Emergency medical equipment storage: benefits of visual cues tested in field and simulated settings.

514605 2013

HFS56510.1177/0018720813514605Human FactorsIllustrated Divider in Emergency Drawers

Emergency Medical Equipment Storage: Benefits of Visual Cues Tested in Field and Simulated Settings Tobias Grundgeiger, Julius-Maximilians-Universität Würzburg, Germany, Bonnie Harris and Nicholas Ford, University of Queensland, Brisbane, Australia, Michael Abbey, Princess Alexandra Hospital, Brisbane, Australia, Penelope M. Sanderson, University of Queensland, Brisbane, Australia, and Balasubramanian Venkatesh, Princess Alexandra Hospital, Brisbane, Australia Objective: We tested the effectiveness of an illustrated divider (“the divider”) for bedside emergency equipment drawers in an intensive care unit (ICU). In Study 1, we assessed whether the divider increases completeness and standardizes the locations of emergency equipment within the drawer. In Study 2, we investigated whether the divider decreases nurses’ restocking and retrieval times and decreases their workload. Background: Easy access to fully stocked emergency equipment is important during emergencies. However, inefficient equipment storage and cognitively demanding work settings might mean that drawers are incompletely stocked and access to items is slow. Method: A pre-post-post study investigated drawer completeness and item locations before and after the introduction of the divider to 30 ICU drawers. A subsequent experiment measured item restocking time, item retrieval time, and subjective workload for nurses. Results: At 2 weeks and 10 weeks after the divider was introduced, the completeness of the drawer increased significantly compared with before the divider was introduced. The divider decreased the variability of the locations of the 17 items in the drawer to 16% of its original value. Study 2 showed that restocking times but not retrieval times were significantly faster with the divider present. For both tasks, nurses rated their workload lower with the divider. Conclusions: The divider improved the standardization and completeness of emergency equipment. In addition, restocking times and workload were decreased with the divider. Application: Redesigning storage for certain equipment using human factors design principles can help to speed and standardize restocking and ease access to equipment. Keywords: health care quality improvement, patient safety, equipment design

Address correspondence to Tobias Grundgeiger, Institute for Human-Computer-Media, Julius-Maximilians-Universität, Oswald-Külpe-Weg 82, 97074 Würzburg, Germany; e-mail: [email protected]. HUMAN FACTORS Vol. 56, No. 5, August 2014, pp. 958–972 DOI: 10.1177/0018720813514605 Copyright © 2013, Human Factors and Ergonomics Society.

Introduction

Intensive care units (ICUs) care for very ill patients whose physiological and clinical status can change rapidly, often requiring emergency interventions. Consequently, equipment and supplies for fast interventions, such as adrenalin, must be readily available and easily accessible when needed (Agarwal et al., 2005; Donchin, 2002). ICU staff make frequent checks on both the availability and functionality of all emergency items within bedside drawers. However, the list of emergency items that are required is often long, and critical care environments are cognitively demanding (DeLucia, Ott, & Palmieri, 2009). For example, distractions and interruptions are frequent (Grundgeiger & Sanderson, 2009) and may increase the likelihood that checks of the emergency equipment are incomplete (Smith et al., 2008). In the present studies, we used human factors principles to redesign an emergency drawer. In Study 1, we investigated potential benefits of the redesign on item completeness, standardization of item locations in the drawer, and nurses’ perceptions. In Study 2, we investigated nurses’ performance at restocking and retrieving items from the drawer as well as their subjective workload. Across several studies, researchers have attempted to improve access to emergency items in code carts by applying human factors principles (e.g., Agarwal et al., 2005; Chitkara, Rajani, Lee, Hansen, & Halamek, 2013; McLaughlin, 2003; Merry et al., 2011; Rousek & Hallbeck, 2011; Schultz et al., 2010). For example, McLaughlin (2003) showed that nurses could retrieve drugs faster when the layout of code cart drawers was redesigned. More recently, Rousek and Hallbeck (2011) redesigned code cart drawers, and Chitkara et al. (2013) introduced a code

Downloaded from hfs.sagepub.com at Univ. of Tasmania Library on September 27, 2015

Illustrated Divider in Emergency Drawers

cart to a neonatal resuscitation area. In both cases, the new drawers reduced item retrieval times. Moreover, staff felt that it was easier to use the newly designed drawers and preferred them to the previous arrangements. In the ICU under study, at the start of our investigation, 17 items were located in an emergency bedside drawer near the head of the patient’s bed. Five items were used for routine tasks, such as patient assessment, and 12 items might be required during an emergency. The items were placed loosely in the otherwise empty drawer without any mandated locations. Therefore, the locations of the items were not standardized across the unit, and items shifted each time the drawer was opened and closed. The drawer contents were checked for completeness twice at the start of each shift. A complete list of the intended contents was available at each bedside for use as a checklist. Notwithstanding, a senior nurse estimated that in 90% of the drawers, at least one item was missing. A clinician noted that any item missing can be of critical importance in an emergency. In a previous observational study in the same ICU, before the redesigned drawer was in use, a distracted nurse had missed the fact that a Guedel’s airway was absent from a drawer (Grundgeiger, Sanderson, MacDougall, & Venkatesh, 2010). If the patient’s airway had later become blocked, there would have been a delay in restoring the patient’s breathing. Moreover, using the checklist required additional time and effort, such as walking between the checklist and the drawer, because the list was seldom available next to the drawer; as a result, memory was often used. Finally, research has shown that if people use items that are present to search memory for items that are absent, the likelihood of remembering the absent items might actually decrease (part-list cuing effect; see Slamecka, 1968). Overall, it was apparent that there was room for improvement. Restocking the drawer is a habitual prospective memory task, whereby an individual needs to remember to execute a task in the future that consists of multiple steps that have been performed repeatedly in the past (see discussion in Dismukes, 2010; Ellis, 1996; Meacham & Leiman, 1982). Theoretically, the successful performance of a habitual memory task depends on how well each task step is cued by the preceding steps

