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Original Investigation | ONLINE FIRST

Patient Education to Prevent Falls Among Older Hospital Inpatients:  A Randomized Controlled Trial FREE

Terry P. Haines, PhD; Anne-Marie Hill, MS; Keith D. Hill, PhD; Steven McPhail, BS; David Oliver, MD; Sandra Brauer, PhD; Tammy Hoffmann, PhD; Christopher Beer, MBBS
[+] Author Affiliations

Author Affiliations: Allied Health Clinical Research Unit, Physiotherapy Department, Monash University and Southern Health, Cheltenham, Victoria, Australia (Dr Haines); Physiotherapy Department (Ms Hill and Dr Brauer) and Division of Occupational Therapy (Dr Hoffmann), University of Queensland, Brisbane, Queensland, Australia; LaTrobe University, Northern Health and the National Ageing Research Institute, Melbourne, Victoria, Australia (Dr Hill); Institute of Health and Biomedical Innovation and School of Public Health, Queensland University of Technology, and Centre for Functioning and Health Research, Queensland Health, Brisbane (Mr McPhail); School of Community and Health Sciences, City University, London, England (Dr Oliver); and Western Australia Centre for Health and Ageing, Centre for Medical Research, and School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia (Dr Beer).


Arch Intern Med. 2011;171(6):516-524. doi:10.1001/archinternmed.2010.444.
Text Size: A A A
Published online

Falls are a leading patient safety incident event in general hospitals and are especially common in older patients.1 Approximately 30% of falls result in injury,2 the consequences of which may cause increased length of stay or risk of institutionalization for the patient,3 and legal complaint with subsequent litigation against the health service.4

Randomized trials of single interventions to prevent falls in hospitals have not identified a statistically significant reduction in falls outcomes.58 Multifactorial interventions have also been investigated with mixed results.2,911 A recent Cochrane review of these trials12 found that although multifactorial interventions appeared effective for preventing falls in hospitals, no recommendations could be made regarding effective components of these multifactorial interventions. In addition, compared with individual interventions, multifactorial falls programs may (1) be more difficult and costly to implement, (2) create confusion for individual patients, and (3) reduce the effectiveness of constituent components.13 Hence, there is need to identify single intervention strategies that prevent falls across a mixture of hospital wards.

A promising intervention is the patient education program used as a part of the first targeted multifactorial program shown to prevent falls in a randomized trial.2 The education program involved providing written information coupled with 1-to-1 follow-up with a research occupational therapist. Surprisingly, exploratory analyses revealed that the intervention was effective (~ 50% reduction) in people with impaired cognitive function as well as in those with intact cognitive function, although contamination by other interventions included in that trial clouds these results.14 This finding led authors to recommend further investigation of patient education in isolation to determine if this intervention was effective in isolation and equally effective for patients who have intact vs those with impaired cognitive function. The present study addresses this recommendation by comparing 2 models of providing patient education to prevent in-hospital falls vs usual care.

DESIGN, PARTICIPANTS, AND SETTING

A 3-group randomized controlled trial with recruiters, data collectors, and statistical analyst blind to group allocation, was undertaken.15 Potential participants were older adults admitted to acute (orthopedic and acute-respiratory medicine) and subacute (geriatric assessment and rehabilitation) wards of the Princess Alexandra Hospital, Brisbane, Australia, and the acute (medical-surgical) and subacute (restorative–stroke rehabilitation) wards of Swan Districts Hospital, Perth, Australia. Patients were excluded if (1) they were too ill to provide informed consent, as determined by hospital staff, until discharge, death, or transfer to a nonstudy ward; or (2) if they had previously participated in the trial.

