1.12)
X X X 2.27 3.89 1.71 (1.491.97)
X X X 6.40 2.80 0.44 (0.270.70)
X X X X X 7.76 7.74 1.00 (0.581.71)
X X X X X X 3.60 1.94 0.54 (0.430.68)
JAGS APRIL 2013–VOL. 61, NO. 4 FALL PREVENTION INTERVENTIONS IN HOSPITALS 491
Page 9
Meta-Regressions and Publication Bias
Meta-regressions showed that, as the adherence level
increased, the IRR decreased (P = .005) in studies with
concurrent controls (five studies). This result indicates that
larger intervention effects were observed in studies with
greater evidence of adherence to intervention components,
although the effect was not replicated in the analysis com-
paring pre- and postintervention data (P = .79, eight stud-
ies). None of the meta-regressions showed a statistically
significant effect for implementation intensity, intervention
complexity, or comparator information.
The quality of the reporting may have confounded
results; excluding studies with little or no information and
comparing only medium- and high-intensity studies
showed a significant effect of intervention intensity
(P < .001), although this result was based on six prepost
data studies only and was not replicated in the studies
with concurrent controls (P = .70, four studies). The
adherence effect was significant in the sensitivity analysis
for concurrent controls (P = .001, four studies) but was
not present in the prepost data studies (P = .49, five stud-
ies).
In the few studies reporting analyzable data, no evi-
dence of publication bias was identified (controlled trials:
Egger test P = .75, Begg test P > .99, five studies; prepost
data analysis: Egger test P = .16, Begg test P = .71, eight
studies).
DISCUSSION
The literature was systematically screened, and 59 U.S.
acute care hospital studies reporting evaluations of fall
prevention approaches were identified. Only a fraction
reported sufficient data to compare fall rates, and pooled
estimates found no statistically significant intervention
effect. The implementation strategies were sparsely docu-
mented; most interventions included multiple components;
information on the comparator was often absent; and
many studies neither reported data on, nor described,
adherence strategies to monitor completion of care pro-
cesses.
Most interventions were unique approaches combining
a number of different components and care processes aim-
ing to prevent falls, such as risk assessment, visual alerts
indicating risk, patient and family education, care rounds,
bed-exit alarms, and postfall evaluations. Some compo-
nents, such as screening patients for fall risk, were
employed in almost all studies. A large number of inter-
ventions were applied only to patients identified as being
at high risk. The overall success of such interventions may
depend on the accuracy of the risk assessment in ensuring
that the right patient is targeted. More than half of the
included studies did not use published validated scales but
instead developed their own tools, for which no psycho-
metric data were reported. The sensitivity and specificity
of even well-known tools are limited; the author of
STRATIFY, one of the best-documented tools, concluded
that it may not be optimal for identifying high-risk indi-
viduals for fall prevention.
22
The large number of fall prevention studies identified
that reported on U.S. acute care hospitals could provide
great insight for clinicians and policy-makers on effective
and less-effective strategies for reducing the risk of falls,
but only a small proportion of studies reported sufficient
data to evaluate the effectiveness of their approach, partic-
ularly among historical control studies. Assessing changes
in the outcome of patient falls, a rare event that is subject
NOTE: Weights are from random effects analysis
Overall (I-squared = 94.1%, p = 0.000)
Hunderfund, 2011
20
Rainville, 1984
17
Lane, 1999
21
Peterson, 2005
18
Weinberg, 2011
16
Dacenko-Grawe, 2008
15
Geffre, 2006
19
Barker,1993
14
ID
Study
0.77 (0.52, 1.12)
0.72 (0.54, 0.98)
1.00 (0.58, 1.71)
1.71 (1.49, 1.97)
0.44 (0.27, 0.70)
0.54 (0.43, 0.68)
0.69 (0.56, 0.84)
0.75 (0.50, 1.12)
0.75 (0.59, 0.94)
IRR (95% CI)
0.77 (0.52, 1.12)
0.72 (0.54, 0.98)
1.00 (0.58, 1.71)
1.71 (1.49, 1.97)
0.44 (0.27, 0.70)
0.54 (0.43, 0.68)
0.69 (0.56, 0.84)
0.75 (0.50, 1.12)
0.75 (0.59, 0.94)
IRR (95% CI)
Favors PostIntervention Favors PreIntervention
1.5 1 1.5 2 2.5
Figure 2. Log scale fall incidence rate ratio (IRR) status before and after the intervention. CI = confidence interval.
492 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
Page 10
to fluctuation, is challenging; to evaluate the effect of an
intervention, the number of fallstogether with the num-
ber of patients at risk or the fall rateneeds to be
reported for similar study periods.
