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Looking for the Best WOW: Understanding the Nurses’ Needs
Bibiana Schachner, Zulma González, Rodrigo Cano, Daniel Luna, Sonia Benítez
Health Informatics Department, Hospital Italiano de Buenos Aires, Argentina
Abstract
The effective use of nurses' time for providing increasingly
safe, efficient, and patient-centered care is a major concern
for healthcare managers as well as for nurses themselves.
Different solutions have been used aimed at improving those
times by providing nurses with mobile and 'on wheels’
alternatives for bedside care. Nevertheless, the selection of
solutions is still a complicated organizational decision. This
paper describes the evaluation of ergonomic characteristics of
five local mobile carts for the bedside nursing care at Hospital
Italiano de Buenos Aires. Cornell University’s checklist was
used for data collection according to five domains: car
handling, work surface and data load, documents and screen
reading, storage and dimensions, and energy and cleaning.
Considering the scarcity of literature on needs for WOWs
assessment, the findings of this paper represent a valuable
approach to the requirements of nurses in real work
environments and a support for decision-making based on
nursing observations.
Keywords:
Computers; Nurses; Informatics
Introduction
The decrease in time that nurses use to perform tasks related
to direct patient care and to document evidence of the care
they provided continues to be a challenge for administrators
and an unmet demand for nurses [1].
The use of computers and workstations on wheels (COWs and
WOWs) is a growing trend for bedside care in healthcare
settings. It is an acceptable notion that the use of time and
coordination of care will be more effective if devices are used
to load the data where they are generated ("point of care") [2].
However, the best solution has not yet been found and
although there are recommendations to take into account while
making decisions on the subject, there is little research about it
[3,4].
Different health professionals can use WOWs but nurses are
the main users, and they use them to record patients’
assessments and to transport medications [3, 5].
Studies show that WOWs for bedside care that are available
on the market have high costs and do not include mobile
technology and other equipment that serve as support. They
also have some other related problems, such as long inactivity
times due to battery recharge, inadequate dimensions, difficult
handling [6], and designs based on the devices’ ergonomics—
and not that of the cart or WOW itself—thus generating low
adherence to use [7].
It is imperative for the development of a mobile app for
nursing data load at the point of care, and for our nurses’
appraisal and needs to make an assessment and collect
information regarding the characteristics of different carts and
workstations on wheels. This is also useful for the selection
that complies with ergonomic recommendations of these
devices in nurses’ bedside care environments.
Methods
Setting
The study was conducted at the Hospital Italiano de Buenos
Aires (HIBA), an academic hospital founded in 1853, located
in Buenos Aires, Argentina. As a JCI-accredited and stage 6+
HIMSS-EMRAM hospital, HIBA belongs to a nonprofit
healthcare network including 25 outpatient centers and 150
offices located in the city of Buenos Aires. It has an
infrastructure supporting 750 inpatient beds, 41 operating
rooms, and a home care network with 800 beds. The
organization employs nearly 2800 physicians, 1600 nurses,
and 1900 employees in administrative services and
management. In the past 20 years, HIBA has developed and
implemented an “in house” health information system,
including clinical and administrative data. The electronic
health record (EHR), named ITÁLICA, is a modular,
problem-oriented, and patient-centered system with different
settings (outpatient, inpatient, emergency, and home care). It
includes clinical documentation system, medication
administration using bar coding (intensive care areas), and
computerized provider order entry (CPOE). Sections
according to the stages of the nursing care process organize
the electronic nursing record. Nurses must also diagnose using
NANDA-I taxonomy II diagnoses classification and care plan
that is based on the nursing interventions classification (NIC).
Study design
This study was cross-sectional, observational and descriptive
work, with mixed methodology.
Phase 1:
We used three workstations on wheels (named Dina, Jordan,
and Andrea) from July 21 to August 15, 2016. Different local
suppliers provided them according to pre-established
requirements based on the various necessary characteristics.
The supppliers did not provide WOWs with bar code scanners,
computer or mobile devices such as a PC tablet (except for
Andrea) (Figure 1), because the purpose was to evaluate the
carts alone at this stage and to assess devices and barcode
readers in a subsequent stage.
A convenience sample was performed. Data collection was
made through observations made by the adult and pediatric
general care nurses from four different wards, including five
nursing shifts (morning, afternoon, night number 1, night
number 2, and weekends). They were provided with a copy of
MEDINFO 2017: Precision Healthcare through Informatics
A.V. Gundlapalli et al. (Eds.)
© 2017 International Medical Informatics Association (IMIA) and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms
of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
doi:10.3233/978-1-61499-830-3-212
212
a Cornell checklist, translated into Spanish, which included
ergonomic factors for computer carts in health environment.
