Evidence RUA

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Clinical Interventions in Aging 2019:14 145–154

Clinical Interventions in Aging

This article was published in the following Dove Medical Press journal: Clinical Interventions in Aging

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http://dx.doi.org/10.2147/CIA.s191832

effects of a fall prevention program in elderly: a pragmatic observational study in two orthopedic departments

Bodil røyset1

Bente A Talseth-Palmer2–4

stian lydersen5

Per g Farup6,7

1Department for Medicine and rehabilitation, Møre og romsdal hospital Trust, Ålesund, norway; 2Department for research, Innovation, education and Competence Development, Møre og romsdal hospital Trust, Molde, norway; 3Department of Clinical and Molecular Medicine, Faculty of Medicine and health sciences, norwegian University of science and Technology, Trondheim, norway; 4school of Biomedical sciences and Pharmacy, Faculty of health and Medicine, University of newcastle and hunter Medical research Institute, newcastle, nsW, Australia; 5regional Centre for Child and Youth Mental health and Child Welfare, Department of Mental health, Faculty of Medicine and health sciences, norwegian University of science and Technology, Trondheim, norway; 6Department of research, Innlandet hospital Trust, Brumunddal, norway; 7Unit for Applied Clinical research, Department of Clinical and Molecular Medicine, Faculty of Medicine and health sciences, norwegian University of science and Technology, Trondheim, norway

Purpose: Falls are a common adverse event experienced by elderly in hospitals. This study assessed the effects of a fall prevention program on the rate of fallers, the patient safety culture,

and patient-perceived safety.

Materials and methods: Two orthopedic departments in different towns in Norway partici- pated in the study. A comprehensive, multifactorial fall prevention program was implemented

in one of the departments, the other one was used for control. The changes in the outcomes in

the two departments from before to after the intervention were compared. All patients above

64 years of age admitted to the two departments in a 1-year period before and after the interven-

tion were included. All employees at the two departments were invited to participate in surveys

measuring the patient safety culture, and a selection of the patients reported patient-perceived

safety. The primary outcome was the rate of fallers. Secondary outcomes were the employees’

perceived patient safety culture (measured with the Safety Attitudes Questionnaire) and patient-

perceived safety (measured with Norwegian Patient Experience Questionnaire).

Results: Falls were registered in 114 out of 3,143 patients (3.6%) with 17,006 days in the hospital. Ten patients had two falls, giving a fall rate of 7.3 falls/1,000 days in the hospital. The

number of fallers before and after the intervention in the intervention department were 37/734

(5.04%) and 31/735 (4.22%), P=0.46, and in the control department, 25/811 (3.08%) and 21/863 (2.43%), P=0.46. The difference between the changes in the two departments was not statistically significant; 0.17% (95% CI: -2.49 to 2.84; P=0.90). There were also no significant differences in the changes in patient safety culture and patient-perceived safety.

Conclusion: The fall prevention program revealed no significant effect on the rate of fallers, the patient safety culture, or patient-perceived safety.

Keywords: accidental falls, accident prevention, adverse effects, patient safety, safety culture

Introduction The report “To Err is Human,” published in 1999, estimated adverse events in hospitals

to cause 44–98,000 deaths in the USA every year.1 The report draws attention to an

important health care-related concern and has resulted in a significant increase in

patient safety efforts, such as system-based interventions, practical clinical initiatives,

and research. In 2004, the WHO established the network World Alliance for Patient

Safety, which aims to coordinate, disseminate, and accelerate improvements in patient

safety worldwide.2 Systems for reporting adverse events are in use internationally for

quality assurance and patient safety.3–5

Worldwide, falls are one of the most commonly reported adverse events in hospitals

with prevalence rates in the order of 10 per 1,000 patient days or 5%–15% of the patients

Correspondence: Per g Farup Department of research, Innlandet hospital Trust, PB 104, n-2381 Brumunddal, norway Tel +47 9 481 8603 Fax +47 6 115 7437 email [email protected]

Journal name: Clinical Interventions in Aging Article Designation: Original Research Year: 2019 Volume: 14 Running head verso: Røyset et al Running head recto: Effects of a fall prevention program in elderly DOI: 191832

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røyset et al

and are associated with both minor and major injuries.6–8

Preventive measures have been taken with conflicting results.

