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Evaluation and refinement of a handheld healthinformation technology tool to support the timelyupdate of bedside visual cues to prevent fallsin hospitals
Ruth C.-A. Teh FRACP, MBBS, B Pharm (Hons),1,2 Renuka Visvanathan PhD, FRACP, FANZSGM, G.Cert.Ed (H.Ed.),
MBBS, ATCL,1,2 Damith Ranasinghe PhD, BOE3 and Anne Wilson PhD, MN, BN, RN, FACN2,4,5
1Aged and Extended Care Services, The Queen Elizabeth Hospital, 2Adelaide Geriatrics Training and with Aged Care (GTRAC) Centre, Adelaide
Medical School, The University of Adelaide, Adelaide, South Australia, 3School of Computer Science, The University of Adelaide, Adelaide, South
Australia, Australia, 4College of Medicine and Public Health, Flinders University of South Australia, and 5Prince of Wales Medical School, University of
New South Wales, Sydney, New South Wales, Australia
A B S T R A C T
Aim: To evaluate clinicians’ perspectives, before and after clinical implementation (i.e. trial) of a handheld healthinformation technology (HIT) tool, incorporating an iPad device and automatically generated visual cues for bedsidedisplay, for falls risk assessment and prevention in hospital.
Methods: This pilot study utilized mixed-methods research with focus group discussions and Likert-scale surveys toelicit clinicians’ attitudes. The study was conducted across three phases within two medical wards of the QueenElizabeth Hospital. Phase 1 (pretrial) involved focus group discussion (five staff) and surveys (48 staff) to elicitpreliminary perspectives on tool use, benefits and barriers to use and recommendations for improvement. Phase 2(tool trial) involved HIT tool implementation on two hospital wards over consecutive 12-week periods. Phase 3 (post-trial) involved focus group discussion (five staff) and surveys (29 staff) following tool implementation, with similarthemes as in Phase 1. Qualitative data were evaluated using content analysis, and quantitative data using descriptivestatistics and logistic regression analysis, with subgroup analyses on user status (P�0.05).Results: Four findings emerged on clinicians’ experience, positive perceptions, negative perceptions and recom-mendations for improvement of the tool. Pretrial, clinicians were familiar with using visual cues in hospital fallsprevention. They identified potential benefits of the HIT tool in obtaining timely, useful falls risk assessment toimprove patient care. During the trial, the wards differed in methods of tool implementation, resulting in lower uptakeby clinicians on the subacute ward. Post-trial, clinicians remained supportive for incorporating the tool into clinicalpractice; however, there were issues with usability and lack of time for tool use. Staff who had not used the tool hadless appreciation for it improving their understanding of patients’ falls risk factors (odds ratio 0.12), or effectivelypreventing hospital falls (odds ratio 0.12). Clinicians’ recommendations resulted in subsequent technologicalrefinement of the tool, and provision of an additional iPad device for more efficient use.
Conclusion: This study adds to the limited pool of knowledge about clinicians’ attitudes toward health technologyuse in falls avoidance. Clinicians were willing to use the HIT tool, and their concerns about its usability were addressedin ongoing tool improvement. Including end-users in the development and refinement processes, as well as havinghigh staff uptake of new technologies, is important in improving their acceptance and usage, and in maximizingbeneficial feedback to further inform tool development.
Key words: falls prevention, health information technology, mixed-methods, perspectives
Int J Evid Based Healthc 2018; 16:90–100.
Correspondence: Ruth C.-A. Teh, FRACP, MBBS, B Pharm (Hons),
Sunbury Hospital, 7 Macedon Road, Sunbury, Victoria, 3429,
Australia. E-mail: [email protected]
DOI: 10.1097/XEB.0000000000000129
90 International Journal of Evidence-Based
iversity of Adelaide, Joanna Briggs Institute. U
Background
F alls are the seventh most common cause of hospi-tal-acquired injury1 and are more prevalent amongolder persons.2,3 Despite the introduction of mandatory
Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
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ORIGINAL RESEARCH
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hospital falls risk assessment and prevention strategies
as a healthcare priority, the incidence of inpatient
falls continues to rise by 2% each year.3–5 Overall, the
reported incidence of falls in hospital varies widely from
2–3 (acute setting) to 46% (rehabilitation setting).6,7 Falls
are more prevalent in medical compared with surgical
wards,8 in public compared with private hospitals (4.2 vs.