The Cornell checklist is developed by the Cornell University
and represents a guide on considerations to evaluate a single
cart or a WOW. Taking into account the anthropometric data
of adults in the USA, the Cornell checklist is organized into
five sections: a) Cart maneuvering; b) Work surfaces and data
input; c) Screen reading; d) storage/accessories/power; and e)
Hygiene in addition to free space for comments. The items of
each section have a binary response (Yes/No) option about
whether the cart satisfies the item or not. If all items are
relevant, the total number of "yes" values can be added at the
end of each of the five sections and the overall total score can
be summarized at the end of the entire checklist. The
maximum possible score is 35 and the higher score represents
the computer cart with better ergonomic design. A list of
activities to be carried out by the nurses with each computer
cart was drawn up in the chosen areas before answering the
checklist (Table 3). These activities were presented and
explained to the nurse teams. Once the days established in the
work plan schedule were met, the cart in a particular area was
removed along with the filled checklists and a new cart was
delivered to that area. Once the cart had completed its rotation
in all the four sectors, it was returned to the Health Informatics
Department.
The data based on the responses by the nurses for each cart by
area and nursing shift were manually entered into an Excel®
data sheet. We performed descriptive statistics for each cart
with Stata®13. We used non-parametric Kruskal-Wallis test
for independent samples to compare differences between the
carts. Then we calculated a pairwise comparison of total
scores sorted by each cart with the Dunn’s procedure.
Furthermore, comments made in the comment space by the
nurses in each ward were analyzed independently by the
Informatics nurses to gain additional insight about items that
were possibly not in the structured checklist.
Phase 2:
Once the data were processed and analyzed, the cart with the
best score was returned to the supplier for the necessary
adjustments and improvements. A new provider handed over a
new cart called Mariano. The WOW ‘ANDREA renewed’ and
MARIANO were delivered to the same sectors and teams of
nurses who had participated in the Phase 1 from October 20 to
November 9 for following the same methodology that we used
in the first phase. Then we performed descriptive statistics for
each cart, and a t-student test to compare means from the two
phases.
Results
A total of 59 checklists were completed during the three-week
rotation of the carts during the first phase. ANDREA was
evaluated 20 times, obtaining a minimum score of seven and a
maximum of 34, with a mean of 15.85 points (SD 6.9).
Meanwhile DINA was also evaluated 20 times, obtaining a
minimum score of three and a maximum of 16, with a mean of
6.7 points (SD 3.2). On the other hand, JORDAN was
evaluated 19 times obtaining a minimum score of two and a
maximum of 16, with a mean of 7.3 points (SD 3.7). Figure 1
shows the carts evaluated in both the phases and Table 1
summarizes the total number of observations for each cart by
sector with respective mean, the standard deviation, as well as
the minimum and maximum score obtained per sector.
ANDREA got the best scores in the carts observed and it was
selected for a new evaluation after its reconfiguration by the
supplier. The main improvements requested from ANDREA's
supplier were in the areas of the handle with a better grip, the
tray and the bracket where the optical scanner would hang,
and the main pillar where the internal power cables of the
device and battery would fit in. The other two (DINA and
JORDAN) were discarded. A Kruskal-Wallis test was
performed to compare differences between carts. With a type I
error of 5%, at least one of the carts had a total score different
from the rest (Chi-squared (23.39 (2d.f.), p = 0.0001). Then,
after controlling with Dunn's pairwise comparisons, we
encountered statistical significant differences between
ANDREA and DINA (4.66, p < 0.00001), ANDREA and
JORDAN (4.01, p = 0.0001), and non significant difference
between DINA and JORDAN ( -0.059, p=0.8280)
A total of 52 checklists were completed during the second
phase. The scores obtained by ‘ANDREA renewed’ and
MARIANO were similar in general but varied by areas.
Nevertheless, the t-student test to compare the means of total
scores resulted in a statistic of 0.812 (50 d.f.) and a p value of
0.4209, showing that there is no statistically significant
difference for the evaluation of the characteristics evaluated
by the nurses with Cornell's checklist.
Table 2 summarized the total number of observations.
Figure 1 – evaluated WOWs
Figure 2 – Scores per cart, area and shift – phase 1
Comments analysis
We mention the themes that emerged in the first phase from
nurses' comments related to the topics in the Cornell's
checklist. Nursing staff in each ward identified several
negative features of WOWs: lack of stability and difficulty in
maneuvering (DINA), noise, unstable cart wheels, large
footprint that made ‘it impossible to walk beside it
(JORDAN)’.