INTERVENTIONS

Two models of a patient education program were tested. The first (complete program) involved providing written and video-based materials and 1-to-1 follow-up with a health professional (physiotherapist) trained to provide this program at the patient's bedside. The content and progression of this education program was based on the health-belief model and included presentation of epidemiologic falls data (frequency and outcomes), causes of falls, self-reflection of individual risk, problem area identification, development of preventive strategies and behaviors, goal setting, and goal review.16 Video materials were subjected to extensive testing and consumer feedback,17 and the overall program underwent incremental cost-effectiveness analysis economic modeling to ensure feasibility of the delivery approach.18 Video materials were viewed by patients using a portable digital video disk player with a 9-inch screen and external head phones. Bedside curtains were drawn during the 1-to-1 follow-up to minimize contamination with participants not allocated to this group. One-to-1 follow-up sessions were aimed to be completed during the first week of patient involvement in the study. The number of actual sessions provided was at the discretion of the research physiotherapists providing the follow-up.

The second model (materials only) involved providing the written and video-based materials without the trained health professional follow-up. Assistance was provided by the trained health professional to use the portable digital video disk player for viewing of the video materials.

Both interventions were provided in addition to usual ward-based care.

CONTROL

A usual-care-only control group (control) received no specific falls prevention education from the research team members. Usual ward-based care varied between and within hospitals though it primarily consisted of falls risk screening using locally developed instruments, use of risk alert items (arm bands), generic interventions (eg, nursing checklist to prompt activities such as a regular toileting program and regular visual observation of patients), and additional 1-to-1 nursing for patients with acute agitation and/or confusion at extreme risk of falls. Physical restraint was not a front-line method for managing patients with agitation and/or confusion at either of the participating sites. Multidisciplinary input (eg, medical, nursing, physiotherapy, occupational therapy) was routinely provided on all wards, although therapists such as physiotherapists and occupational therapists provided more intensive input (ie, daily 1-hour sessions) on subacute rehabilitation wards.

MEASUREMENTS

The primary outcome measure was participant falls. The definition of a fall used in this study was the World Health Organization definition: “an event which results in a person coming to rest inadvertently on the ground or floor or other lower level.”19 Prestudy training was provided to hospital staff on study wards regarding classification of falls and procedures for recording falls on incident reports using previously developed video materials.20 Falls data were collated from 3 sources during the trial: computerized incident reports, hand searching of individual patient medical notes, and weekly patient interviews (or at patient discharge if earlier than 1 week), and falls captured through any of these approaches were included. It was considered important to use multiple sources of data collection for the primary outcome owing to identified limitations of using single sources.2123

Numerous participant demographic measures were taken at the baseline assessment, including the Short Portable Mental Status Questionnaire (SPMSQ)24 as a screen of cognitive function where scores of 7 of 10 or below indicated impairment. This cut point corresponded to 23 of 30 or below on the Mini-Mental State Examination (the cut point used in the previous subgroup analysis of the education program14) when 455 available Mini-Mental State Examination scores were regressed against SPMSQ scores from this baseline demographic data set. The Geriatric Depression Scale25 and the EQ-5D26 (formerly EuroQol) health-related quality of life instruments were also administered (Table 1).

Table Graphic Jump LocationTable 1. Participant Demographics and Baseline Assessment Outcomesa

Time spent by trained health professionals providing the complete program was recorded session by session. The trained health professional at the Princess Alexandra Hospital site also recorded the written behavior modification goals that were set by participants in the complete program and materials-only groups.

PROCEDURE
Recruitment

Participant flow through this study is presented in Figure 1. All patients admitted to subacute study wards were referred to researchers by clinical staff. Patients older than 60 years on acute wards who were expected to stay at least 3 more days were also referred. Those referred were approached for consent by researchers to participate as soon as practicable. Family members were approached for consent where treating clinicians had assessed the patient to have impaired cognitive function. Recruitment occurred between January 2008 and April 2009, with the final participant being discharged in October 2009. Participants recruited on one ward but later transferred to another ward participating in this study (eg, transferred from acute ward to rehabilitation ward) were observed until discharge to the community or a ward or facility not participating in this study.

Place holder to copy figure label and caption
Figure 1.

Study flowchart.

Graphic Jump Location
Randomization and Masking

A computer-generated, random allocation sequence (without permuted blocks) was developed by the principal investigator (T.P.H.), and the randomly allocated numbers were placed into opaque, consecutively numbered envelopes by 2 investigators (T.P.H. and S.M.). The randomization envelopes were kept in the locked research office at each site, and 1 envelope was opened for each participant in order of recruitment on completion of the baseline assessment by the trained health professionals providing the intervention at each site (A.-M.H. and S.M.), who were unaware of the participant's result from the baseline assessment. The trained health professionals then provided the materials-only intervention or the complete program to participants as soon as practicable following this random allocation sequence.