959

and by the context of the task (Dismukes, 2008; Meacham & Leiman, 1982). Given the relative unavailability of the checklist and in the absence of strong cues for each step, the linkages between each step may have become vulnerable to forgetting or to distraction. Using human factors principles for redesigning a task (Gosbee, 2002), an alternative method to either using the checklist for cuing drawer contents or relying on unaided habitual prospective memory would be (a) to use a divider to assign specific slots in the drawer for each piece of equipment and (b) to provide pictorial illustrations for the equipment in the divider slots. Clearly, the illustrations would cue the items and would reduce the habitual prospective memory load of restocking the task. In addition, the illustrations would work to standardize all the bedside emergency equipment drawers in the unit. If proven to be successful, the principles used to design the divider could apply to other contexts where sets of equipment must be kept complete. In the current paper, we report two studies investigating the effectiveness of an illustrated divider system (the “divider”). The aim of Study 1 was to test whether the introduction of the divider to the emergency bedside drawers would improve the completeness and standardization of drawer contents and whether nurses would prefer it. After Study 1 was completed, the nurses voted to keep the dividers in the drawers. The aim of Study 2 was to probe more deeply into possible reasons that nurses valued the drawers so highly, using dependent variables more directly related to restocking and retrieval tasks, such as speed and subjective workload. Study 1

The aim of Study 1 was to test whether the introduction of the divider to the emergency bedside drawers would (a) increase item completeness in the drawers, (b) standardize equipment locations between bedside drawers, and (c) affect parameters of the daily check, such as nurses’ perception of the duration of the check or nurses’ confidence in its completeness. Method

Participants and setting. The study was conducted in a tertiary ICU with 30 beds. Ten beds


960

August 2014 - Human Factors

were postoperative beds, mostly for elective patients staying less than 24 hr in the ICU. Twenty beds were general ICU beds, mostly for patients staying for several days or more in the ICU. Approximately 190 nurses work in direct patient care. Local hospital and university ethics committees approved the study. A note on the ICU research board informed nurses that a redesign of the drawers was being conducted to make the drawers tidier and easier to use. Otherwise, ICU staff were blind to the kind of data being collected or the specific outcomes we sought, and they were not informed about the specific days of data collection. Study design and data collection. The intervention was evaluated in three ways. First, we compared drawer item completeness for occupied beds before introduction of the divider with completeness at 2 weeks and at 10 weeks after introduction of the divider. Because the two ICU areas have different patient cases and turnaround times, the factor ICU area (postoperative ICU, general ICU) was included in the design. A separate completeness analysis was conducted for empty but ready-to-use beds for the three different points in time. Empty but ready-to-use beds should have their bedside drawers fully stocked, but nurses still have a chance to restock before a patient arrives. Second, the location of items in the drawer was noted preintroduction and postintroduction to evaluate the standardization of the item locations. Third, a questionnaire was administered to evaluate nurses’ perceptions of the drawer. The study was conducted from October 2009 until February 2010 and included six phases, outlined next. Weeks 1 to 4: Preintroduction data. As a baseline, data about item completeness in the drawers were collected before the divider was introduced. Four completeness audits spread across 4 weeks were conducted. For each bedside, a completeness percentage score was calculated by dividing all items present (whether in the drawer, on top of the drawer, or in use) by the 17 possible items. Data were collected for occupied beds and for empty beds that were ready for use. Average completeness scores were calculated for

each bedside across the four audits that were used for the analysis. To assess the effect of the dividers on standardization, the locations of the items were noted during the fourth audit. Weeks 5 to 9: Illustrated divider design. During this period, the drawer divider and the labels illustrating each item were designed and verified (see section Drawer and Label Design Process). Weeks 10 to 11: Divider introduction. The divider was introduced to the bedside drawer in all 30 ICU beds. All nursing staff were notified about the divider by e-mail. The introduction was followed by a 2-week period to allow nurses to familiarize themselves with the divider. Weeks 12 to 15: Two weeks postintroduction data. Item completeness was assessed in four completeness audits, as for the preintroduction data collection. Again, items were considered to be present if they were in the drawer (independently of whether they were in the correct location), on top of the drawer, or in use. Weeks 16 to 19: Questionnaire. For a 4-week period, a questionnaire was available to nurses that could be completed and dropped into a box provided. The questionnaire consisted of 7-point Likert-type scale questions that asked nurses for their perceptions of the divider. The questions addressed whether the divider (a) made safety checks faster and (b) easier, (c) reminded nurses of missing items, (d) increased nurses’ confidence that all items are present, (e) made access in emergencies easier, and (f) was useful overall. In addition, we asked which three things nurses liked most and disliked most about the divider. Weeks 20 to 23: Ten weeks postintroduction data. Item completeness was assessed in four completeness audits, as for the preintroduction and 2 weeks postintroduction data collection. In addition, the locations of the items were noted during the fourth audit.

Drawer and label design process. The design process took place during Weeks 5 to 9 of the



961

Figure 1. Location of equipment in drawer without and with divider. Lower section: Locations in the drawer with or without the divider. The larger the font, the more items were at this location. Font is intended not to be legible but to illustrate the variability of item locations. Missing or used items are not represented. Upper section: Drawer in one of many possible arrangements without the divider (left) and with the divider (right).

study. Off-the-shelf drawer dividers were purchased from a storage shop. During the design of the divided drawer, nurses’ preferences for item locations in the drawer were preserved as much as possible. As shown in Figure 1, some items (emergency medication) were always located in the front right corner of the undivided drawer. This preference was probably due to the importance of such medication in an emergency. Other items, such as the vomit bag, were usually located in the back of the drawer. This placement may have been because such items were less frequently used, but it may also have been because when at the back of the drawer, they were less likely to obscure other items. The 17 items were photographed and electronically

enhanced. Each item was printed in black with the relevant name on a yellow, 24-mm label. The top right photo in Figure 1 shows the illustrated divider filled with items. The design of the pictorial representations was guided by existing research. Specifically, pictorial warnings increase compliance compared with written warnings (Wogalter, Begley, Scancorelli, & Brelsford, 1997). Colored warnings increase compliance (Kalsher & Williams, 2005), black on yellow increases legibility compared with black on white (Frascara, 2005), and yellow is associated with caution (Wogalter, 2005). To collect feedback on the proposed location of the items in the drawer, an A4 printout of the


962


Table 1: Emergency Drawer Completeness Across the Phases of Study 1 (in percentages) Preintroduction M (SD) Occupied beds Postoperative ICU General ICU Average across ICU areas Empty beds

2 Weeks Postintro- 10 Weeks Postintroduction M (SD) duction M (SD)

Average Across Time Points (SD)

94.19 (3.05) 98.20 (1.64) 96.93 (2.86)

97.34 (2.70) 98.20 (2.18) 97.93 (2.23)

96.78 (1.91) 98.95 (1.57) 98.26 (1.94)