Overall, fall prevention exercise interventions have shown no

effect, while vitamin D supplement has reduced the rate of

falls but not the risk of falls in elderly in nursing homes.9,10

Multifactorial interventions in hospitals have shown a reduc-

tion in the rate of falls and an inconclusive trend for the risk

of falling according to a Cochrane review.10 In large, fall pre-

vention measures in hospitals have been disappointing.10–13

Norway has since 1994 had a national system for report-

ing adverse events in hospitals.14 The database has been

used to plan and implement prevention activities related to

frequent and serious adverse events. Eleven percent of all

reports from the specialized health services were incidents

related to falls.14

In January 2011, the Norwegian health minister launched

a national patient safety campaign called “In Safe hands.”15

The campaign had three aims: 1) reduce patient-related

adverse events, 2) build sustainable systems and structures

for patient safety, and 3) improve the patient safety culture.

Hospitals and primary care units were invited to participate

in 16 specific and measurable areas for improvement; one

of the areas was fall prevention. One out of four orthopedic

departments at different sites in Møre og Romsdal Hospital

Trust, Norway, participated actively in the national multi-

factorial fall prevention program.

This pragmatic observational study aimed to compare

the differences in the changes from before to after the fall

prevention intervention in the rate of fallers, the employees’

perceived patient safety culture, and the patient experienced

safety between the department with the intervention and the

department without the intervention in the same hospital

trust. The hypothesis was that the fall intervention program

would reduce the rate of fallers in the intervention department

(ID) compared with the department without the intervention.

A secondary aim was to study predictors of fallers.

Materials and methods study design The study was performed in two orthopedic departments in

Møre og Romsdal Hospital Trust, located in different cities.

The hospital trust serves a population of 265,000 inhabitants.

The ID served a population of 62,000 inhabitants and had

~1,400 admissions each year. The corresponding numbers for the control department (CD) were 95,000 inhabitants

and 2,000 admissions. From November 2012 to September

2013, the fall prevention measures were implemented in one

of the orthopedic departments hereafter referred to as the ID.

The intervention was performed as proposed by the national

patient safety campaign “In safe hands.”15 The department

that did not participate in the safety campaign was used for

comparison and will be referred to as the CD. Comparisons

were made between two departments in the same hospital

trust with approximately the same size and organizational

culture, the same expectations and challenges from the

director and the board, and well-matched patients from the

same region.

In both departments, all falls were registered in a 12-month

period before (from November 2011 to October 2012) and

after (from November 2013 to October 2014) the interven-

tion. Before (in April 2012) and after (in April 2014) the

intervention, all employees in both departments were invited

to participate in a survey, measuring patient safety culture.

The survey was a part of the national patient safety campaign

and performed anonymously.

Similarly, two cross-sectional studies conducted by The

Norwegian Institute of Public Health were performed among

a selection of patients admitted to the orthopedic department

in 2012 and 2014 (before and after the intervention). They

were invited to participate in a survey measuring patient-

perceived safety. Figure 1 shows the timeline for data used

in different analyses.

Participants The fall registration included all patients above 64 years of

age admitted to the ID and CD during the two registration

periods and with a stay of at least 24 hours’ duration.

All employees at the two departments were invited to par-

ticipate in surveys measuring the patient safety culture. The

exact number of employees in the two departments asked to

participate was unknown. Since the surveys were performed

anonymously, no information was available on the subjects’

characteristics, and therefore no matching was possible.

Randomly selected patients from the two orthopedic

departments were invited to participate in surveys measuring

patient-experienced safety. The surveys were part of national

surveys, and the number and characteristics of patients asked

to participate are unknown.