Research assistants who approached participants for consent also completed the baseline assessments, weekly falls reviews, and discharge assessments and were blind to group allocation. Data, with mock codes for group allocation (inserted by S.M.), were forwarded to the principal investigator (T.P.H.), who undertook the study interim analysis and final data analysis procedures. A blinding survey was also distributed to clinical staff members (nursing and allied health) caring for participants during the final month of the study recruitment period, asking the staff members which group they believed their patients had been allocated to.

Analysis

Falls outcomes were divided into 3 categories: the rate of falls, the proportion of patients who experienced 1 or more falls (fallers), and the rate of injurious falls. The rate of falls was measured in events per 1000 patient-days. Injurious falls were defined as falls resulting in bruising, laceration, fracture, loss of consciousness, or patient reports of persistent pain. All analyses were conducted with participants in their assigned groups and were adjusted for whether the patient was treated on a subacute ward during the study (given the imbalance between groups in this factor and the impact this factor has on length of stay and rate of falls).2,10

The rate of falls and rate of injurious falls per 1000 patient-days outcomes were compared across groups using Andersen-Gill Cox recurrent events survival analysis with clustering by participant and robust variance estimates.27,28 The proportion of patients who incurred 1 or more falls was compared between groups using logistic regression. For these analyses, an initial model was constructed that included an interaction term between the group variables and the dichotomous variable of whether a patient's admission SPMSQ score was 7 of 10 or less. Where significant interaction was identified, simple effects were investigated for participants with intact cognitive function separately from those with impaired cognitive function.

The Andersen-Gill Cox recurrent events survival analysis approach models data under the assumption of proportional hazards. Nelson-Aalen plots displaying the cumulative hazard curves for each group were used to investigate this assumption. Where there was graphical evidence of this assumption being violated, negative binomial regression was used instead.

Statistical power for this study was calculated using 1000 bootstrap simulations of patient-level data previously collected from the Australian hospital setting,2 and the results indicated that our experiment would have 80% power to detect a difference between groups in the rate of falls of 30%. This assumed a sample size of 390 patients per group, a falls rate of 15.7 per 1000 patient-days in the group with the higher falls rate, and a 2-tailed alpha of .05. An additional 12 patients per group were recruited (additional 3%) to account for potential dropouts, creating a per-group size of n = 402 (total, n = 1206).

Deviation From Published Protocol

The published protocol for this trial did not include detail on use of negative binomial regression where the proportional hazards assumption did not hold, nor did it include adjustment for whether the participant was treated on a subacute ward during the study. These modifications were made in light of the distribution of trial data collected. Examination of the interaction effect between intervention group and cognitive impairment was not included in the published protocol despite the previously stated intention of the authors to examine this interaction.14

TRIAL REGISTRATION AND ETHICAL APPROVAL

This trial was registered with the Australia New Zealand Clinical Trials Registry (ACTRN12608000015347) on January 11, 2008. Ethical clearance was provided by the medical research ethics committee of the University of Queensland and the human research ethics committees of the Princess Alexandra Hospital and Swan Districts Hospital.

Baseline and demographic characteristics of participants allocated to each group are summarized in Table 1. Participants in each group were broadly similar, although a noticeable difference was evident for the proportion of participants allocated to each group who were recruited from a subacute ward. There were no control participants provided with either of the intervention conditions, but some participants allocated to the intervention conditions did not receive their intervention for reasons presented in Figure 1.

There were 247 falls across the study sample and 97 injurious falls (Table 2 and Table 3). Five falls resulted in fractures (control: pubic rami and sacrum in one case and olecranon in another; materials only: distal radius and first metacarpal in one case and distal radius and rib in another; and complete program: orbital fossa and C2 vertebra). Pairwise comparisons did not reveal significant differences between groups overall (Table 2, Table 3, and Figure 2). Interaction plots between group allocation and cognitive impairment for each fall outcome (Figure 3) and statistical investigation of these revealed significant interaction for each falls outcome (P <.05).