1.6 per 1000 hospitalizations), and among patients living
in major cities compared with remote areas (3.4 vs.
1.9 per 1000 hospitalizations).9 Actual fall rates are likely
to even be higher as there is no universal definition for a
fall, and falls incidents tend to be under-reported.10
Hospital falls tend to cause serious complications,
with 44–60% resulting in harm,11,12 especially among
older persons.13 The 6-PACK trial (2011–2013) in six
Australian hospitals demonstrated that hospital falls
increased length of stay (LOS) by 8 days [95% confidence
interval (CI) 5.8–10.4, P<0.001], and hospital costs by
AU$6669 (95% CI $3888–9450, P<0.001), even after
adjusting for age, sex, cognitive impairment, comorbid-
ities and admission type.14 Older persons who sustain
hip fractures in hospital have poorer outcomes com-
pared with their peers who sustain hip fractures in the
community,15 including longer LOS,16 reduced return
to preadmission ambulation and functional status,
increased rates of discharge to permanent residential
care15 and higher mortality rates.16 Indeed, falls may lead
to chronic pain, reduced quality of life, functional
impairment, permanent disability and higher rates of
inpatient mortality.13,17,18
Health technology has the potential to influence this
outcome but has been limited by the lack of rigorous
evidence for effective single-technology interventions,
including sensors and electronic medical records.19
Moreover, clinicians’ perspectives toward the use of
health technology in falls prevention are not well-known,
despite systematic review evidence that staff attitudes
are crucial to successfully integrating any falls preventive
strategy.19,20
Nursing staff are familiar with using visual cues to
communicate falls risk and preventive strategies.21 Visual
cues, as part of a Falls Prevention Tool Kit, have been
shown in a single randomized controlled trial to be
effective in lowering hospital falls rate (3.15 vs. 4.18
per 1000 patient-days; P¼0.04), especially among thoseaged 65 years and over (rate difference 2.08 vs. 1.03 per
1000 patient-days; P¼0.03).22 However, further researchwas needed into whether such findings could be repli-
cated in different settings. Within the Geriatric and
Evaluation (GEM) unit at the Queen Elizabeth Hospital
(TQEH), a preliminary audit found 20% staff compliance
with existing patient bedside posters for falls prevention
International Journal of Evidence-Based Healthcare � 2018 University
iversity of Adelaide, Joanna Briggs Institute. Un
(Fig. 1; Visvanathan R, Ranasinghe D, Hoskins S, Wood J,
Mahajan N, unpublished data). Nursing staff reported
these paper-based posters were time-consuming and
hence not completed, as they involved placing adhesive
colored dots on eight different locations of the poster
to indicate falls risk (i.e. green for low risk, yellow for
medium risk, red for high risk), before displaying the
poster by the patient’s bedside (Visvanathan R, Rana-
singhe D, Hoskins S, Wood J, Mahajan N, unpublished
data). Due to poor uptake and negative feedback of the
existing posters, and mindful of the pending electronic
health record (EHR) system due to roll out across public
hospitals statewide in South Australia, the opportunity
was seized to develop a health information technology
(HIT) tool in collaboration with ward clinicians. This HIT
tool incorporated an iPad 2 device (model number
A1315; Apple, Cupertino, California, USA) for direct clini-
cians’ entry of up to 13 common falls risk activities23
(Fig. 2), with automatic generation of visual cues for
bedside display (Fig. 3).
Our pilot study aimed to evaluate clinicians’ attitudes
toward this HIT tool, in particular, their experiences,
positive and negative perspectives and recommenda-
tions for improvement, both preclinical and postclinical
implementation (i.e. trial), to inform ongoing tool refine-
ment, ultimately as part of a novel movement-detection
sensor technology system for hospital falls prevention.