96.10 (2.55) 98.45 (1.80) 97.71 (2.34)

92.28 (9.78)

95.49 (5.28)

98.24 (2.84)

95.23 (5.97)

Note. ICU = intensive care unit.

divider was shown to 14 nurses in the ICU. A total of 21 suggestions about locations were made by the nurses, and the three most frequently mentioned suggestions were adopted. To test whether the illustrations of the items were recognizable, the 14 nurses were asked to name the items on printouts with the name absent. Because the illustrations had a low resolution, some nurses had trouble identifying 4 of the 17 items. Those 4 items were photographed again to improve the resolution of the final labels (no further formal testing was done). For six beds, the divider needed to be adjusted because the bedside drawers were slightly smaller. Some of the items for these drawer dividers were repositioned, resulting in a slightly different layout. Data analysis. Differences in completeness scores for occupied beds were tested by calculating a 3 × 2 mixed ANOVA with the repeated measures factor time (preintroduction, 2 weeks postintroduction, 10 weeks postintroduction) and the grouping factor ICU area (postoperative ICU, general ICU). Differences in completeness for empty beds ready for use were calculated with the use of a Kruskal-Wallis test because variances were not homogeneous. To examine the standardization of item locations in the drawer, we represented the locations of items noted during preintroduction and 10 weeks postintroduction in tag clouds. In the present case, in the tag cloud, font size represents the frequency of an item at a specific location. The questionnaire was evaluated with the use of an exploratory factor analysis, a one-way ANOVA, and t tests for independent samples. All tests were

conducted with SPSS 17.0 (SPSS Inc., Chicago, IL), and alpha was set at .05. Results

Equipment completeness. The 3 × 2 mixed ANOVA showed a significant difference in item completeness between the three data collection times, F(2, 40) = 3.933, p = .028, ηp2 = .20, and worse completeness for the postoperative ICU compared to the general ICU, F(1, 20) = 19.68, p < .001, ηp2 = .50, but no significant interaction between the two factors, F(2, 40) = 2.80, p = .07 (see Table 1). Planned contrasts between successive weeks, collapsed over ICU area, showed that completeness (a) increased significantly from preintroduction compared with 2 weeks after the divider was introduced (p = .040) and (b) increased significantly from preintroduction to 10 weeks after the divider was introduced (p = .020). To check whether the slightly different layout of the divider for the six beds with smaller drawers affected the completeness scores, we conducted an additional 3 × 2 mixed ANOVA with the factors data collection time and divider layout. The result showed a significant effect only of data collection time, F(2, 46) = 4.729, p = .014, and no other significant effects: divider layout, F(1, 23) = 2.628, p = .119; interaction, F(2, 46) = .039, p = .962. The Kruskal-Wallis test showed that the numeric increase in drawer completeness for beds that were empty, but ready to use, was not significant (χ2 = 3.572, df = 2, p = .17). Standardization. If each of the 17 emergency items were always in its correct location in the drawer, the number of item locations observed



on any audit would be exactly 17. As it was, in the preintroduction audit without the divider, 73 item locations were observed (329% more than the optimum of 17), but in the postintroduction audit, with the divider, only 26 item locations were observed (53% more than the optimum of 17). This finding represents a reduction of suboptimal item locations with the divider (26 – 17 = 9 suboptimal locations) to just 16% of what it had been without the divider (73 – 17 = 56 suboptimal locations). The tag clouds in Figure 1 show exactly where each item was found in the aforementioned two sampled audits. Data without the divider are based on n = 22 beds; data with the divider are based on n = 21 beds (the n is unequal as some beds were unoccupied when the audits were done). Font size represents the number of observed instances of an item being found at a given location. On only five occasions out of an audit of approximately 300 drawers was a nonemergency item found in a drawer. We also tested whether the different layout of the divider for the smaller drawers affected standardization. Across the two kinds of drawers, we used Fisher’s exact test to compare whether all items were in their designated locations or whether at least one item was not in its designated location. We found no difference across the two types of drawers. For the regular dividers, 8 of 16 drawers (50%) had all items in the designated locations, whereas for the different dividers, 2 of 5 drawers (40%) had all items in the designated locations, Fisher’s exact test, p > .05. Questionnaire. Overall, 50 questionnaires were returned, which was an approximately 41% response rate, given that only 122 nurses were rostered during the evaluation period, and approximately a 28% response rate if all 176 nurses involved in direct patient care were considered. The demographics of the sample were as follows: age (20–25 years, n = 10; 26–30 years, n = 12; 31–35 years, n = 13; 36+ years, n = 15), years worked as registered nurse (M = 9.46, median = 8.50), years worked at the ICU under study (M = 4.66, median = 3.00), and number of shifts worked with divider (90% > 11 shifts). Quantitative measures. An exploratory factor analysis (maximum likelihood extraction; criteria

963

eigenvalues > 1) included the six questions (see Method section, Weeks 16 to 19) and revealed one factor explaining 83.65% of the variance associated with satisfaction with the divider. Accordingly, we developed a single scale using the mean of the six items. The internal consistency of the scale was high (Cronbach’s alpha = .96). Based on the content of the six questions, we refer to the single factor as “satisfaction with the divider.” The mean satisfaction with the divider for all participants was 4.08 (SD = 2.09) on a scale from 1 to 7 (higher score indicates more satisfaction with the divider). A median split for years worked in the local ICU showed that nurses who had worked for less than 3 years at the ICU in question (M = 4.72, SD = 1.93, n = 27) were more satisfied with the divider than were nurses who had worked more than 3 years at the ICU (M = 3.33, SD = 2.05, n = 23), t(48) = 2.473, p = .017, d = .70. A median split comparison for total work experience as a registered nurse showed no difference in satisfaction with the divider between nurses with less than 8.5 years of experience (M = 4.22, SD = 2.01, n = 25) and nurses with more than 8.5 years of experience (M = 3.94, SD = 2.20, n = 25), t(48) = .775, p = .637. Similarly, there was no difference in satisfaction with the divider between the age groups 20 to 25 years (M = 4.44, SD = 1.76, n = 10), 26 to 30 years (M = 4.72, SD = 2.21, n = 12), 31 to 35 years (M = 3.89, SD = 2.10, n = 13), 36+ years (M = 3.49, SD = 2.18, n = 15), F(3, 46) = 0.905, p = .446. Qualitative measures. Table 2 categorizes nurses’ open-ended comments about what they liked and disliked most about the divider and reports a count of each kind of comment. The most frequently cited like was the fact that the divider made the drawer organized. The most frequently cited dislike was the potential for clutter with the divider. Discussion