10
One study summariz-
ing a systematic review on fall prevention published in
1998 indicated that the usefulness of published evaluations
is limited because of small sample sizes, the research
design used, and study quality.
7
The current study found
the even more basic problem that data were not described
sufficiently to enable effects to be evaluated.
In the few studies that reported data, the pooled inter-
vention effect estimate was not statistically different from
the preintervention status or standard care control group.
Results of meta-analyses summarizing the international lit-
erature vary and report, for example, a statistically signifi-
cant effect for historic control studies but not for
controlled trials
23
or no consistent results across outcomes
(rate ratio vs number of fallers).
8
Patient falls are not a
novel problem in hospitals, so to understand the effect of
a new intervention, the comparator status (part of the
intervention context) needs to be known (which fall-reduc-
tion strategies were in place before the tested intervention
or in a concurrent control group). The comparator is an
important determinant of the success (the achieved change)
of the intervention. Unfortunately, fewer than half of the
included studies reported on existing, routine fall preven-
tion approaches present in the comparator group. Recent
publications have emphasized that, to comprehend study
effects, more information is needed on the context in
which interventions take place.
24
Similarly, details of the
implementation process have been singled out as a crucial
element in patient safety practice evaluations to advance
the science of patient safety,
25
but information on how a
fall prevention intervention was introduced into clinical
practice in the target organization, for example through
staff education or known continuous quality improvement
strategies, was seldom documented.
Individual study results varied, and there was evidence
of statistical heterogeneity between studies. It was hypoth-
esized that the implementation intensity, intervention com-
plexity, comparator information, and adherence to care
processes were effect modifiers for the effectiveness of
interventions to reduce falls, but the large majority of
included studies could not be statistically analyzed. Meta-
regressions showed some evidence of the importance of
adherence levels (data on whether the intervention took
place as intended and implemented care processes were
indeed adhered to) and the intensity of the intervention,
but effects were not consistent across available data.
Adherence strategies are of particular importance for long-
term changes. Initial success might not be maintained
because adherence to introduced care processes fades in
clinical practice, use of the introduced risk assessment tool
may not be sustained, and recommended measures may no
longer be systematically applied. Some barriers encoun-
tered in clinical practice included forgetting to remove
identification signs next to call lights after high-risk
patients were discharged and failing to educate new staff
about fall prevention programs.
26,27
This systematic review relied on published information.
The amount of reported details, in particular regarding
implementation and adherence strategies, may depend on a
journal’s word limit and preferences. Contacting primary
authors may have provided answers to unresolved ques-
tions, but fall prevention interventions are only as good as
their implementation and adherence strategies, and suffi-
cient data to communicate the nature of the comparator
and its intensity are crucial to understanding study effects.
The Standards for QUality Improvement Reporting Excel-
lence (SQUIRE) criteria provide detailed guidance for how
complex interventions to improve the quality of healthcare
delivery should be reported.
28
Low statistical power limited these quantitative analy-
ses. The absence of definitive findings should therefore not
be interpreted as evidence that implementation strategies,
intervention complexity, and level of adherence are unim-
portant. Until better data are available, readers may bene-
fit from reviewing the successful studies documented in
this review and pursuing approaches that are most com-
patible with their hospital culture and patient populations.
Promising approaches exist, but better reporting of
outcomes and detailed information on intervention compo-
nents and comparison groups, as well as the implementa-
tion strategy and adherence to care processes, need to be
included in published fall prevention evaluations to estab-
lish a strong evidence base for successful interventions to
reduce patient falls in hospitals.
ACKNOWLEDGMENTS
We thank Paul Shekelle (Veterans Affairs Greater Los
Angeles; Evidence-based Practice Center, RAND) and
Rhona L. Imcangco (Agency for Healthcare Research and
Quality (AHRQ)) for pertinent comments, and Tanja Perry
(RAND) and Aneesa Motala (RAND) for administrative
support.
Conflict of Interest: The editor in chief has reviewed
the conflict of interest checklist provided by the authors
and has determined that the authors have no financial or
any other kind of personal conflicts with this paper. This
project was funded under Contract HHSA290201000017I
TO #1 from the AHRQ. Additional support was provided
through the U.S. Department of Veterans Affairs, Veterans
Health Administration, Veterans Affairs Health Services
Research and Development (HSR&D) Service through the
VA Greater Los Angeles HSR&D Center of Excellence
(Project VA CD2 080121 and a locally initiated
project).