Variables Participants The following data were registered for all patients admitted to

the hospital during the two registration periods: age (years),

gender, operation (yes/no), fall (yes/no; if yes, number of

falls, point of time related to the admission, operation, and

time of fall; daytime/evening/night), fall as the cause of

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effects of a fall prevention program in elderly

admission (yes/no), fall causing fracture (yes/no), fall for-

mally reported in the hospital’s systems for adverse events

(yes/no), fall screening performed (yes/no), and the duration

of the stay (days).

Fall Fall was defined according to WHO as “an event which

results in a person coming to rest inadvertently on the ground

or floor or other lower level.”16

Falls were registered retrospectively. Four individuals

shared the reviewing of all the medical records written by

doctors, nurses, and physiotherapists during the registration

periods. They read parts of the medical records and searched

the records with appropriate keywords to retrieve and find

information about all falls. Also, the hospital’s formal registry

of adverse events was searched and the findings compared

with the medical records.

Fall prevention interventions Two doctors and three nurses from the ID participated

in the Patient Safety Campaign’s national workgroup for

prevention of falls. The group had meetings and published

national guidelines that proposed tools, training programs,

and improved procedures to prevent falls. The interventions

were implemented in the ID.

The fall prevention program, not unlike the 6-PACK

programme,13 was described in detail (in Norwegian).17

It consisted of 1) seven examples of risk factors which might

cause falls (diseases and medications, movement, cognitive

behavior, vision, continence, nutrition, and the room and

surroundings), 2) methods to detect the risk factors, and

3) measures to avoid falls or protect the patient in case of

a fall. The interventions were multifaceted and included

short- and long-term activities to prevent falls. To detect

risk factors, a fall screening was performed with the Norwe-

gian version of the risk assessment tool for falls in elderly

“STRATIFY” (score 0–5).18 Patients were scored on five

risk factors, each of them is one point: falls last 3 months,

reduced vision, uneasy patient, frequent visits to the toilet,

and reduced walking/movement ability. Standard measures

for all patients were a review of the medication and infor-

mation about the room and the surroundings. There were

individually tailored measures such as to lock the wheels of

the bed and the tables, make sure that the patients can reach

the alarm and their personal belongings, lower the bed to the

lowest level, adjust day and night lightening, and remove

furniture and equipment that may cause falls. In patients with

a score of 2 or more, a comprehensive individual plan for

fall prevention was worked out, documented in the medical

records, and communicated to the staff responsible for the

patient. The plan included practical initiatives like adjusting

the beds, proper illumination, instructions not to leave the

bed unaided, and the use of appropriate shoes. There were

also long-term measures like the treatment of underlying

diseases, changes in medication associated with the risk

of fall, physical training, and healthier dietary habits. Dur-

ing the intervention, reports about the process (number of

patients screened, etc) and the results (number of falls, etc)

were regularly sent to the authorities. The governmental

intervention was designed for use in hospitals, care facilities,

and patients living at home. Most of the proposed activities

aimed at preventing falls in a long time perspective. The fall

intervention was added to the routine preventive measures,

which were performed in the CD at the employees’ discre-

tion. The patients were offered suitable, often low, beds

with bed staffs, special surveillance if they were confused

Figure 1 The study design. Abbreviations: CD, control department; ID, intervention department.

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røyset et al

or dizzy, and were urged to ask for help if they wanted to

get out of the bed.

Patient safety culture Patient safety culture was measured with the validated

Norwegian version of the Safety Attitudes Questionnaire

(SAQ).19,20 The national campaign used only two factors

(teamwork climate and safety climate) out of the six factors

in the questionnaire. According to the scoring algorithm,

some answers were recoded and the results transformed into

a scale 0–100; high values indicate a good culture.