The cardinal findings of Study 1 were that an illustrated divider increased item completeness in the bedside emergency equipment drawers and standardized the location of equipment in the drawers. Nurses who had a lower level of experience in the ICU under study were more satisfied with the divider. The findings


964


Table 2: Qualitative Results of the Questionnaire (n = 50) What are the three things you like most about the divider? 1. Was organized 2. Acted as a reminder 3. Other 4. Standardized across ICU 5. Items do not move 6. Removing all content easy Total

What are the three things you dislike most about the divider? 40 (53.3%) 20 (26.7%) 6 (8.0%) 4 (5.3%) 3 (4.0%) 2 (2.7%)

75 (100%)

1. Was cluttered 2. Required extra cleaning 3. Other 4. Not standardized across ICU 5. No space for additional items 6. Some compartments too small 7. Real professionals should not need it 8. Less concentrated checking 9. Items at wrong places Total

23 (27.1%) 14 (16.5%) 11 (12.9%) 10 (11.8%) 7 (8.2%) 7 (8.2%) 6 (7.1%) 5 (5.8%) 2 (2.4%) 85 (100%)

Note. The table shows frequencies of categorized comments to the two open-ended questions in the questionnaire. Percentages in parentheses report the percentage of comments in a category out of the total number of answers to that question. ICU = intensive care unit.

are consistent with research on checklists and daily worksheets that show improvements in safety (Hales & Pronovost, 2006; Halm, 2008) and with previous work on code cart redesign involving human factors principles (e.g., Rousek & Hallbeck, 2011). It is possible that the yellow labels at each equipment location in the divider increased restocking compliance by reminding nurses of missing items. This explanation is supported by the questionnaire answers. It is also supported by the findings of a subsequent full-scale simulation study that showed that distracted nurses were significantly more likely to notice a missing item when the illustrated divider was present rather than absent (Grundgeiger et al., 2013). The worse item completeness in the postoperative ICU compared to the general ICU might reflect the higher patient turnover and a different pattern of use of drawer items within the postoperative ICU. Finally, the questionnaire indicated that nurses who are new to the ICU might benefit more from the divider, possibly because providing visual cues eases equipment checks and increases nurses’ confidence in the completeness of the drawers. Neither the length of the nurses’ experience working as an RN nor their age was associated with their satisfaction with the divider. The qualitative data indicated that most nurses perceived the divided drawer arrangement as organized, and many reported that the

locations and labels acted as reminders, possibly reducing the workload of restocking. Research on compliance with instructions and warnings indicates that people’s likelihood of complying with rules increases as the effort or time involved in complying decreases (see Kalsher & Williams, 2005; Rogers, Lamson, & Rousseau, 2000). In Study 2, we measured subjective mental workload associated with restocking and retrieval processes to test whether the divider indeed decreases workload. Whether the drawer is fully stocked is no doubt affected by factors other than the design of the drawer. Even if the divider reduces workload, nurses may forgo restocking the drawer if they believe that the missing items pose very little risk or if the relative inconvenience of checking and restocking the items outweighs the potential benefits of doing so (Wogalter & Laughery, 1996). Furthermore, staff members may not necessarily perform the required check (Smith et al., 2008). The qualitative data also revealed nurses’ perceptions of the disadvantages of using a divider, for example, the need for additional cleaning, the perception by some nurses that the divider implied they had professional weaknesses rather than being a supporting artefact, and the perception that some nurses might rely on the labels and perform less rigorous checks. The latter two problems have also been raised about the



introduction of checklists in critical care contexts (Hales & Pronovost, 2006). Finally, some nurses expressed concern that the drawer divider was not standardized across the ICU. Limitations. Study 1 has weaknesses, some of which are inherent to pre-post study designs. First, the repeated testing for drawer completeness and item locations is a possible limitation. Fortunately, no changes in completeness were discovered across the four repeated drawer audits within any of the three data collection periods, suggesting that changes in drawer contents were caused by other factors than testing alone. Second, the completeness data that were collected 10 weeks postintroduction of the divider might have been affected by the previous administration of the questionnaire. However, the data collected 2 weeks postintroduction already showed an increase in completeness similar to the subsequent increase for the data collected 10 weeks after introduction of the dividers, suggesting that the questionnaire could not have had a strong influence. Third, the increase in item completeness might seem small and of little clinical significance. The very high baseline level of completeness of 96.93% did not leave much room for improvement. However, any missing item could have safety consequences in an emergency; therefore, 100% completeness is important. Moreover, if the same kind of intervention were applied to storage in other hospital areas where there is a lower baseline level of completeness, there might be stronger effects. Fourth, we cannot rule out the possibility that the note on the research board prior to the study or the presence of the researcher (TG) during the study may have caused reactive behavior by the nurses. However, the note was unspecific about the data that were to be collected (completeness score), and the researcher was known to nurses from previous studies and observations. We therefore consider reactive behavior as rather unlikely. Unresolved issues. At present, the illustrated dividers are still in the bedside emergency drawers in the ICU under study because the nursing staff voted to retain them after Study 1 was finished. The results of Study 1 suggest that the

965

nurses may have wished to keep the illustrated divider because of the improvement in how completely the drawers were stocked and because the labels reminded them of the items that were missing. In Study 1, we recorded only the completeness and standardization of drawers and did not measure the potential benefits of the divider on variables more directly related to efficiency and workload. We therefore conducted a second, more controlled, study to examine these factors. Study 2

The goal of Study 2 was to compare the speed and accuracy with which the ICU nurses can restock the bedside emergency equipment drawer and retrieve items from it with and without the divider. The goal was also to measure nurses’ subjective mental workload to test whether the divider reduced subjective mental workload. In pilot work using office stationery items and student participants, we prepared a drawer restocking task and an item retrieval task (Harris, Ford, Sanderson, Grundgeiger, & Venkatesh, 2013). We established that when the drawer contained an illustrated divider, our pilot participants could restock the drawer in only around 55% of the time it took to restock when it had no divider or illustrations. Surprisingly, however, when we tested how quickly participants could retrieve items called out in rapid succession, we found that our participants took a small but significant 5% longer when using the illustrated and divided drawer. Despite this finding, at the end of the pilot experiment, 32 of our 36 participants reported that they preferred working with the divided drawer. In Study 2, we used the same drawer restocking task and item retrieval task that we had used in the Harris et al. (2013) pilot study. However, we now used participants who were nurses in the same ICU where the illustrated drawer divider is currently being used, and we used the normal ICU bedside emergency items. The restocking task tested whether the divider helped participants to identify missing items from each drawer more quickly and accurately than they could without the divider. The number of items missing from the drawers