MethodsEthics approvalThe study protocol was approved by the Human
Research Ethics Committee of the Basil Hetzel Institute,
South Australia (HREC/13/TQEHLMH/66), and conformed
to the World Medical Association Declaration of Hel-
sinki.24 Each participant provided written, informed con-
sent prior to research involvement, and participant
information was deidentified.
Research methodologyMixed methods design was applied to allow for greater
robustness and richness of information gathered,25,26
with focus group research used to obtain qualitative
data simultaneously from multiple individuals on differ-
ent ideas and perspectives.27
Study protocolThe current pilot study was divided into three phases.
Phase 1 (pretrial) evaluated clinicians’ perspectives on
the HIT tool (i.e. study aims) prior to implementation,
using focus group discussion and surveys. Phase 2 (tool
trial) involved tool implementation on hospital wards.
Phase 3 (post-trial) examined clinicians’ perspectives on
of Adelaide, Joanna Briggs Institute 91
authorized reproduction of this article is prohibited.
ST MargaretõsRehabilitation
Hospital
Stepping forward programš falls risk chart
Showeringš once seated Toiletingš once seated
Wet area
Wet area transfer Wet area mobility/AMB
StickerSticker
Sticker Sticker
StickerSticker
StickerSticker
Patient sticker
Dry area
Dry area mobility/AMB Night mobility
Red dot needs hands on assistance
Yellow dot needs supervision and/or standby
Green dot independent
Bed mobility Dry area transfer
Figure 1. Example of a paper-based bedside poster using colored stick-on dots to indicate patient’s falls risk.
RC-A Teh et al.
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the tool after trial completion, using focus group discus-
sion and surveys with similar themes as in Phase 1.
Focus group sessions were led by the chief researcher,
who was employed by TQEH as a medical doctor, but not
working on the wards at the time of the study. The chief
researcher defined focus group goals (i.e. study aims)
at each session and facilitated discussion for an hour or
until data saturation was reached (i.e. when information
occurred so repeatedly that additional data collection had
no additional worth).28 Textual data were transcribed
verbatim by the chief researcher from Dictaphone (Philips
PocketMemo voice recorder DPM8000; Atlanta, Georgia,
USA) recordings and written notes. Transcripts were not
returned to participants for comment.
Likert-scale surveys were derived following focus
group discussion and utilized similar themes. These were
distributed to ward staff over 2 week periods, before and
after the tool trial, by the chief researcher and two ward
clinical nurse consultants (CNCs), who were considered
nursing leaders and experts in clinical care.29 Completed
nonidentifiable questionnaires were returned to the
92 International Journal of Evidence-Based
iversity of Adelaide, Joanna Briggs Institute. U
researcher personally or via a designated tray on the
wards.
The HIT tool was implemented on the GEM unit (June
to August 2014), followed by the Acute Medical Unit
(AMU) (September to November 2014), over two conse-
cutive 12-week periods. Ward clinicians had up to
6 weeks of researcher training and reminders on tool
use (3-h-long sessions each week) and were indepen-
dent for the remaining 6 weeks. GEM staff utilized the full
period of researcher-led support, whereas AMU staff
declined researcher input after 1 day, citing staff confi-
dence with tool use.
The HIT tool took less than 5 min to use for each
patient. There was no automatic trigger for staff to use
the tool, other than reminders from the researcher in the
first 6 weeks. The iPad device was carried by the clinician
responsible for using the tool. This person directly
entered patient’s details (age, bed location, mobility
aid) and their own clinical judgment (yes/no responses)
about the patient’s day and nighttime falls risk for
13 different movement and location types (Fig. 2).
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Walking
Sitting/standing
Toilet
Corridor
Next
Shower
In/out of bed
Yes
No
Yes
No
At-risk
No risk
At-risk
No risk
At-risk
No risk
Yes
No
Movements requiring supervision?
State additional locations where supervision required?
Figure 2. Example of a screenshot of direct clinician entry of patient’s falls risk assessment using the health informationtechnology tool.