Patient-perceived safety The Norwegian Patient Experience Questionnaire (PEQ) has

been used regularly in Norwegian hospitals since 1996.21 This

study used ten out of 52 questions that measure the patient-

experienced patient safety.22 The answers were transformed

according to the scoring algorithm into a scale 0–100; high

values indicate high patient-perceived safety.

statistics The results have been reported as mean (SD), median

(range), and number (with proportion in brackets). Com-

parisons between groups were analyzed with Fisher’s exact

test, Student’s t-test, and Mann–Whitney U-test depending

on the type of data and distribution, and logistic regression

analyses for the study of predictors of falls. For continuous

variables, the comparisons of changes from before to after the

intervention were performed with linear regression with the

point of time, department, and their interaction as covariates.

For dichotomous variables, the risk difference was calculated

with a semirobust generalized linear model for a binary out-

come. In each analysis, we included all the cases with data on

the relevant variables (“available case analysis”). P-values

,0.05 were judged as statistically significant. The analyses

were performed with IBM SPSS Statistics for Windows,

version 23.0 (IBM Corporation, Armonk, NY, USA), except

for the risk difference for dichotomous variables that were

analyzed with STATA Release 13 (StataCorp LP, College

Station, TX, USA).

ethics approval The project was approved by the Regional Committees

for Medical and Health Research Ethics (REK) in Norway

(approval number REK 2015/2469). A waiver of consent was

granted in this study as the project was deemed not to be a

medical or health research project according to the Health

Research Act. By virtue of regulations of February 7, 2009,

#989 REK is delegated authority to grant exemption from

the duty of confidentiality pursuant to the Health Personnel

Act, §29 first paragraph and the Act of First Amendment, §13

first paragraph, and a waiver of consent is given to obtain the

data mentioned in the application (see registration variables

under participants) as the project is of genuine interest to

society and the data collection does not significantly interfere

with the welfare and integrity of the patients. The data were

anonymized after registration. The Norwegian Data Inspec-

torate represented by the Privacy Ombudsman for research

at Møre og Romsdal Hospital Trust approved the responses

to the questionnaires SAQ and PEQ for research after ano-

nymization. The study was registered in ClinicalTrials.gov

NCT03354468; date of registration: November 24, 2017;

“Retrospectively registered.”

Results In all, 3,143 patients with 17,006 days in the hospital were

included in the study. Falls were noted in 114 patients, ten

patients had two falls, which gave an overall fall rate of

3.6% of the patients or 7.3 falls/1,000 days in the hospital.

Table 1 shows the patients’ characteristics and the results

separately for the ID and CD with comparisons between the

departments.

The overall prevalence rates of fallers in both the regis-

tration periods in the ID and CD were 68/1,469 (4.6%) and

46/1,674 (2.7%), respectively (P=0.005), and the prevalence rates of fallers before and after the intervention were 62/1,545

(4.0%) and 52/1,598 (3.3%), respectively (P=0.30). Patients with falls had a longer stay in hospital compared with those

who did not fall; the median lengths were 7 days (range

1–164) and 4 days (range 0–56), respectively (P,0.001).

The prevalence rate of fallers in patients with and without

an operation were 91/2,274 (4.0%) and 22/824 (2.7%),

respectively (P=0.08). In the ID, the fall risk evaluation was performed in 327/727 (45%) of the patients after the

intervention. The number of fallers in patients evaluated and

not evaluated for fall risk were 17/327 (5.2%) and 14/400

(3.5%) (P=0.27), respectively, and the number of fallers formally registered in the hospital registry of adverse events

before and after the intervention were 2/37 (5.4%) and 4/31

(12.9%) (P=0.40), respectively. Table 2 shows unadjusted and adjusted predictors of fallers.

In the ID and CD, the changes in the faller rates from

before to after the intervention were 0.82% and 0.65%,

respectively, the difference was not statistically significant

(P=0.90). Table 3 shows the details and Figure 2A visualizes the main results.