Place holder to copy figure label and caption
Figure 2.

Nelson-Aalen cumulative hazard curves for rates of falls and rates of injurious falls outcomes.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Interaction plots between group allocation and cognitive function (intact/impaired) on falls outcomes.

Graphic Jump Location
Table Graphic Jump LocationTable 2. Between-Group Comparisons on Fall-Related Outcomes
Table Graphic Jump LocationTable 3. Between-Group Comparisons on Fall-Related Outcomesa

The rate of falls was significantly lower among participants with intact cognitive function and allocated to the complete program group (4.01 falls per 1000 patient-days) compared with the rate among similar participants allocated to the control and materials-only groups (8.72 falls per 1000 patient-days and 8.18 falls per 1000 patient-days, respectively), and the proportion of these patients who became fallers was lower in the complete program group than in the control group (6% vs 11%). The unadjusted number needed to treat with the complete program to prevent 1 patient becoming a faller relative to the control group was 32.9; and to prevent 1 fall, it was 15.4. The proportion of cognitively intact participants in the complete program group who fell was significantly lower than that in the control group (6% vs 11%). There was a trend toward a reduction in the rate of injurious falls among cognitively intact participants in the complete program group compared with those in the control group.

Among participants with impaired cognitive function, those allocated to the complete program incurred a significantly higher rate of injurious falls per 1000 patient-days than participants in the control group (7.49 vs 2.89). However, there were no serious injuries (fractures) incurred by any of these patients, and the proportion of participants with impaired cognitive function who fell was comparable (complete program, 26%; control, 24%).

The median (interquartile range) time spent by the trained health professional setting up the multimedia materials and in face-to-face contact with participants in the complete group was 25 (20-36) minutes, with a maximum of 200 minutes for 1 participant. Of the 280 patients allocated to the complete program group at the Princess Alexandra Hospital site, 273 patients recorded a total of 700 goals in relation to behavior modification in their education materials. The most common goal (142 patients) related to asking for help, followed by identifying environmental hazards (131 patients), using walking aids or other aids (97 patients), waiting for help after it has been asked for (71 patients), wearing safe footwear or clothing (38 patients), and doing more exercise to get stronger and better balance (34 patients). Of the 299 patients allocated to the materials-only intervention at the Princess Alexandra Hospital site, 31 patients recorded a total of 75 goals. The most common goals related to asking for help and waiting for help to arrive once it had been asked for (14 patients each), followed by identifying environmental hazards (9 patients) and using aids (8 patients).

The cross-sectional hospital staff blinding survey revealed that of 54 study participants, only 16 had their group allocation correctly identified by their primary care nurse (29%) (κ = −0.05), and 17 had their group correctly identified by their treating physiotherapist (31%) (κ = −0.06). No adverse events were reported directly from interaction with the education materials.

The 2 models of patient education did not significantly reduce falls outcomes across the entire sample. This study was one of the few falls prevention randomized trials to specifically target cognitively impaired patients for recruitment, and this decision was made on the basis of encouraging findings from an earlier trial. An exploratory subgroup analysis revealed that the effect of the complete program (with trained health professional follow-up) was modified by whether the patient had cognitive impairment for each of the 3 falls outcomes examined. For cognitively intact patients, the complete program produced a relatively consistent and sizeable reduction (~ 50%) across each of the falls outcomes examined, and the difference was significant in 2 of these outcomes. The complete program also demonstrated a significant reduction in rate of falls among cognitively intact participants relative to the materials-only group. The magnitude of reduction in falls outcomes was comparable with results from previous research examining an earlier version of this intervention in the hospital setting.14 Hence, there is now growing evidence that the complete program may be an effective strategy for preventing falls among hospital patients who are cognitively intact.