ORIGINAL RESEARCH
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Black-and-white A4-sized visual cues were automatically
printed at assessment completion (Fig. 3), and the same
clinician was responsible for displaying these paper-
based visual cues by the patient’s bedside. Ward staff
subsequently targeted falls preventive interventions
according to clinical judgment.
Both wards were given freedom on how to imple-
ment the HIT tool. AMU staff used the tool daily on all
ward patients. All registered nurses on AMU were rotated
to use the tool, which was usually completed by the
International Journal of Evidence-Based Healthcare � 2018 University
iversity of Adelaide, Joanna Briggs Institute. Un
registered nurse allocated to nonpatient-related duties
(e.g. ward medication management), to allow for timely
use of the HIT tool, unencumbered by other duties. GEM
staff used the tool on new admissions and in which falls
risk altered (e.g. posthospital fall), reasoning this as
appropriate for a subacute setting, in which patients’
falls risk changed less often compared with an acute
ward. The CNC and two registered nurses from GEM used
the HIT tool, due to limited confidence by the rest of the
staff in using the device.
of Adelaide, Joanna Briggs Institute 93
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TQEHWard: GEMU
0700–2000Day
Movements requiring
supervision:
Walking Corridor Walking Corridor
Sitting/standing Sitting/standingShower
In/out of bed In/out of bedToilet
Toilet
Issue date: 28/01/2013
Movements requiring
supervision:
Additional locations where
supervision required:
Additional locations where
supervision required:
2001–0659NightYes
Requires walking aid?UR: 100001
Name: Alice AlicemanBed No.: 7.1
Figure 3. Example of an automatically generated visual cue from the health information technology tool.
RC-A Teh et al.
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Setting and participantsThe study was conducted on two ground-floor medical
wards at TQEH, a tertiary teaching hospital in metropoli-
tan Adelaide, South Australia. The 16-bed AMU managed
patients in the acute phase of illness, whereas the 20-bed
GEM unit provided rehabilitative care aimed at restoring
patients’ function and independence after an acute
illness, usually with the goal of returning back home.30
Ward clinicians consisted of nursing [38.68 FTE (full-
time equivalent) GEM, 32 FTE AMU], junior medical (four
FTE GEM, five FTE AMU), and allied health staff, meaning
occupational and physical therapists (2.5 FTE GEM, two
FTE AMU). No pharmacists, speech therapists, dieticians,
social workers or senior medical staff were approached
to be part of this study.
Focus group participants were identified by ward
CNCs as clinicians having an expertise in falls prevention,
94 International Journal of Evidence-Based
iversity of Adelaide, Joanna Briggs Institute. U
with greater than 5 years of clinical experience, and
working within GEM, AMU or the Central Adelaide Local
Health Network (CALHN) Falls Prevention group at the
time of the study. Five clinicians were involved in each
pretrial and post-trial focus group discussion, with one
participant involved on both occasions. All five post-trial
focus group participants were HIT tool users from AMU,
with six clinicians from GEM and CALHN declining to
participate as they had not used the tool or were unable
to attend the focus group session.
Survey participants consisted of clinicians working
within GEM or AMU at the time of the study, and
consecutively approached by the chief researcher in
the 2-week periods, before and after the tool trial. There
were 49 pretrial (29 GEM, 20 AMU) and 28 post-trial (20
GEM, eight AMU) participants. It was not recorded which
participants were involved both pretrial and post-trial.
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ORIGINAL RESEARCH
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Post-trial, both those who had used the HIT tool (i.e. tool
users, n¼11) and those who had not (i.e. nonusers,n¼17), were included to reflect tool uptake. Post-trial,54 clinicians (65.9%) declined to participate as they had
no experience with or recommendations for improving
the HIT tool. Participation was voluntary with the option
to withdraw at any point.
AnalysisQualitative data from focus group sessions were manu-
ally analyzed using content analysis to systematically
code data and identify themes, to gain new knowledge
and initiate action.31,32 Descriptive statistics and logistic
regression were performed on quantitative survey data,
to describe and evaluate differences between clinicians’
perspectives pretrial and post-trial (P<0.05), with sub-
group analysis on users and nonusers using SPSS Statis-
tics for Windows, Version 22.0 (IBM Corp., Armonk, New
York, USA). Responses indicating ‘strongly agree’ or
‘agree’ were classified as positive, whereas those indicat-
ing ‘strongly disagree’, ‘disagree’ or ‘uncertain’ were
classified as negative responses to the item statement.