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effects of a fall prevention program in elderly

In all, 130 and 128 employees had satisfactorily filled in

the teamwork and safety culture parts of the SAQ, respec-

tively. The patient safety culture did not differ significantly

between the two departments. Table 1 shows the overall

results in the two departments, and Table 3 shows the culture

in the two departments before and after the intervention with

comparisons between the departments and the time of regis-

tration. The changes in the teamwork and safety climate from

the first to the second registration did not differ significantly

between the departments.

Before and after the intervention, 62 and 76 patients in the

ID and 26 and 33 patients in the CD, respectively, answered

the patient-perceived safety questionnaire. The patient-

perceived safety scores did not differ significantly between

the departments and were not significantly influenced by the

intervention. Table 1 shows the overall results, and Table 3

shows the results in the two departments before and after the

intervention with comparisons between the departments and

time of registration.

The main outcomes of the study were the comparisons

of the changes in the faller rates, patient safety culture, and

patient-perceived safety from before to after the intervention

between the departments. There was no significant effect

of the intervention in either of the variables (Table 3 – the

Table 1 Patients’ characteristics and the overall results from both registration periods in the two departments

Patient characteristics and results

Intervention department (ID) n=1,469

Control department (CD) n=1,674

Statistics, P-values

Women/men 943 (64%)/526 (36%) 1,072 (64%)/602 (36%) 0.94a

Age (years) 77.7 (8.5) 78.0 (8.4) 0.41b

Days in hospital 4.0 (0 to 164) 4.0 (0 to 53) 0.58c

Operation 1,036 (71%) 1,271 (76%) 0.001a

Fall as the cause of the admission 538 (37%) 716 (43%) ,0.001a

Falls 68 (4.6%) 46 (2.7%) 0.005a

Falls causing fracture 4/68 (5.9%) 3/46 (6.5%) 1.00a

Falls causing operation 3/68 (4.4%) 3/46 (6.5%) 0.68a

Fall: days after admittance 3.0 (0 to 31) 4.0 (0 to 16) 0.07c

Fall: days after an operation 2.0 (-6 to 32) 3.5 (1 to 15) 0.004c

Fall: day/evening/night 23 (34%)/18 (26%)/27 (40%) 21 (46%)/8 (17%)/17 (37%) 0.38a

Falls formally reported 6/66 (9.1%) 1/46 (2.2%) 0.24a

Teamwork climated 77 (16) 78 (15) 0.65b

safety climatee 75 (17) 76 (17) 0.98b

Patient-perceived safetyf 89 (18) 85 (17) 0.10b

Notes: The results are given as number and proportion (%), mean (sD), and median (range). aFisher’s exact test; bt-test; cMann–Whitney U-test. dnumber of subjects in the ID and CD were 76 and 54, respectively. enumber of subjects in the ID and CD were 75 and 53, respectively. fnumber of patients in the ID and CD were 138 and 59, respectively.

Table 2 Comparisons of the patients with and without a fall and predictors of fallers

Variables Faller Predictors of fallersa

Yes (n=114) No (n=3,029) P-value OR 95% CI P-value

gender (female/male) 68 (60%)/46 (40%) 1,947 (64%)/1,082 (36%) 0.321b 1.30 0.88–1.94 0.19

Age (years) 80 (65–97) 77 (64–101) 0.025c 1.02 0.996–1.05 0.11

Department (ID/CD) 68 (60%)/46 (40%) 1,401 (46%)/1,628 (54%) 0.005b 0.57 0.39–0.84 0.005

Point of time (before/after the intervention)

62 (54%)/52 (46%) 1,483 (49%)/1,546 (51%) 0.294b 0.90 0.61–1.32 0.58

Fall as the cause of the admission 48 (42%) 1,206 (40%) 0.627b 1.04 0.68–1.58 0.86

Operation during hospitalization 92 (81%) 2,215 (73%) 0.084b 1.38 0.85–2.24 0.20

Days in hospital 7.0 (1–164) 4.0 (0–56) ,0.001c 1.08 1.05–1.10 ,0.001

Notes: The results are given as number (proportion), median (range), and Or with 95% CI. alogistic regression analysis with faller as the dependent variable and all the variables in the table as covariates; bFisher’s exact test; cMann–Whitney U-test. Abbreviations: CD, control department; ID, intervention department.