Many of the strategies pursued by patients as a result of participating in the complete program focused on (1) working more effectively with staff members caring for them; (2) identifying environmental hazards; and (3) using appropriate aids, equipment, and clothing. These proposed strategies form a plausible mechanism of action for reducing falls among these patients and highlight the importance of behavioral elements in the causes of falls in this setting. However, the complete program was not an effective strategy and may even be harmful for patients with impaired cognitive function: the rate of injurious falls was higher in this group. Cognitive impairment can limit the ability of patients to adhere to the planned safety-promoting behaviors and is a reason why an education program might not be beneficial among these patients. However, reasons why it may be harmful are less apparent. It is possible that the education process made these participants more willing to report injuries from falls, such as pain, to the blinded research assistants. In support of this notion, we found a discrepancy in the proportion of injurious falls to total falls reported by patients in the materials-only (43% of falls were injurious) and complete program (49% injurious) groups compared with those in the control group (29% injurious).

Our study was limited by its inability to conceal from study participants their group allocations, although this limitation is common for education-based interventions. It may have influenced results because participants allocated to the intervention groups may have been particularly motivated to avoid falls by virtue of knowing they had been allocated to the intervention groups. This enhanced level of motivation might not have been present had the complete program been provided outside the research context.

The simple randomization approach used in the present study generated groups that were not equal in total size or proportion recruited from subacute hospital wards. The investigators had anticipated that a simple randomization approach would be sufficient for generating groups of relatively equal size and comparable baseline demographics given the number of participants being recruited. However, the discrepancy in proportion of participants recruited from subacute hospital wards necessitated adjustment for this in the analyses to account for the effect of this imbalance.

A high proportion of patients admitted to study wards were not approached for consent to enter this study. Study recruiters were not present 7 days per week at participating sites, and periods of leave meant that not all patients admitted could be approached before they were within 3 days of anticipated discharge, particularly on acute wards.

The present study has strengths relative to previous work in this field. Most importantly, this study has evaluated the efficacy of a single intervention for the prevention of falls in hospitals. Previous studies that have demonstrated a reduction in falls in this setting have all used multifactorial interventions, and it was very difficult to determine which elements were the most important.2,9,11

The present study has not only investigated patient education in isolation, but it has analyzed 2 models of patient education so that the important elements within this approach can be further identified. As a result, we now know that low-cost, materials-only educational approaches are unlikely to be of benefit.

This study also used the most rigorous approach to collection of falls data (primary outcome) in a randomized trial to date. This is particularly important because falls prevention research in hospitals commonly relies on reports from third parties (hospital clinicians) who are commonly not blinded to the research hypothesis or participant group allocation and who have been shown to be inconsistent in their approach to classifying and reporting falls.20,22 In the present study, a research assistant blinded to participant group allocation collated data not only from medical records and computerized incident reports but also from direct, weekly patient interviews. It was impossible to blind hospital staff to participant group allocation in the present study, but the surveys of hospital staff members revealed that they were largely unaware of participant group allocation.

Further research is warranted to examine the efficacy of the complete program targeted at cognitively intact patients and used within the context of a broader falls-prevention program that uses other strategies to reduce falls among cognitively impaired patients. Such an intervention may need to take the form of a complex intervention that can adapt to the specific strengths and limitations of individual wards. Even with the education intervention investigated in the present trial, the cost-effectiveness of this approach is likely to vary between acute and subacute wards owing to the higher rate of falls and slower throughput on subacute wards; thus, the cost-effectiveness of this and future interventions should also be examined.

Correspondence: Terry P. Haines, PhD, Allied Health Clinical Research Unit, Physiotherapy Department, Monash University and Southern Health, Kingston Centre, Kingston Road, Cheltenham, Victoria 3192, Australia (terrence.haines@med.monash.edu.au).

Accepted for Publication: July 31, 2010.

Published Online: November 22, 2010. doi:10.1001/archinternmed.2010.444

Author Contributions: Dr Haines had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Haines, A.-M. Hill, K. D. Hill, McPhail, Oliver, Brauer, and Hoffmann. Acquisition of data: Haines, A.-M. Hill, McPhail, and Beer. Analysis and interpretation of data: Haines, A.-M. Hill, K. D. Hill, Oliver, Hoffmann, and Beer. Drafting of the manuscript: Haines, McPhail, and Oliver. Critical revision of the manuscript for important intellectual content: Haines, A.-M. Hill, K. D. Hill, McPhail, Oliver, Brauer, Hoffmann, and Beer. Statistical analysis: Haines and A.-M. Hill. Obtained funding: Haines, K. D. Hill, and Brauer. Administrative, technical, and material support: Haines, A.-M. Hill, K. D. Hill, McPhail, Brauer, Hoffmann, and Beer. Study supervision: Haines, A.-M. Hill, McPhail, Oliver, Brauer, Hoffmann, and Beer.