B. Schachner et al. / Looking for the Best WOW: Understanding the Nurses’ Needs 213
Table 1 – Assessment of Carts by Sectors and Shifts
Cart Sector
2 8 20 37
ANDREA
Observation by
area 55 55
Mean 25.6 10.6 13.2 14
SD 5.12 3.91 2.04 4.18
Minimun score 21 7 11 7
Maximun score 34 17 15 18
DINA
Observation by
area
55 55
Mean 6.8 5 10 5
SD 2.58 1.41 4.41 1.58
Minimun score 3 3 6 3
Maximun score 10 6 16 7
JORDAN
Observation by
area
45 55
Mean 8.75 6.4 5.8 8.8
SD 2.62 4.33 2.68 4.71
Minimun score 6 2 3 5
Maximun score 11 11 9 16
Adult general care: sectors 2, 20 and 37. Pediatric general care: sector 8
Table 2– Assessment of ‘ANDREA renewed’ and MARIANO
Cart Sector
2 8 20 37
‘ANDREA
renewed’
Observation by
area 91 59
Mean 18.67 20 16 17.78
SD 4.58 6.67 3.15
Minimum score 10 20 8 10
Maximum score 27 20 26 21
MARIANO
Observation by
area
54 712
Mean 18.6 13.5 15.28 18.16
SD 2.07 5.26 4.15 4.04
Minimum score 17 9 8 12
Maximum score 22 21 20 25
The size ‘too small’ or ‘inadequate’, adding a basket and a
handles emerged as very important aspects. The main theme in
all the observations was that the tray was ‘inappropriate to
administer the medications’, as it was very small or had no
containment edges.
The theme related to the need for more comfortable handles
and the basket, as well as the noise when moving the carts
emerged again in the second phase. The nurses appreciated
the improvements from the previous evaluation for ANDREA,
but now it was ‘too big to mobilize considering that patient
rooms are small’. Another new element was that the power
cable was ‘very short’.
Table 3 – Activities List
Activities
Handle the cart by "pulling" the handle
Adjust handle to fit comfortably
Pull and push the cart, causing it to move
Move the cart in a certain direction
Move the cart through different areas where you walk for
your work:
oNursing Station
oPreparation of medication area (Bunker)
oHallways
oPatient Room
Elevate the work surface of the cart more than one meter
from the floor
Take notes on the work surface of the cart
Place the medication tray on the work surface and move
the cart to a room
Adjust the inclination of the working surface of the cart
Turn the work surface of the cart
Lift and lower the platform for the keyboard as if to use it
to write while:
oStanding
oSeating
Type on the surface where the device's keyboard would
go
Put the items you use to do your work in the cart and
move it through different areas
Brake the wheels of the cart and try to move it
Remove the wheel brake of the cart
Throw liquid (small amount) onto the work surface and
wipe it with a dressing
Rotate the bracket for the device to left and right without
moving the cart
Rotate the bracket for the device up and down (changing
the angle) without moving or turning the cart
Discussion
We performed an ergonomic assessment of five WOWs for
bedside nursing care, seeking to find a solution to difficulties
experienced by our nurses in collecting data at the point of
care, and also for the purpose of improving communication
and coordination of care. We aligned our work with suggested
changes in healthcare systems to achieve more effective
processes that truly support the way care is delivered and
transformed [8][9].
Our evaluation examined the ergonomic characteristics
available and desired in mobile stations. ANDREA showed a
significant advantage over the other carts in the first phase and
B. Schachner et al. / Looking for the Best WOW: Understanding the Nurses’ Needs214
renewed ANDREA continued in the race for a new evaluation.
None of the carts, however, obtained the maximum score, that
is, none has all the required characteristics. Some aspects
continue to not meet the needs of some nurses at the start of
the third phase. This could suggest a low adherence to cart use
in future, even more so if we do not include the devices in this
stage. Some aspects represent enhancements, such as inability
to rotate the axis of the device used to document the patient
care, size of the cart perceived by nurses as 'bulky' and
difficult to mobilize. Such aspects limit the storage and
efficient mobilization [6] in zones in which they will be
deployed.
The results of this work can not be generalized since it was
performed in a single hospital center. Furthermore, there was a
lack of consistency in some answers—for example, user
answered only a single survey in one ward in Phase 2—
probably because they were self-administered by the nursing
staff.
ANDREA was provided with a tablet and that feature had not
been included during the previous training to the nurses. We
had instructed them to ignore it, however, some observations
may have been influenced by the mere presence of the device.
Two Health Informatics research interns, an Informatics nurse,
and an Informatics physician agreed upon and decided on the
final version of the English-Spanish translation process. The
Cornell University's checklist [10] is neither externally
validated nor adapted to Spanish; nevertheless, its use
provided us a first approximation to the needs of nurses
related to mobile workstations. We could include all the HIBA
nursing shifts to strengthen our evaluation instead of using
only the weekly day shifts. On the other hand, when we
discarded the 'worst' carts in terms of score and reconfigured
the best positioned cart, we received better response from the
nurses who thought that their input was taken into account.
We benefited from creating an elaborate list of activities—that
simulated real-wrold scenarios in daily practice—before the
evaluation. We are about to start a bedside care pilot study,
indicating the third phase of WOW evaluation, with a new
version of MARIANO renewed based on the findings and
suggestions of the second phase. We also plan to incorporate a
tablet PC, a bar-code scanner, and the test of the mobile app
for nursing bedside care.
Acknowledgements
The authors would like to thank the nurses who participated in
the evaluation study and acknowledge the collaboration
between the Nursing Department and Health Informatics
research.
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