ResultsThe qualitative and quantitative data were integrated
into four main findings, and presented from Phase 1
(pretrial), followed by Phase 3 (post-trial), regarding
clinicians’ experience, positive perceptions, negative per-
ceptions and barriers to use, and recommendations for
refinement of the HIT tool.
Phase 1 (pretrial): Qualitative results fromfocus group sessionClinicians’ experiencePretrial, no participant had used the HIT tool. All partic-
ipants were familiar with using visual cues in falls pre-
vention, with four participants expressing negative views
about the existing posters using colored stick-on dots to
indicate falls risk. These were seen as a bit complicated,
tedious to complete, ineffective and therefore, underu-
tilized, due to time constraints with high patient turnover
and competing clinical duties.
Positive perceptionsIncorporating technology into falls risk assessment was
identified by three participants as beneficial in providing
staff with a fun, quick means of risk assessment. One
participant stated the HIT tool would serve as a stress
reduction tool for staff, in providing an immediate visual
of each patient’s falls risk factors. Four participants cited
benefits to patients and their families in increasing
knowledge on falls risk and preventive strategies, both
in hospital and on discharge.
International Journal of Evidence-Based Healthcare � 2018 University
iversity of Adelaide, Joanna Briggs Institute. Un
Negative perceptions and barriers to useClinicians perceived the main barrier to tool implemen-
tation to be shifting a workplace culture that resisted
change and did not view hospital falls as a problem. The
HIT tool was seen as increasing work for clinicians, with
time pressures on staff thought to compromise accuracy
of falls risk assessment and placement of visual cues
at the correct patient’s bedside. Three participants
expressed apprehension about clinicians using new
health technology, with one participant especially con-
cerned about older workers and technology use.
Recommendations for refinementThree participants requested tool technology be simple
to use, and eventually incorporated into the upcoming
EHR system. They recommended providing staff with
tool education, with training attendance linked to points
for continuous professional development (CPD). CPD
referred to the number of hours stipulated by national
registration standards for clinicians to engage in ongoing
professional education per annum.33 Four participants
suggested involving patients and families in the tool
process, to improve adherence to falls preventive mea-
sures in hospital and at home. One participant advo-
cated senior leadership endorsement to drive tool
integration into hospital programs.
Phase 1 (pretrial): Quantitative results fromsurvey participantsThe majority of survey participants were women (81.6%),
nursing staff (73.4%), aged between 18 and 39 years old
(63.3%) and had 10 years or less of experience in clinical
care (57.1%).
Clinicians’ experienceNo participants had used the HIT tool pretrial.
Positive perceptionsThe majority perceived the HIT tool as an easy,
accurate and timely means of assessing patients’ falls
risk (items 1, 2 and 3, Table 1). Over 70% thought it
facilitated safer, better quality patient care, improved
staff’s understanding of patients’ falls risk factors, effec-
tively prevented falls, and were willing to use the tool if
made available (items 4, 5, 6, 8 and 9). Half the partic-
ipants cited that it would effectively prevent inpatient
falls (item 7).
Negative perceptions and barriers to useLess than half the participants considered potential
barriers to tool use as being duplication of written work
(44.9%), lack of time to use the tool (38.8%) and lack of
of Adelaide, Joanna Briggs Institute 95
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Table
1.Comparisonbetw
eenpretrialandpost-trialresultsofclinicians’
perspectivesofthehealthinform
ationtech
nologytool,with
subgroupanalysesforuserstatus Pretrial,
n¼49(%
)
Post-trial
Total,
n¼28(%
)Users,
n¼11(%
)Nonusers,
n¼17(%
)Preusers
vs.
postusers
Prenonusers
vs.
postnonusers
Pre
vs.
post
(usersþnonusers)
Postusers
vs.