966


during the restocking task was manipulated with four levels of completeness: zero or one item missing replicated the most commonly observed completeness of drawers in the ICU, and five or eight items missing replicated a halfempty drawer, such as might occur after a medical crisis. The retrieval task was intended to replicate partially the findings of Rousek and Hallbeck (2011), who found that health care workers could retrieve items from an emergency medication cart faster and more accurately when the layout of cart drawers was designed to achieve visibility, grouping, and organization. In our retrieval task, participants reported the presence or absence in the drawer of a series of items whose names were called out in rapid succession. We expected that participants would perform the restocking task faster with the divider than without the divider. Furthermore, as the number of items missing increased in the restocking task, performance without the divider would slow down more than would the performance with the divider. We also expected that participants would perform the retrieval task faster with the divider than without the divider. In both the restocking and retrieval tasks, we expected that participants would report greater workload when working without the divider than with the divider. Finally, we expected that participants would prefer using the illustrated divided drawer. Method

Participants. Twenty-four nurses participated from the same tertiary hospital ICU as in Study 1 (work experience at the ICU, M = 4.45 years, median = 3.00). On average, participants had been working for 2.34 years with the divider. Thirteen out of 24 participants had worked without the divider prior to its introduction (M = 2.05 years). Ethical approval was granted by Queensland Health and the University of Queensland. Apparatus. The experimental materials were set up on two trolleys that could be moved for testing into vacant bed areas within the ICU (see Figure 2). Drawers contained the standard 18 medical items currently used in the emergency

bedside drawers (an emergency response card had been added since Study 1) minus any items due to be missing from the drawer for a particular experimental trial. The item labels were regenerated for slightly greater clarity with a better-quality printing process than had been used for Study 1 and were placed in the divided drawer in the same locations as for Study 1. Design. For the restocking and retrieval tasks, the presence or absence of the divider was manipulated within participants. In the restocking task, the number of items missing (zero, one, five, or eight items) was manipulated within subjects. Within each drawer condition, the order of presentation of the four levels of number of items missing was counterbalanced between participants with the use of a Latin square design. To avoid a repetition of condition sequence or of missing item identities, a different row of the Latin square with a different pattern of items missing was used when the participants worked with the divider versus without the dividers. In the retrieval task, the experimenter called out item names, and the participant had to state as quickly as possible whether the item was present or absent before hearing the next item name. Ten item names were called. The drawer always had either 4 or 5 items missing (4M, 5M), and the 10-item list called out by the experimenter always included either 2 or 3 of the items that were missing from the drawer (2ML, 3ML). Across the four trials with each drawer, the four combinations of items missing from the drawer coupled with items missing from the 10-item list were 4M/2ML, 4M/3ML, 5M/2ML, and 5M/3ML. The order of presentation of the aforementioned arrangements of drawer items was counterbalanced across participants, with the same general approach as for the restocking task. Procedure. Participants first performed the restocking task, whereby they had to identify which items were missing from the drawer, if any. Participants were given two practice restocking trials, one with and one without the divider. Then participants completed eight formal restocking trials, four with the divider and four without the divider. For the four restocking trials within each divider condition, either zero,



967

how long they had worked in the local ICU, how long they had used the divider, whether they had ever used an undivided and unillustrated drawer in the ICU and, if so, for how long. In addition, the postexperiment questionnaire asked participants how easy it had been to use each kind of drawer during the experiment, how much they had needed to concentrate when using each kind of drawer, and which drawer they would prefer to use, in general. Results Figure 2. Participant (right) performing the restocking task in Study 2 with the illustrated divider. Experimenter running the trial is at center with stopwatch. Assistant assembling the drawer contents for each trial is at left. Small video camera on cross-beam records the drawer, participant’s hands, and audio.

one, five, or eight items were missing. Half of the participants started the restocking task by using the divider, and the other half started without the divider. For each trial, response speed was measured with a stopwatch and accuracy was noted on a paper response list. Response speed was recorded from the start (i.e., participant opens drawer) to when the participant stated, “Finished.” Video recordings were taken to check timings and drawer composition. After each set of four trials with a specific drawer configuration, participants used the NASA Task Load Index (NASA-TLX) workload scale (unweighted; see Nygren, 1991) to give a rating of their workload across the previous four restocking trials with the relevant drawer condition. Participants then performed the retrieval task. For each trial, 10 items were requested in quick succession; after each item name, participants noted whether the item was present or absent in the drawer, and the experimenter immediately called the next item name. Presentation of the drawer with and without the divider was counterbalanced across participants. Practice trials, test trials, response recordings, and the workload measurement were conducted for the retrieval task as for the restocking task. At the end of the experiment, participants answered a postexperiment questionnaire asking

Restocking task. A two-way repeated-measures ANOVA was conducted on how long it took participants to indicate which items were missing, with factors divider (present or absent) and items missing (zero, one, five, or eight). Results are shown in Figure 3. As expected, participants restocked significantly faster when the divider was present than when it was absent, F(1, 23) = 31.28, p < .001, ηp2 = .58. There was also a main effect of the number of items missing, F(3, 69) = 19.91, p < .001, ηp2 = .47. As hypothesized, participants restocked significantly more slowly when eight items or five items were missing than when zero or one item was missing (Bonferroni corrected post hoc tests, p < .05). Finally, as expected, there was a significant interaction between drawer and items missing. As the number of items missing increased, restocking time increased at a greater rate when the divider was absent than when it was present, F(3, 69) = 3.10, p = .032, ηp2 = .12. Accuracy in the restocking task was measured by calculating the average of the number of stocked items, with 17 being the maximum (the emergency evacuation card was not included in the analysis because it was always present in the drawer). A repeated-measures ANOVA was conducted with factors divider (present or absent) and items missing (0, 1, 5, or 8). Overall, accuracy was high. The ANOVA showed a main effect of items missing, F(3, 69) = 12.23, p < .001, ηp2 = .34, indicating that participants’ accuracy at restocking was lower when 8 or 5 items were missing (M = 15.98 and M = 16.25, respectively) than when 1 or 0 items were missing (M = 16.88 and M = 16.94; Bonferroni corrected post hoc tests, p < .05). No other ANOVA effects were significant (F < 1).