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Table 3 Main variables in the two departments before and after the intervention

Variables ID before

ID after

Statistics, P-values

CD before

CD after

Statistics, P-values

ID vs CD before, P-values

ID vs CD after,

P-values

Difference in change (95% CI)

Statistics, P-values

Faller, n (%)

37/734 (5.04)

31/735 (4.22)

0.460a 25/811 (3.08)

21/863 (2.43)

0.456a 0.052a 0.048a 0.17% (-2.49 to 2.84) 0.90b

Teamwork climate,c mean (sD)

77 (18) 77 (13) 0.986d 81 (13) 75 (16) 0.130d 0.266d 0.609d 6.3 (-4.6 to 17.3) 0.26e

safety climate,f mean (sD)

74 (18) 77 (16) 0.408d 80 (17) 72 (18) 0.094d 0.195d 0.201d 11.3 (-0.8 to 23.5) 0.07e

Patient- perceived safety,g mean (sD)

91 (16) 88 (19) 0.312d 83 (18) 86 (17) 0.563d 0.052d 0.614d -5.8 (-16.8 to 5.2) 0.30e

Notes: The number of fallers, the patient safety culture, and the patient-perceived safety in the two departments before and after the intervention with comparisons between the time points and comparisons of the changes from before to after between the departments are shown. A positive difference in the changes is in favor of the ID. The results are given as number (proportion in %); mean (sD), and differences in the changes of proportions with 95% CI. aFisher’s exact test; bgeneralized linear model for a binary outcome; cnumber of subjects in the ID department before and after the intervention were 37 and 39, respectively, and in the CD 27 both before and after. dstudent’s t-test. elinear regression. fnumber of subjects in the ID department before and after the intervention were 36 and 39, respectively, and in the CD 26 and 27, respectively. gnumber of patients in the ID department before and after the intervention were 62 and 76, respectively, and in the CD 26 and 33, respectively. Abbreviations: CD, control department; ID, intervention department.

Figure 2 Changes from before to after the intervention. Notes: The four parts of the figure show: (A) the proportions of fallers (%); (B) the teamwork climate (mean); (C) the safety climate (mean); (D) the patient-perceived safety before and after the intervention in the departments with and without the intervention. The text gives the differences in the changes between the departments from before to after the intervention; positive values indicate changes in favor of the intervention department.

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effects of a fall prevention program in elderly

column “Difference in change”). Figure 2A–D shows the

results with the differences in changes between the depart-

ments from before to after the intervention.

Discussion We observed no differences in the changes in the faller rates,

patient safety culture, or patient-perceived safety from before

to after the intervention between the two departments and

conclude that the fall intervention had no clinically significant

effect at the time of observation. An initial temporary effect

during the implementation period might have been missed

due to the long period between the two registrations (1 year).

The fall rate in this study (7.3 falls per 1,000 patient days

in hospital) was in accordance with other studies on elderly

patients.6,8 A more conscientious registration of falls in the

medical records in the ID is the most likely explanation of

the higher faller rate in this department compared with the

CD. Patients with falls were older and had more days in

the hospital, but only days in hospital was an independent

predictor of fall. It is unknown if the fall caused prolonga-

tion of the stay in the hospital or if frail patients have more

extended stays and more falls. Independent of the causation,

patients with long stays should receive extra preventive inter-

ventions and surveillance. Both older age and length of stay,

independent of injury caused by the fall, have been associated

with fall in other studies.23,24 Risk factors associated with

falls in other studies, but not in this one, are previous falls

and gender.24,25 Information about falls over a longer period

before the admission was not available. This information and

not only fall as the cause of admittance could have been a

predictor of falls.

