When evaluating the success of travel, whether the food or sites met expectations may be the main qualitative measure. Other meas
When evaluating the success of travel, whether the food or sites met expectations may be the main qualitative measure. Other measures will be more quantitative, such as whether the projected budget reflected the actual cost.
Some measures of successful HIT are qualitative in nature, while others are more quantitative. Most HIT evaluations will include one very important quantitative measure based on costs and returns. A cost analysis can help ensure that HIT investments are returning the benefits necessary to meet goals while remaining within budget.
In this Assignment, examine various types of cost analysis and select one for use in your HIT Evaluation Plan Project and justify your choice.
To prepare:
· Recall the HIT-ACE for the Evaluation Plan Project.
· Review Chapter 7 in the Herasevich text (link below)
· Select one of the five main types of analysis Herasevich lists as appropriate for HIT.
In a 3-page assignment:
– Choose one of the five main types of analysis Herasevich lists as appropriate for HIT and describe how you might use it to perform an analysis of a financial aspect of your HIT-ACE evaluation methodology.
– Describe the key elements you would include in your analysis.
– Justify your choice and provide a brief explanation of the alternative types of analysis.
– Explain why each would not be useful to analyze the financial aspect of your chosen case.
Requirement:
– 5 scholarly articles, peer-reviewed, within the last 5 years.
1)
Herasevich, V., & Pickering, B. W. (2017). Health information technology evaluation handbook: From meaningful use to meaningful outcome (1st ed.). Taylor & Francis Group.
· Chapter 7, “Cost Evaluation” (pp. 124–146)
2)
Teh, R., Visvanathan, R., Ranasinghe, D., & Wilson, A. (2018, June). Evaluation and refinement of a handheld health information technology tool to support the timely update of bedside visual cues to prevent falls in hospitals. International Journal of Evidence-Based Healthcare, 16(2), 90–100. doi:10.1097/XEB.0000000000000129
3, 4, 5 – please add related scholarly and peer-reviewed articles within last 5 years
2/24/22, 12:50 PM Rubric Detail – Blackboard Learn
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Rubric Detail Select Grid View or List View to change the rubric's layout.
Excellent Good Fair Poor
Select a cost analysis for use in your HIT Evaluation Plan Project and justify your choice.
In a 2- to 3-page paper:
Choose one of the �ve main types of analysis Herasevich lists as appropriate for HIT and describe how you might use it to perform an analysis of a �nancial aspect of your chosen case.
32 (32%) – 35 (35%)
The response clearly, accurately, and with speci�c detail describes the type of analysis selected and describes how it may be used to perform an analysis of a �nancial aspect of the chosen case.
28 (28%) – 31 (31%)
The response describes the type of analysis selected and describes how it may be used to perform an analysis of a �nancial aspect of the chosen case.
24 (24%) – 27 (27%)
The response describes in a vague or inaccurate manner the type of analysis selected and/or a description of how it may be used to perform an analysis of a �nancial aspect of the chosen case.
0 (0%) – 23 (23%)
The response describes in a vague, inaccurate, or incomplete manner the type of analysis selected and/or a description of how it may be used to perform an analysis of a �nancial aspect of the chosen case.
Name: NURS_6541_Week8_Assignment2_Rubric EXIT
Grid View List View
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Excellent Good Fair Poor
Describe the key elements you would include in your analysis.
23 (23%) – 25 (25%)
The response clearly, accurately, and with speci�c detail describes the elements to include in the analysis.
20 (20%) – 22 (22%)
The response describes the elements to include in the analysis.
18 (18%) – 19 (19%)
The response describes the elements to include in the analysis in a vague or inaccurate manner.
0 (0%) – 17 (17%)
The response describes the elements to include in the analysis in a vague, inaccurate, or incomplete manner.
Justify your choice and provide a brief explanation of the alternative types of analysis. Explain why each would not be useful to analyze the �nancial aspect of your chosen case.
23 (23%) – 25 (25%)
The response clearly, accurately, and with speci�c detail justi�es the choice with a clear explanation of the choice and the alternatives.
20 (20%) – 22 (22%)
The response justi�es the choice with an explanation of the choice and the alternatives.
18 (18%) – 19 (19%)
The response vaguely justi�es the choice with an incomplete or inaccurate explanation of the choice and the alternatives.
0 (0%) – 17 (17%)
The response vaguely and/or weakly justi�es the choice with an incomplete, inaccurate, or missing explanation of the choice and the alternatives.
2/24/22, 12:50 PM Rubric Detail – Blackboard Learn
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Excellent Good Fair Poor
Written Expression and Formatting — Paragraph Development and Organization:
Paragraphs make clear points that support well- developed ideas, �ow logically, and demonstrate continuity of ideas. Sentences are carefully focused—neither long and rambling nor short and lacking substance. A clear and comprehensive purpose statement and introduction are provided that delineate all required criteria.
5 (5%) – 5 (5%) Paragraphs and sentences follow writing standards for �ow, continuity, and clarity.
A clear and comprehensive purpose statement, introduction, and conclusion are provided that delineate all required criteria.