Financial Disclosure: None reported.

Funding/Support: This trial was supported by National Health and Medical Research Council (Australia) (NHMRC) project grant number 456097 (Drs Haines, Hill, Brauer, Oliver, and Hoffmann), an NHMRC Career Development Award (Dr Haines), and a Menzies Research Scholarship (Ms Hill).

This article was corrected for a typographical error on March 28, 2011.

US Department of Veterans Affairs, National Center for Patient Safety 2004 Falls Toolkit. http://www4.va.gov/ncps/SafetyTopics/fallstoolkit/index.html. Accessed April 2009
Haines  TPBennell  KLOsborne  RHHill  KD Effectiveness of targeted falls prevention programme in subacute hospital setting: randomised controlled trial. BMJ 2004;328 (7441) 676- 679
PubMed
Aditya  BSSharma  JCAllen  SCVassallo  M Predictors of a nursing home placement from a non-acute geriatric hospital. Clin Rehabil 2003;17 (1) 108- 113
PubMed
Oliver  DKillick  SEven  TWillmott  M Do falls and falls-injuries in hospital indicate negligent care—and how big is the risk? a retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. Qual Saf Health Care 2008;17 (6) 431- 436
PubMed
Haines  TPBell  RAVarghese  PN Pragmatic, cluster randomized trial of a policy to introduce low-low beds to hospital wards for the prevention of falls and fall injuries. J Am Geriatr Soc 2010;58 (3) 435- 441
PubMed
Mayo  NEGloutney  LLevy  AR A randomized trial of identification bracelets to prevent falls among patients in a rehabilitation hospital. Arch Phys Med Rehabil 1994;75 (12) 1302- 1308
PubMed
Tideiksaar  RFeiner  CFMaby  J Falls prevention: the efficacy of a bed alarm system in an acute-care setting. Mt Sinai J Med 1993;60 (6) 522- 527
PubMed
Donald  IPPitt  KArmstrong  EShuttleworth  H Preventing falls on an elderly care rehabilitation ward. Clin Rehabil 2000;14 (2) 178- 185
PubMed
Healey  FMonro  ACockram  AAdams  VHeseltine  D Using targeted risk factor reduction to prevent falls in older in-patients: a randomised controlled trial. Age Ageing 2004;33 (4) 390- 395
PubMed
Cumming  RGSherrington  CLord  SR  et al. Prevention of Older People's Injury Falls Prevention in Hospitals Research Group, Cluster randomised trial of a targeted multifactorial intervention to prevent falls among older people in hospital. BMJ 2008;336 (7647) 758- 760
PubMed
Stenvall  MOlofsson  BLundström  M  et al.  A multidisciplinary, multifactorial intervention program reduces postoperative falls and injuries after femoral neck fracture. Osteoporos Int 2007;18 (2) 167- 175
PubMed
Cameron  IDMurray  GRGillespie  LD  et al.  Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Database Syst Rev 2010; (1) CD005465
PubMed10.1002/14651858.CD005465.pub2
Campbell  AJRobertson  MC Rethinking individual and community fall prevention strategies: a meta-regression comparing single and multifactorial interventions. Age Ageing 2007;36 (6) 656- 662
PubMed
Haines  TPHill  KDBennell  KLOsborne  RH Patient education to prevent falls in subacute care. Clin Rehabil 2006;20 (11) 970- 979