The lack of effect on the faller rate could indicate that

the intervention has added little to the routine fall preven-

tion practice or that the observation period during the stay

in the hospital was too short. Most of the interventions

had a longer perspective (such as training of balance and

strength, nutritional advice, and change of medication) and

might have reduced the faller rate after discharge from the

hospital. The intervention might have increased the attention

to risk factors for falls but added little to the normal activities

to prevent falls during a short stay in a busy hospital unit.

Barker et al13 have questioned the time spent to fall risk

screening and interventions in acute care hospitals, which

was an essential part of the intervention in the current study,

since they are often ineffective. Identifying new methods

to reduce harm from falls and improve the observation of

patients, such as environmental adaptations, intelligent sen-

sor systems with alarms, videos, and icons might be better

preventive measures.26 Reports from multifactorial and

knowledge-based interventions made to decrease falls in

hospitals are contradictory. Some have concluded that the

interventions were ineffective.12,13 In a review of 17 trials

from hospitals, Cameron et al10 concluded that multifacto-

rial interventions reduced falls in hospitals, but the evidence

for risk of falling was not conclusive. Individualized patient

education programs combined with training and feedback to

the staff might be a better way to reduce falls in older patients

than fall intervention programs intended for staff only.27

This view has been supported by more recent studies.28,29

A systems-based fall prevention program has been shown to

reduce the fall rate from 4.34 to 2.53 per 1,000 patient days.30

The faller rate declined in both departments from before

to after the intervention. The report from the Norwegian

Institute of Public Health in 2016 showed that the incidence

of reported harm due to falls decreased after the national

campaign in 2013 and 2014 but increased again in 2015.31

The overall reduction during the study period could, there-

fore, be related to the national campaign and not the specific

intervention.

The duration of the stay in the hospital was, in addition

to the department, the most important predictor of being a

faller. It is unknown whether the long stay was caused by

the fall or if frail elderly need longer stays and have a higher

risk of falling. The reason for the differences between the

departments remains unexplained.

The mean scores for teamwork climate and safety cli-

mate in this study were in the upper part of the measures

from other hospitals using SAQ.20,32 An improvement in the

patient safety culture from before to after the intervention was

expected in the ID due to the focus on safety, but the culture

was in large unchanged. The fall in the patient safety culture

in the CD was likely due to local turbulence related to plans

to reorganize the department, reduce the number of beds

and employees, and new management. The nonsignificant

difference in the change in the patient safety culture in favor

of the ID during the study was due to the unfavorable effect

in the CD and not a favorable effect in the ID.

The patient safety culture is assumed to reflect real patient

safety. In this study, the local turbulence and deteriorated

patient safety culture in the CD did not affect the faller rate.

The association between patient safety culture and true

patient safety, and the validity and reliability of the tools

used for measuring patient safety culture and adverse events

have been questioned.33,34 Reviews indicate an association

between patient safety culture and patient outcomes, but the

documentation has been questioned.34,35

The patient-perceived safety was of the same order

as reported on the national level; the mean national score

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in 2014 was 86. The study did not show any effect of the

intervention on patient-perceived safety. The tendency to

a better patient-perceived safety in the ID than in the CD

before the intervention might have occurred by chance. In a

study with other instruments, patient satisfaction was higher

in hospitals where the employees had a high score for patient

safety culture.36

strengths and limitations strengths The departments were chosen because they were fairly similar

except for participation in the campaign.

The intervention was multifactorial, which is assumed to

be the most effective method, well planned on the national

and local level, implemented after education and training of

the staff, and strongly supported by the director.

The current study registered not only fallers but also the

employees’ perceived patient safety culture and patient-

perceived safety with validated questionnaires. We are not

aware of other studies evaluating the effect of an interven-

tion on all three variables. Measuring quality in different

ways provides a qualified basis for assessing the effect of

an intervention and the need for improvement.