postnonusers
Benefits
ofHIT
tooluse
OR
OR
OR
OR
Easy
touse
duringbedto
bed
handover
39(75%)
13(46.4%)
6(54.5%)
7(41.2%)
0.22�
0.13�
0.16�
0.58
More
accurate
updatingfallsrisk
inform
ationcf.currentmethod
37(75.5%)
17(60.7%)
7(63.6%)
10(58.8%)
0.57
0.54
0.55
0.95
Updatesfallsrisk
inform
ationin
atimely
manner
36(73.5%)
17(60.7%)
8(72.7%)
9(52.9%)
0.89
0.43
0.62
0.48
Providessafercare
forpatients
at
risk
offalls
39(79.6%)
19(67.9%)
9(81.8%)
10(58.8%)
1.15
0.43
0.70
0.37
Improvesquality
ofpatientcare
43(87.8%)
19(67.9%)
9(81.8%)
10(58.8%)
0.63
0.23�
0.38
0.37
Improvesstaff’sunderstandingof
patients’fallsrisk
factors
35(71.4%)
12(42.9%)
8(72.7%)
4(23.5%)
1.07
0.12�
0.36
0.12�
Effectively
prevents
falls
26(53.1%)
7(25%)
5(45.5%)
2(11.8%)
0.74
0.12�
0.29�
0.16
Allowsmore
timeforstaffto
attend
tootherduties
7(14.3%)
3(10.7%)
2(18.2%)
1(5.9%)
1.33
0.38
0.71
0.28
Iwilluse
thistoolifitismade
available
44(89.8%)
21(75%)
10(90.9%)
11(64.7%)
1.14
0.25
0.53
0.22
Barriers
toim
plementingHIT
tool
Lack
oftime
19(38.8%)
11(39.3%)
6(54.5%)
5(29.4%)
1.90
0.66
1.11
0.35
Lack
offamiliarity
withtechnology
14(28.6%)
5(17.9%)
3(27.3%)
2(11.8%)
0.94
0.33
0.56
0.36
Duplicateswrittenwork
22(44.9%)
4(14.3%)
3(27.3%)
1(5.9%)
0.46
0.08�
0.19�
0.17
Lack
ofusability
0(0%)
6(21.4%)
1(9.1%)
5(29.4%)
>100
>100
Undefined
4.17
Suggestedtoolim
provements
Providingtoolfeedback
tostaff
31(63.3%)
4(14.3%)
4(36.4%)
0(0%)
0.33
0.00
<0.01
<0.01
Providingeducationalpresentations
ontoolto
staff
19(38.8%)
9(32.1%)
8(72.3%)
1(5.9%)
4.21
0.10�
0.65
0.02�
AwardingCPDpoints
tostafffor
attendingtooleducation
15(30.6%)
3(10.7%)
3(27.3%)
0(0%)
0.85
0.00
<0.01
<0.01
cf.,comparedwith;CPD,continuousprofessionaldevelopment;HIT,healthinform
ationtechnology;OR,oddsratio.
� P�0.05,i.e.significant.
RC-A Teh et al.
96 International Journal of Evidence-Based Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
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ORIGINAL RESEARCH
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familiarity with tool technology (28.6%) (items 10, 11 and
12). No participants perceived the HIT tool as lacking
usability (item 13).
Recommendations for refinementOver 60% recommended providing regular feedback to
clinicians to improve tool uptake (item 14, Table 1). A
third felt regular staff education on tool use and award-
ing of CPD points for training attendance would help
foster HIT tool use (items 14, 15 and 16)
Phase 3 (post-trial): Qualitative findings fromfocus group sessionClinicians’ experiencePost-trial, all focus group participants had used the HIT
tool. Participants A (tool use >10 times) and B (tool use
1–2 times) were the most verbal during discussion.
Positive perceptionsAll participants were positive about the tool’s benefits
and wanted to continue using it after trial completion. It
was perceived as beneficial to staff in being a visually
appealing and useful snapshot of patients’ falls risks.
Participants A and B cited its benefit to patients and
families as a teaching tool for falls risk and preventive
strategies.