Author Contributions: Hempel S., Ganz D. A., Saliba
D., and Specter W. D.: designed the study. Shanman R.:
provided the literature searches. Hempel S., Wang Z.,
Ganz D. A., Shier V., and Newberry S.: extracted the data.
Johnsen B.: managed the data. Booth M.: performed the
statistical analyses. All authors contributed to interpreta-
tion of the data. Hempel S., Johnsen B., and Ganz D. A.:
drafted the manuscript. All authors provided critical
revisions to the final manuscript.
Sponsor’s Role: The opinions expressed in this docu-
ment are those of the authors and do not reflect the official
position of AHRQ or the Department of Veterans Affairs.
AHRQ and the Department of Veterans Affairs had no
role in the design, methods, subject recruitment, data col-
lections, analysis and preparation of this paper; the
expressed views are those of the authors.
JAGS APRIL 2013–VOL. 61, NO. 4 FALL PREVENTION INTERVENTIONS IN HOSPITALS 493
Page 11
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the
online version of this article:
Table S1. Evidence Table.
Please note: Wiley-Blackwell is not responsible for the
content, accuracy, errors, or functionality of any support-
ing materials supplied by the authors. Any queries (other
than missing material) should be directed to the corre-
sponding author for the article.
494 HEMPEL ET AL. APRIL 2013–VOL. 61, NO. 4 JAGS
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  • Source
    • "According to the analysis of fall incident reports, patients often fall during unassisted tasks such as toileting, ambulating, getting out of bed, and getting into or out of the bath [9][10][11]. To prevent inpatient falls, multidisciplinary interventions are necessary, including assessment, environment improvement, establishment of a care plan dependent on individual patient needs, use of adequate alarm devices for high-risk patients, and communication and information support for patients and caregivers [3,[12][13][14][15][16][17]. For these interventions, educational efforts can be important, as can effective measures of informing patients and caregivers of fall risk and preventive strategies [15,[17][18][19][20]. "
    Full-text · Article · Dec 2016
  • Source
    • "These in-hospital adverse events not only increase the length of hospital stay and cause extraneous medical expense but may also engender unnecessary medical disputes (Bates et al. 1995; Mion et al. 2012 ). Therefore, the implementation of preventive strategies for in-hospital falls has been an important practical issue in the hospital care (Hempel et al. 2013). However, the investigation of the in-hospital falls during the postoperative period is insufficient (Amador and Loera 2007; Church et al. 2011). "
    [Show abstract] [Hide abstract] ABSTRACT: Background In-hospital falls may result in serious clinical adverse consequences, but the effects of anesthesia in the occurrence of postoperative falls are still undetermined. Anesthesia may theoretically cause postoperative falls due to the residual pharmacologic and neuromuscular blocking effects of anesthetics. We retrospectively reviewed events of in-hospital falls occurred after anesthesia management to identify the incidence and risk factors of postanesthesia falls. Methods We reviewed the postanesthesia visit of patients received anesthesia in the Hualien Buddhist Tzu Chi General Hospital from January 2009 to December 2013. Falls happened within 24 h after anesthesia were recorded. The Poisson regression model was used for simultaneous analysis of the association between incidence proportion of postanesthesia falls and the potential risk factors. Results A total of 60,796 inpatients received anesthesia management over the past 5 years, and ten patients fell within 24 h after anesthesia. All cases happened in the general wards. Falls occurred more often at the bedside, presence of caregivers, and during the daytime. Patients underwent regional anesthesia, and old age significantly increased the risk of postanesthesia falls, while differences in gender and ASA physical status did not affect the occurrence of postanesthesia falls. Conclusions The overall incidence proportion of postanesthesia falls is 1.6 cases per 10,000 patients (95 % CI 0.006 to 0.026 %) over a 24-h observation period. Falls are more commonly happened during the less expected periods after operation and are increased in the elderly and patients received regional anesthesia. This study highlights that more comprehensive clinical practice guidelines for postoperative care should be exercised to prevent the in-hospital falls.
    Full-text · Article · Dec 2016
  • Source
    • "The causes are often aspects related to the physical environment and human impact, e.g., dizziness and lack of own responsibility [14]. Despite these factors, outdoor fall prevention has been neglected since most research has focused on falls occurring in the home or hospital environment [15, 16]. Risk factors differ between outdoor and indoor falls, e.g. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: Senior citizens are over-represented in injury statistics, and fall-related injuries are globally recognized as a major threat to their health and wellbeing. Outdoor falls are likely to occur among those who are active and healthy when walking or cycling. The objective of this study was to explore active senior citizens' experiences and perceptions of how their safety could be increased and their risk reduced in outdoor environments.
    Full-text · Article · Jul 2015
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