968 40

Restocking me in seconds

35


Without divider With divider

30 25 20 15 10 05 00

0

1 5 Items missing

8

Figure 3. Restocking time in Study 2 as a function of performance with and without the divider and number of missing items. Error bars are standard error of the mean.

For each participant, the average of the six NASA-TLX subscale ratings was calculated after each set of four trials with a specific drawer. As hypothesized, participants rated their workload lower when the divider was present than when it was absent, t(23) = 5.01, p < .001, d = 0.95 (see Table 3). Retrieval task. A dependent t test was conducted on how long it took participants on average to retrieve the called-out items. Contrary to our hypothesis, there was no difference in participants’ retrieval times between when the divider was present (M = 20.91, SD = 2.71) and when it was absent (M = 20.92, SD = 2.81), t < 1. Accuracy of the retrieval task was calculated by averaging the accurately retrieved items across the four trials per condition, with 10 being the maximum. As for the restocking task, accuracy was high and there was no significant difference in accuracy between when the divider was present (M = 9.79, SD = 0.30) and when it was absent (M = 9.76, SD = 0.29), t < 1. Again, for each participant, the average of the six NASA-TLX subscale ratings was calculated after each set of four trials with a specific drawer. As hypothesized, participants rated their workload lower when the divider was present than when it was absent, t(23) = 2.56, p = .018, d = 0.38 (see Table 3).

Postexperiment questionnaire. T tests for dependent samples were used to compare participants’ judgments on a scale from 1 to 7 of how easy each drawer was to use and how much they needed to concentrate when using the drawers (see Table 3). Participants reported that it was easier to use the drawer when the divider was present than when it was absent, t(23) = 10.47, p < .001, d = 2.14, and that using the drawer with the divider required less concentration, t(23) = –7.77, p < .001, d = 1.59. Of the 24 participants, 23 preferred to use the divider and 1 participant liked each drawer equally, p < .001 (binomial test with p = q = .5). Discussion

The findings of Study 2 show that an illustrated divider improves the speed with which users can restock an emergency bedside equipment drawer, that subjective mental workload is always lower with the divided drawer, and that users strongly prefer the divided drawer. These findings support the idea that visual cues help people perform habitual prospective memory tasks, such as the restocking task, which have to be repeatedly executed and that have several subtasks (Grundgeiger et al., 2013). Despite these results, we did not find faster or more accurate performance with the divider in an item retrieval task, and in pilot work, we found a small but significant effect in the opposite direction (Harris et al., 2013). At first, our retrieval results may seem inconsistent with work by Rousek and Hallbeck (2011) and others (e.g., Chitkara et al., 2013) that show improved item retrieval performance with drawer redesigns. However, our task required the retrieval of disparate and highly visually differentiated items from one drawer, whereas the other studies required participants to distinguish and retrieve either visually and functionally similar emergency medication items (Rousek & Hallbeck, 2011) or items from a larger set of items located in multiple drawers (Chitkara et al., 2013). In addition, our tests were conservative and may have prevented a speed or accuracy advantage emerging for the divider in the retrieval task. In the condition with the divider absent, the items were consistently in the same locations as



969

Table 3: Subjective Responses in Study 2 Collected After Each Drawer Condition and at the End of the Experiment Condition Variable

With Divider

Postcondition ratings Restocking workload (NASA-TLX) Retrieval workload (NASA-TLX) Postexperiment ratings Ease of use Concentration required Preference

Without Divider

2.04 (1.25)** 2.51 (1.86)* 6.42 (0.72)** 3.00 (1.18)** 23**

3.52 (1.82) 3.29 (2.24) 3.33 (1.34) 5.38 (1.10) 1 (liked both)

Note. Entries show means with standard deviations in parentheses. NASA-TLX = NASA Task Load Index. NASATLX ratings are on a 1-to-10 scale, with 10 indicating highest workload imaginable. Postexperiment ratings are on a 1-to-7 scale, with 7 indicating greatest ease of use and highest concentration required. **p < .001. *p < .05.

when the divider was present, but the drawer was shaken just a little to simulate repeated opening and closing of the drawer. However, as Study 1 revealed (see Figure 1), the locations of items in the bedside drawers were not consistent before the divider was introduced. In Study 2, retrieval without the divider may have been more difficult if we had put some of the items in unfamiliar locations and changed the locations a little across trials, reflecting the findings of Study 1. Indeed, in unpublished work in our laboratory involving student participants and stationery items, we have found that restocking and retrieving times can sometimes become very long if drawer items are in “nonstandard” locations and change between trials. Further research would clarify the impact of the consistency versus inconsistency of item locations on retrieval times as well as the role of visual differentiation of the items themselves on visual search times. Limitations. One possible limitation of Study 2 is that the nurses participating had worked with the divider for an average of around 2 years. As a result, they may have been able to use their knowledge of the drawer layout, even during retrieval trials without the divider, so reducing the difference between conditions. However, in our earlier finding (Harris et al., 2013), student participants using a divided drawer for the first time restocked stationery

items faster with the divider present and actually retrieved items a little faster when the divider was absent, showing that differences in retrieval times could not be attributed solely to familiarity. Further research may help to determine whether the retrieval task and conditions we used were not sensitive enough to detect a performance difference, whether the present divider really does not help people retrieve items, or whether the ICU bedside drawer we used was too simple compared to the design in previous studies to show a difference (e.g., Chitkara et al., 2013; McLaughlin, 2003; Rousek & Hallbeck, 2011). A second possible limitation of Study 2 is that nurses’ prior experience with the divider may have led them to be more favorably disposed to it, possibly explaining the workload and questionnaire findings. However, in our pilot work with stationery items, as many as 32 out of 36 of the student participants preferred the divider (Harris et al., 2013), despite never having seen the divider before (the difference in preferences beween the pilot study and Study 2 is nonsignificant with an odds ratio of 0.1537, p = .22). It therefore seems unlikely that the nurses’ familiarity with the drawer layout and contents explains the results of Study 2. Further comparisons of performance without the divider, or with the divider involving nurses unfamiliar with it, would provide a final confirmation.