Negative perceptions and barriers to useCompeting clinical duties and time pressures on a busy
ward were seen as barriers to tool use. One participant
outlined these barriers extended to challenges ensuring
visual cues were physically moved when patients were
swapped into another bed. Participants A and B reported
difficulties with technical aspects of the iPad application,
including difficulties managing these bed swaps and
surplus patient numbers, and re-entering the same
medical record number and demographic details for
returned patients.
Recommendations for refinementParticipants debated and decided against displaying
extra falls risk information on visual cues, preferring to
keep these uncluttered for simplicity and visual appeal.
Having A4-sized black-and-white visual cues, as opposed
to larger colored posters, was seen as appropriate given
already cluttered bedside walls and ongoing printing
costs. Participant B recommended coding high falls risk
status as a red dot on visual cues, with an automatic
trigger for staff to provide patients with printed infor-
mation on falls prevention. Participants A and B
requested an extra iPad device for more efficient and
timely tool use.
International Journal of Evidence-Based Healthcare � 2018 University
iversity of Adelaide, Joanna Briggs Institute. Un
Phase 3 (post-trial): Quantitative findings fromsurvey participantsPost-trial, survey participants were mainly women
(85.7%), nurses (92.9%), and had 10 years or less of
clinical experience (67.8%). Half were aged between
18 and 39 years old (50%). More than half (n¼54,65.9%) of ward clinicians declined to participate, citing
lack of use of, or recommendations for improving, the
HIT tool.
Clinicians’ experienceOf the 28 participants surveyed, 11 [eight (100%) AMU,
three (15%) GEM] had used the HIT tool on researcher
questioning. Most survey participants (60.7%) had not
used the tool, mainly due to low uptake on GEM unit.
Positive perceptionsThe majority of participants advocated ongoing use of
the HIT tool in clinical practice (75%) and were positive
about its accuracy, timeliness and facilitation of safer
patient care (items 2, 3, 4 and 9, Table 1). Compared with
pretrial, there were significantly lower numbers of non-
users who thought the tool was easy to use [odds ratio
(OR) 0.13], improved quality of patient care (OR 0.23) or
informed staff’s understanding of patients’ falls risk
factors (OR 0.12) post-trial (items 1, 5 and 6, Table 1).
Negative perceptions and barriers to useParticipants identified the main barriers to tool use as
lack of time to complete the tool (39.3%) and lack of tool
usability (21.4%) (items 10 and 13, Table 1). Significantly,
fewer participants thought duplication of written work
was a barrier, post-trial vs. pretrial (OR 0.19, item 12).
Recommendations for refinementThe main recommendation for improvement was for
staff education on the HIT tool (32.1%); however, this
was less so among nonusers compared with users (OR
0.02, item 15, Table 1).
DiscussionThe majority of clinicians advocated incorporating the
HIT tool in clinical practice, both pretrial and post-trial,
due to the benefits for staff and patients in hospital falls
risk assessment and prevention. Pretrial, clinicians were
positive about using a tool that incorporated visual cues
and health technology, both well accepted methods of
evaluating risk and preventing falls within literature.20,34
Post-trial, most clinicians continued to view the HIT tool
as useful to staff as an accurate, quick and timely means
of assessing patients’ falls risk. Indeed ease of workflow
has been identified by clinicians as an advantage of
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RC-A Teh et al.