PubMed
Hill  AMHill  KBrauer  S  et al.  Evaluation of the effect of patient education on rates of falls in older hospital patients: description of a randomised controlled trial. BMC Geriatr 2009;914
PubMed
Janz  NKBecker  MH The Health Belief Model: a decade later. Health Educ Q 1984;11 (1) 1- 47
PubMed
Hill  AMMcPhail  SHoffmann  T  et al.  A randomized trial comparing digital video disc with written delivery of falls prevention education for older patients in hospital. J Am Geriatr Soc 2009;57 (8) 1458- 1463
PubMed
Haines  TKuys  SSMorrison  GClarke  JBew  P Cost-effectiveness analysis of screening for risk of in-hospital falls using physiotherapist clinical judgement. Med Care 2009;47 (4) 448- 456
PubMed
World Health Organization, Definition of a fall. www.who.int/violence_injury_prevention/other_injury/falls/en/index.html. Accessed January 15, 2010
Haines  TPMassey  BVarghese  PFleming  JGray  L Inconsistency in classification and reporting of in-hospital falls. J Am Geriatr Soc 2009;57 (3) 517- 523
PubMed
Sari  ABSheldon  TACracknell  ATurnbull  A Sensitivity of routine system for reporting patient safety incidents in an NHS hospital: retrospective patient case note review. BMJ 2007;334 (7584) 79
PubMed
Haines  TPCornwell  PFleming  JVarghese  PGray  L Documentation of in-hospital falls on incident reports: qualitative investigation of an imperfect process. BMC Health Serv Res 2008;8254
PubMed
Hill  AMHoffmann  THill  K  et al.  Measuring falls events in acute hospitals-a comparison of three reporting methods to identify missing data in the hospital reporting system. J Am Geriatr Soc 2010;58 (7) 1347- 1352
PubMed
Pfeiffer  E A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc 1975;23 (10) 433- 441
PubMed
Sheikh  JIYesavage  JABrooks  JO  III  et al.  Proposed factor structure of the Geriatric Depression Scale. Int Psychogeriatr 1991;3 (1) 23- 28
PubMed
Rabin  Rde Charro  F EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001;33 (5) 337- 343
PubMed
Therneau  TMHamilton  SA rhDNase as an example of recurrent event analysis. Stat Med 1997;16 (18) 2029- 2047
PubMed
Robertson  MCCampbell  AJHerbison  P Statistical analysis of efficacy in falls prevention trials. J Gerontol A Biol Sci Med Sci 2005;60 (4) 530- 534
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Study flowchart.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Nelson-Aalen cumulative hazard curves for rates of falls and rates of injurious falls outcomes.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Interaction plots between group allocation and cognitive function (intact/impaired) on falls outcomes.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Participant Demographics and Baseline Assessment Outcomesa
Table Graphic Jump LocationTable 2. Between-Group Comparisons on Fall-Related Outcomes
Table Graphic Jump LocationTable 3. Between-Group Comparisons on Fall-Related Outcomesa