970

August 2014 - Human Factors General Discussion

In the present paper, we have shown that a drawer divider with yellow-colored illustrated labels effectively increases the completeness and standardization of items in an emergency equipment drawer (Study 1). It also reduces the time to restock the drawer and reduces the workload of working with the drawer (Study 2). The present studies are generally consistent with results of previous work on the redesign of emergency equipment storage based on human factors design principles (e.g., Chitkara et al., 2013; McLaughlin, 2003; Rousek & Hallbeck, 2011). Study 1 goes beyond previous studies to show improvements in an actual health care setting and not in a simulation. Study 2 demonstrates strong advantages for the divided drawer for restocking, and strong reductions in subjective workload and related measures with the divided drawer for both tasks, but it also shows that the advantage is not universal. The fundamental insight contributing to the redesign was to conceptualize the restocking problem, in particular, as a habitual prospective memory task (Dismukes, 2008), the performance of which would be improved and eased with a consistent layout of items and with visual cues indicating the layout. End-user input from nurses contributed greatly to the specific arrangement of items for the divider and to the identification of the most-recognizable images for the items. Finally, principles developed for the design of warnings motivated the actual form of the visual cues, such as their pictorial form supporting immediacy of impact and compliance (Wogalter et al., 1997) and their yellow color for legibility (Frascara, 2005; Kalsher & Williams, 2005). It is notable that the principles used in our study and others’ studies (e.g., Chitkara et al., 2013; McLaughlin, 2003; Rousek & Hallbeck, 2011) have parallels in the “5S” principles of lean thinking used to create a “visual factory”: sort, set in order, shine, standardize, and sustain (Hirano, 1995). This parallel appears not to have been remarked in recent human factors work on storage equipment design. The history of good visual design in easing perceptual and cognitive tasks extends back beyond lean thinking; however, human factors can take a role in translating

theoretical principles into industrial practice. For example, knowledge of prospective memory theory and findings, coupled with knowledge of nursing work, can provide further information about the behavioral resilience that equipment must support, such as effective recovery of restocking after interruption (see Grundgeiger et al., 2013). Moreover, human factors research provides insight into why conventional principles sometimes do not work (see Project Ernestine; Gray, John, & Atwood, 1993), as was the case in the retrieval task of Study 2. The drawer divider may contribute to patient safety, but a much larger study with a longitudinal design would be needed to demonstrate such a contribution. In the meantime, the two studies presented here demonstrate the benefits of the divided drawer sufficiently strongly for the design principles and investigative methods to be applied in other health care contexts. In summary, a drawer divider developed with the assistance of human factors principles associated with warning design and task design appears to have reduced the workload associated with a habitual prospective memory task and improved performance. However, there are constraints in exactly where improvement appears that should be investigated in future research. Future divider systems should employ custom-made dividers to maximize compartment space, and they should ensure standardization of all drawers or spaces. Future studies examining the impact of standardized drawers and trolleys on patient safety and patient outcomes are warranted. Acknowledgments Study 1 was performed while Tobias Grundgeiger held an Endeavour IPRS at the University of Queensland. This project is supported by the National Health and Medical Research Council (NHMRC) Centre of Research Excellence in Patient Safety (NHMRC ID 264643). The Centre is funded by the Australian Council for Safety and Quality in Health Care and is an NHMRC Centre of Research Excellence. The Safety and Quality Council is a joint initiative of the Australian, state, and territory governments. The authors thank the intensive care unit staff of the Princess Alexandra Hospital for supporting the research, Stacey Parker for statistical advice, and Enrico Ryll, Chris Riesner, and Nick Sibbald for


Illustrated Divider in Emergency Drawers helping to build the dividers. The authors also thank an anonymous reviewer for pointing out the connection with lean thinking and 5S.

Key Points •• A redesign of an emergency equipment drawer layout based on human factors principles can increase equipment completeness and standardization between patient bays. •• A redesign of the layout based on human factors principles reduces restocking time and reduces subjective workload for nurses. •• Redesigning equipment storage based on human factors principles is relatively easy and costefficient and can be applied to different equipment in different domains.

References Agarwal, S., Swanson, S., Murphy, A., Yaeger, K., Sharek, P., & Halamek, L. P. (2005). Comparing the utility of a standard pediatric resuscitation cart with a pediatric resuscitation cart based on the Broselow tape: A randomized, controlled, crossover trial involving simulated resuscitation scenarios. Pediatrics, 116, e326–e333. Chitkara, R., Rajani, A. K., Lee, H. C., Hansen, S. F. S., & Halamek, L. P. (2013). Comparing the utility of a novel neonatal resuscitation cart with a generic code cart using simulation: A randomised, controlled, crossover trial. BMJ Quality & Safety, 22, 124–129. DeLucia, P. R., Ott, T. E., & Palmieri, P. A. (2009). Performance in nursing. Reviews of Human Factors and Ergonomics, 5, 1–40. Dismukes, R. K. (2008). Prospective memory in aviation and everyday settings. In M. Kliegel, M. A. McDaniel, & G. O. Einstein (Eds.), Prospective memory: Cognitive, neuroscience, developmental, and applied perspectives (pp. 411–431). New York, NY: Lawrence Erlbaum. Dismukes, R. K. (2010). Remembrance of things future: Prospective memory in laboratory, workplace, and everyday settings. Reviews of Human Factors and Ergonomics, 6, 79–122. Donchin, Y. (2002). Resuscitation trolleys: Human factors engineering. Quality & Safety in Health Care, 11, 393. Ellis, J. (1996). Prospective memory or the realization of delayed intentions: A conceptual framework for research. In M. Brandimonte, G. O. Einstein, & M. A. McDaniel (Eds.), Prospective memory: Theory and applications (pp. 1–51). Mahwah, NJ: Lawrence Erlbaum. Frascara, J. (2005). Typography and the visual design of warnings. In M. S. Wogalter (Ed.), Handbook of warnings (pp. 385–406). Mahwah, NJ: Lawrence Erlbaum. Gosbee, J. (2002). Human factors engineering and patient safety. Quality & Safety in Health Care, 11, 352–354. Gray, W. D., John, B. E., & Atwood, M. E. (1993). Project Ernestine: Validating a GOMS analysis for predicting and explaining real-world task performance. Human–Computer Interaction, 8, 237–309. Grundgeiger, T., & Sanderson, P. M. (2009). Interruptions in healthcare: Theoretical views. International Journal of Medical Informatics, 78, 293–307.