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incorporating EHR into clinical routine.35 Clinicians
within this study cited benefits to patients in facilitating
safer, better quality care and increasing their knowledge
of and participation in falls preventive strategies. This
echoes previous research espousing the advantages of
technology in promoting patient and family education
and engagement in health care.35
Pretrial, clinicians were concerned about potential
barriers to tool use being duplication of existing paper-
work, lack of time for tool use, difficulties navigating new
technology and workplace resistance to change. Paper-
work duplication and time constraints are well docu-
mented barriers to clinicians using EHRs.36,37 Systematic
review evidence has shown technical concerns and
opposition to change are frequently cited barriers to
EHR adoption.38 Addressing nihilistic staff attitudes
and workplace resistance to change have proved impor-
tant in the success of many hospital falls prevention
programs.20,39,40
Post-trial, clinicians criticized the HIT tool in terms of
lack of usability, lack of time to use it amidst competing
clinical duties and lack of clinical effectiveness in pre-
venting inpatient falls. Usability has been shown to be a
key factor in determining user acceptance of health
technology.41,42 Software difficulties are known barriers
to using technology in falls prevention programs,20,43
with users often requesting increasingly sophisticated
software function over time.44 Similar to our findings, a
previous qualitative study found clinicians viewed EHRs
negatively as one more thing to do in an already over-
burdened healthcare system, felt time constraints lim-
ited their use and wanted technology to accommodate
heavy patient volumes and busy clinical workloads.45
The perceived barriers of lack of usability and time to
use the tool were reflected in clinicians’ recommenda-
tions for technological refinement of the iPad application
and provision of another iPad device for more efficient
tool completion. User engagement and feedback have
been used to refine the HIT tool as part of action research
methodology,46–48 by improving technology, color cod-
ing falls risk, having an automated patient education
trigger and providing an additional iPad device. Other
recommendations for improving tool uptake included
providing staff education, a key component of many
effective hospital falls prevention programs,20 and ensur-
ing leadership endorsement, an important factor in
sustaining best nursing practice.49
Strengths and limitationsDespite user attitudes being a major factor in interven-
tion uptake,20 there remains a gap in knowledge on staff
perspectives of health technology use in falls assessment
98 International Journal of Evidence-Based
iversity of Adelaide, Joanna Briggs Institute. U
and prevention.19 This article adds to the depth and
richness of understanding of this area, through the
employment of mixed-methods design.50 Research
limitations included small sample size, single hospital
setting, poor response rate, lack of consistency in partic-
ipant follow-up and incomplete data on which partic-
ipants took the survey on both occasions and how many
times they had used the tool. Sample sizes and with-
drawal rates within this pilot study, were influenced by
the pragmatics of recruitment and the need to assess
study feasibility.51 In addition, items developed for sur-
vey data collection (based on interviews with five focus
group participants) may not have been representative of
all relevant issues. These survey biases may limit gener-
alizability of outcomes and comparison of pretrial and
post-trial results. Additional biases may have been intro-
duced by focus group participants’ reluctance to provide
their opinions, due to researcher presence and concerns
about workplace implications, and researcher bias in
interpreting textual responses to match preconceived
notions.
Future research directionsThe refined HIT tool will be retrialed on the wards, with
future research directed at evaluating clinicians’ use and
perspectives, and clinical effectiveness in falls avoidance,
of this improved HIT tool. The HIT tool could be imple-
mented in healthcare facilities with high prevalence of
falls, and among those patients who are at high falls risk,
such as older persons and those in residential care.
Ensuring the same clinicians participate in pretrial and
post-trial focus group discussions and surveys would
enhance the robustness of data gathered. In addition,
greater depth of information may be elicited by includ-
ing patients and caregivers in discussion, conducting
personal interviews and discussing one topic per focus
group session.
ConclusionThe findings from this study contributed to the limited
pool of evidence on clinicians’ perspectives toward
health technology use in falls prevention. Clinicians were
willing to use the HIT tool, identifying benefits to them-
selves and patients. Their concerns about usability and
time constraints were addressed in ongoing tool refine-
ment, with technological improvement and provision of
an additional iPad device for more efficient use. Includ-
ing end-users in development processes, as well as
having high staff uptake, are important in improving
the acceptance and usage of new technologies, and in
maximizing beneficial feedback to further inform tool
development. Further research directions may include
Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
nauthorized reproduction of this article is prohibited.
ORIGINAL RESEARCH
©2018 Un
evaluating clinicians’ and patients’ perspectives of the
refined HIT tool, and evaluating its clinical effectiveness
in hospital falls prevention.
AcknowledgementsThe Hospital Research Foundation provided a research
grant to Dr Damith Ranasingghe. Dr Ruth Teh thanks
Stephen Hoskins & Sharon Berry of the GEM & AMU
wards at the Queen Elizabeth Hospital, in Adelaide, for
their assistance with the research.
Conflicts of interestThe authors report no conflicts of interest.
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