References

US Department of Veterans Affairs, National Center for Patient Safety 2004 Falls Toolkit. http://www4.va.gov/ncps/SafetyTopics/fallstoolkit/index.html. Accessed April 2009
Haines  TPBennell  KLOsborne  RHHill  KD Effectiveness of targeted falls prevention programme in subacute hospital setting: randomised controlled trial. BMJ 2004;328 (7441) 676- 679
PubMed
Aditya  BSSharma  JCAllen  SCVassallo  M Predictors of a nursing home placement from a non-acute geriatric hospital. Clin Rehabil 2003;17 (1) 108- 113
PubMed
Oliver  DKillick  SEven  TWillmott  M Do falls and falls-injuries in hospital indicate negligent care—and how big is the risk? a retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. Qual Saf Health Care 2008;17 (6) 431- 436
PubMed
Haines  TPBell  RAVarghese  PN Pragmatic, cluster randomized trial of a policy to introduce low-low beds to hospital wards for the prevention of falls and fall injuries. J Am Geriatr Soc 2010;58 (3) 435- 441
PubMed
Mayo  NEGloutney  LLevy  AR A randomized trial of identification bracelets to prevent falls among patients in a rehabilitation hospital. Arch Phys Med Rehabil 1994;75 (12) 1302- 1308
PubMed
Tideiksaar  RFeiner  CFMaby  J Falls prevention: the efficacy of a bed alarm system in an acute-care setting. Mt Sinai J Med 1993;60 (6) 522- 527
PubMed
Donald  IPPitt  KArmstrong  EShuttleworth  H Preventing falls on an elderly care rehabilitation ward. Clin Rehabil 2000;14 (2) 178- 185
PubMed
Healey  FMonro  ACockram  AAdams  VHeseltine  D Using targeted risk factor reduction to prevent falls in older in-patients: a randomised controlled trial. Age Ageing 2004;33 (4) 390- 395
PubMed
Cumming  RGSherrington  CLord  SR  et al. Prevention of Older People's Injury Falls Prevention in Hospitals Research Group, Cluster randomised trial of a targeted multifactorial intervention to prevent falls among older people in hospital. BMJ 2008;336 (7647) 758- 760
PubMed
Stenvall  MOlofsson  BLundström  M  et al.  A multidisciplinary, multifactorial intervention program reduces postoperative falls and injuries after femoral neck fracture. Osteoporos Int 2007;18 (2) 167- 175
PubMed
Cameron  IDMurray  GRGillespie  LD  et al.  Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Database Syst Rev 2010; (1) CD005465
PubMed10.1002/14651858.CD005465.pub2
Campbell  AJRobertson  MC Rethinking individual and community fall prevention strategies: a meta-regression comparing single and multifactorial interventions. Age Ageing 2007;36 (6) 656- 662
PubMed
Haines  TPHill  KDBennell  KLOsborne  RH Patient education to prevent falls in subacute care. Clin Rehabil 2006;20 (11) 970- 979
PubMed
Hill  AMHill  KBrauer  S  et al.  Evaluation of the effect of patient education on rates of falls in older hospital patients: description of a randomised controlled trial. BMC Geriatr 2009;914
PubMed
Janz  NKBecker  MH The Health Belief Model: a decade later. Health Educ Q 1984;11 (1) 1- 47
PubMed
Hill  AMMcPhail  SHoffmann  T  et al.  A randomized trial comparing digital video disc with written delivery of falls prevention education for older patients in hospital. J Am Geriatr Soc 2009;57 (8) 1458- 1463
PubMed
Haines  TKuys  SSMorrison  GClarke  JBew  P Cost-effectiveness analysis of screening for risk of in-hospital falls using physiotherapist clinical judgement. Med Care 2009;47 (4) 448- 456
PubMed
World Health Organization, Definition of a fall. www.who.int/violence_injury_prevention/other_injury/falls/en/index.html. Accessed January 15, 2010
Haines  TPMassey  BVarghese  PFleming  JGray  L Inconsistency in classification and reporting of in-hospital falls. J Am Geriatr Soc 2009;57 (3) 517- 523
PubMed
Sari  ABSheldon  TACracknell  ATurnbull  A Sensitivity of routine system for reporting patient safety incidents in an NHS hospital: retrospective patient case note review. BMJ 2007;334 (7584) 79
PubMed
Haines  TPCornwell  PFleming  JVarghese  PGray  L Documentation of in-hospital falls on incident reports: qualitative investigation of an imperfect process. BMC Health Serv Res 2008;8254
PubMed
Hill  AMHoffmann  THill  K  et al.  Measuring falls events in acute hospitals-a comparison of three reporting methods to identify missing data in the hospital reporting system. J Am Geriatr Soc 2010;58 (7) 1347- 1352
PubMed
Pfeiffer  E A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc 1975;23 (10) 433- 441
PubMed
Sheikh  JIYesavage  JABrooks  JO  III  et al.  Proposed factor structure of the Geriatric Depression Scale. Int Psychogeriatr 1991;3 (1) 23- 28
PubMed
Rabin  Rde Charro  F EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001;33 (5) 337- 343
PubMed
Therneau  TMHamilton  SA rhDNase as an example of recurrent event analysis. Stat Med 1997;16 (18) 2029- 2047
PubMed
Robertson  MCCampbell  AJHerbison  P Statistical analysis of efficacy in falls prevention trials. J Gerontol A Biol Sci Med Sci 2005;60 (4) 530- 534
PubMed

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