971 Grundgeiger, T., Sanderson, P. M., Beltran Orihuela, C., Thompson, A., MacDougall, H. G., Nunnink, L., & Venkatesh, B. (2013). Prospective memory in intensive care nursing: A representative and controlled patient simulator study. Ergonomics, 56, 579–589. doi:10.1080/00140139.2013.765604 Grundgeiger, T., Sanderson, P. M., MacDougall, H. G., & Venkatesh, B. (2010). Interruption management in the intensive care unit: Predicting resumption times and assessing distributed support. Journal of Experimental Psychology: Applied, 16, 317–334. Hales, B. M., & Pronovost, P. J. (2006). The checklist: A tool for error management and performance improvement. Journal of Critical Care, 21, 231–235. Halm, M. A. (2008). Daily goals worksheets and other checklists: Are our critical care units safer? American Journal of Critical Care, 17, 577–580. Harris, B., Ford, N., Sanderson, P. M., Grundgeiger, T., & Venkatesh, B. (2013). Evaluating the redesign of an ICU bedside emergency equipment drawer. In Proceedings of the 57th Annual Meeting of the Human Factors and Ergonomics Society (pp. 678–682). Santa Monica, CA: Human Factors and Ergonomics Society. Hirano, H. (1995). 5 pillars of the visual workplace. Cambridge, MA: Productivity Press. Kalsher, M. J., & Williams, K. J. (2005). Behavioral compliance: Theory, methodology, and results. In M. S. Wogalter (Ed.), Handbook of warnings (pp. 313–331). Mahwah, NJ: Lawrence Erlbaum. McLaughlin, R. C. (2003). Redesigning the crash cart: Usability testing improves one facility’s medication drawers. American Journal of Nursing, 103(4), 64A–64F. Meacham, J. A., & Leiman, B. (1982). Remembering to perform future actions. In U. Neisser (Ed.), Memory observed (pp. 327– 336). San Francisco, CA: Freeman. Merry, A. F., Webster, C. S., Hannam, J., Mitchell, S. J., Henderson, R., Reid, P., . . . Cooper, J. (2011). Multimodal system designed to reduce errors in recording and administration of drugs in anaesthesia: Prospective randomised clinical evaluation. BMJ: British Medical Journal, 343, 343:d5543. Nygren, T. E. (1991). Psychometric properties of subjective workload measurement techniques: Implications for their use in the assessment of perceived mental workload. Human Factors, 33, 17–33. Rogers, W. A., Lamson, N., & Rousseau, G. K. (2000). Warning research: An integrative perspective. Human Factors, 42, 102–139. Rousek, J. B., & Hallbeck, M. S. (2011). Improving medication management through the redesign of the hospital code cart medication drawer. Human Factors, 53, 626–636. Schultz, J., Davies, J. M., Caird, J., Chisholm, S., Ruggles, K., & Puls, R. (2010). Standardizing anesthesia medication drawers using human factors and quality assurance methods. Canadian Journal of Anesthesia/Journal canadien d’anesthésie, 57, 490–499. Slamecka, N. J. (1968). An examination of trace storage in free recall. Journal of Experimental Psychology, 76, 504–513. Smith, A., Kinross, J., Bailey, M., Aggarwal, R., Toresen, D., & Vincent, C. (2008). Re-stocking the resuscitation trolley: how good is compliance with checking procedures? Clinical Risk, 14, 4–7. Wogalter, M. S. (2005). Purposes and scope of warnings. In M. S. Wogalter (Ed.), Handbook of warnings (pp. 3–9). Mahwah, NJ: Lawrence Erlbaum.


972


Wogalter, M. S., Begley, P. B., Scancorelli, L. F., & Brelsford, J. W. (1997). Effectiveness of elevator service signs: Measurement of perceived understandability, willingness to comply and behaviour. Applied Ergonomics, 28, 181–187. Wogalter, M. S., & Laughery, K. R. (1996). Warning! Sign and label effectiveness. Current Directions in Psychological Science, 5, 33–37.

Tobias Grundgeiger completed his PhD in psychology at the University of Queensland in 2011. He is currently working as a postdoctoral researcher and lecturer at Julius-Maximilians-Universität Würzburg, Germany. Bonnie Harris completed her BPsySci(Hons) in psychology with a minor concentration in philosophy at the University of Queensland in 2013. Nicholas Ford is completing a BPsySci(Hons) at the University of Queensland, where he is also completing a diploma in languages, specializing in Japanese.

Michael Abbey received his MPhil from Griffith University, Brisbane, Australia in 2009. He is a clinical nurse consultant at the Princess Alexandra Hospital. Penelope M. Sanderson obtained her PhD in engineering psychology from University of Toronto in 1985. She is a professor of cognitive engineering and human factors at the University of Queensland, with appointments in psychology, information technology and electrical engineering, and medicine. Balasubramanian Venkatesh obtained his MD from the University of Birmingham, United Kingdom, in 1995. He is a professor of intensive care at the University of Queensland with appointments at the Princess Alexandra and Wesley Hospitals, Brisbane, Australia. Date received: April 24, 2013 Date accepted: October 30, 2013


Emergency medical equipment on board German airliners.

Expert and competent non-expert visual cues during simulated diagnosis in intensive care.

Perceptual scaling of visual and inertial cues: effects of field of view, image size, depth cues, and degree of freedom.

Reliability and medical equipment.

The benefits of disposable surgical equipment.

Students tested in emergency mock-up.

Emergency Equipment on Diving Boats.

Inappropriate marketing of medical equipment.

[Out-of-hospital equipment of emergency medical services for hemorrhagic shock management: can do better!].

Relearning auditory spectral cues for locations inside and outside the visual field.

[Disparity of French Emergency medical services equipment: disparity of funding allocation or of management quality?].

Emergency medical triage decisions are swayed by computer-manipulated cues of physical dominance in caller's voice.

"Safety of medical electrical equipment".

Linear vection in the central visual field facilitated by kinetic depth cues.

Semiquantitative Decision Tools for FMD Emergency Vaccination Informed by Field Observations and Simulated Outbreak Data.

Motor function benefits of visual restoration measured in age-related cataract and simulated patients: Case-control and clinical experimental studies.

Identification of visual paternity cues in humans.

Occupational exposure to infection risk and use of personal protective equipment by emergency medical personnel in the Republic of Korea.

Visual time compression: spatial and tmeporal cues.

Length-based endotracheal tube and emergency equipment in pediatrics.

End of life care in emergency settings.

Medical Wire and Equipment Company Microring YT.

Multisensory Convergence of Visual and Vestibular Heading Cues in the Pursuit Area of the Frontal Eye Field.

Impact of Helicopter Emergency Medical Service in Traumatized Patients: Which Patient Benefits Most?