The design with measurement of all the main variables

before and after the intervention in the same hospital made

comparisons of changes from before to after the intervention

valid because other factors than the intervention influencing

on the changes were in large the same.

limitations Registration of fallers and falls were performed retrospec-

tively in the medical records and the hospital’s registry for

adverse events. Since it is likely that some falls without

medical consequences have been omitted in the medical

records, a prospective registration would have been to

prefer. The accuracy of the review of the medical records

has also been crucial for the quality of the study. In all, the

registration of falls might have been suboptimal. Monitoring

of the falls in real time with, for example, wearable sensors

might have improved the fall registration.37 The reviewers

were not blinded. It is, however, no reason to believe that

registration of falls differed between the departments or from

before to after the intervention since the staff was unaware

of the planning of the study and all reviewers of the medical

records reviewed records from both departments and both

points of time.

The response rates to the SAQ and PEQ questionnaires

were unknown because the number of employees and

patients receiving the questionnaires was not known. On

the national level, the response rate to PAQ has been in the

order of 60%.

The surveys used only parts of the questionnaires. SAQ

used two out of six dimensions, and PEQ used ten out of 52

questions. The use of parts of questionnaires is not optimal,

although the patient-experienced patient safety part of PEQ

has been validated.22

It was disappointing that compliance with the fall screen-

ing intervention was only 45% in the ID after the intervention

despite the use of plenty of resources. The low compliance

shows the challenge of implementing new routines in the

busy daily activity. Because the prevalence rate of fallers

was low in this study and the study size was limited, the lack

of effect could be a type II error.

The results of studies like this one are highly dependent

on the fall intervention program, the implementation of the

program, the compliance with the program, and the local

routines. Also, the study design with only one ID and one CD

opens for confounding. The low response rates among both

the employees and the patients might have induced a selection

bias. The validity is therefore questionable. Nevertheless, the

study shows that quality improvement is difficult, resource

demanding, and requires meticulous planning, which are

generalizable knowledge.

Conclusion The fall prevention program performed as a part of a national

safety campaign revealed no effect on the rate of fallers, the

patient safety culture, or the patient-perceived safety during

a short stay in an orthopedic department. Since the recom-

mended interventions included several long-term activities

to prevent falls, a long-term follow-up will be of interest.

Acknowledgments The authors thank the research coordinators Synnøve Herje

and Elisabeth Tennøy Bjerkan, Clinical Research Unit, and

research assistant Veronika Dybvik, Orthopedic department,

Møre og Romsdal Hospital Trust for collecting the data from

the medical records. They also thank Møre og Romsdal

Hospital Trust for the funding.

Author contributions BR has planned the study, has been responsible for the

practical work including collecting of the data, has prepared

the data files for the analyses, and has drafted the manuscript.

BAT-P has supervised the local activities and taken part in all

parts of the project including the analyses and preparation of

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effects of a fall prevention program in elderly

the manuscript. SL has together with PGF been responsible

for the statistical analyses. PGF has been the administrator of

the project after the data were collected and processed further

for the analyses, has performed most of the analyses, and has

finalized the manuscript for publication. All authors have

given valuable comments on the manuscript and approved

the last version. All authors contributed to data analysis,

drafting or revising the article, gave final approval of the

version to be published, and agree to be accountable for all

aspects of the work.

Disclosure The authors report no conflicts of interest in this work.

Availability of data Data from the medical records were transferred manually

to an Excel file and anonymized. Anonymous data from the

questioners SAQ and PEQ were received as Excel files. The

data files were converted to the statistical programs SPSS

and STATA for the analyses and are stored by Innlandet

Hospital Trust, Brumunddal, Norway, on a server dedicated

to research and with security according to the rules given by

The Norwegian Data Protection Authority, Oslo, Norway.

The data are available on request to the authors. The study

was registered in ClinicalTrials.gov with ID number

NCT03354468, date of registration: November 24, 2017;

“Retrospectively registered.”

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