4 (4%) – 4 (4%)
Paragraphs and sentences follow writing standards for �ow, continuity, and clarity 80% of the time.
Purpose, introduction, and conclusion of the assignment are stated, yet are brief and not descriptive.
3 (3%) – 3 (3%)
Paragraphs and sentences follow writing standards for �ow, continuity, and clarity 60%–79% of the time.
Purpose, introduction, and conclusion of the assignment are vague or o� topic.
0 (0%) – 2 (2%) Paragraphs and sentences follow writing standards for �ow, continuity, and clarity < 60% of the time.
No purpose statement, introduction, or conclusion were provided.
Written Expression and Formatting — English Writing Standards:
Correct grammar, mechanics, and proper punctuation
5 (5%) – 5 (5%) Uses correct grammar, spelling, and punctuation with no errors.
4 (4%) – 4 (4%)
Contains a few (1 or 2) grammar, spelling, and punctuation errors.
3 (3%) – 3 (3%)
Contains several (3 or 4) grammar, spelling, and punctuation errors.
0 (0%) – 2 (2%) Contains many (≥ 5) grammar, spelling, and punctuation errors that interfere with the reader’s understanding.
2/24/22, 12:50 PM Rubric Detail – Blackboard Learn
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Excellent Good Fair Poor
Written Expression and Formatting — The paper follows correct APA format for title page, headings, font, spacing, margins, indentations, page numbers, running heads, parenthetical/in- text citations, and reference list.
5 (5%) – 5 (5%) Uses correct APA format with no errors.
4 (4%) – 4 (4%)
Contains a few (1 or 2) APA format errors.
3 (3%) – 3 (3%)
Contains several (3 or 4) APA format errors.
0 (0%) – 2 (2%) Contains many (≥ 5) APA format errors.
Total Points: 100
Name: NURS_6541_Week8_Assignment2_Rubric
EXIT
,
ORIGINAL RESEARCH
©2018 Un
Evaluation and refinement of a handheld health information technology tool to support the timely update of bedside visual cues to prevent falls in 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 health information technology (HIT) tool, incorporating an iPad device and automatically generated visual cues for bedside display, for falls risk assessment and prevention in hospital.
Methods: This pilot study utilized mixed-methods research with focus group discussions and Likert-scale surveys to elicit clinicians’ attitudes. The study was conducted across three phases within two medical wards of the Queen Elizabeth Hospital. Phase 1 (pretrial) involved focus group discussion (five staff) and surveys (48 staff) to elicit preliminary 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 similar themes as in Phase 1. Qualitative data were evaluated using content analysis, and quantitative data using descriptive statistics 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 falls prevention. They identified potential benefits of the HIT tool in obtaining timely, useful falls risk assessment to improve patient care. During the trial, the wards differed in methods of tool implementation, resulting in lower uptake by clinicians on the subacute ward. Post-trial, clinicians remained supportive for incorporating the tool into clinical practice; however, there were issues with usability and lack of time for tool use. Staff who had not used the tool had less appreciation for it improving their understanding of patients’ falls risk factors (odds ratio 0.12), or effectively preventing hospital falls (odds ratio 0.12). Clinicians’ recommendations resulted in subsequent technological refinement 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 technology use in falls avoidance. Clinicians were willing to use the HIT tool, and their concerns about its usability were addressed in ongoing tool improvement. Including end-users in the development and refinement processes, as well as having high staff uptake of new technologies, is important in improving their acceptance and usage, and in maximizing beneficial 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 among older persons.2,3 Despite the introduction of mandatory
Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
nauthorized reproduction of this article is prohibited.
ORIGINAL RESEARCH
©2018 Un
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 those aged 65 years and over (rate difference 2.08 vs. 1.03 per
1000 patient-days; P¼0.03).22 However, further research was 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.
Methods Ethics approval The 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 methodology Mixed 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 protocol The 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 Margaretõs Rehabilitation
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.
©2018 Un
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).
Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
nauthorized reproduction of this article is prohibited.
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 information technology tool.
ORIGINAL RESEARCH
©2018 Un
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
authorized reproduction of this article is prohibited.
TQEH Ward: GEMU
0700–2000 Day
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:
2001–0659 NightYes
Requires walking aid? UR: 100001
Name: Alice Aliceman Bed No.: 7.1
Figure 3. Example of an automatically generated visual cue from the health information technology tool.
RC-A Teh et al.
©2018 Un
Setting and participants The 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.
Healthcare � 2018 University of Adelaide, Joanna Briggs Institute
nauthorized reproduction of this article is prohibited.
ORIGINAL RESEARCH
©2018 Un
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.
Analysis Qualitative 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.
Results The 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 from focus group session Clinicians’ experience Pretrial, 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 perceptions Incorporating 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 use Clinicians 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 refinement Three 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 from survey participants The 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’ experience No participants had used the HIT tool pretrial.
Positive perceptions The 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 use Less 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
authorized reproduction of this article is prohibited.
T a b le
1 . C o m p a ri so n b e tw
e e n p re tr ia l a n d p o st -t ri a l
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