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Identifying Conflicting Priorities in Hand Sanitizers Among Different Clinical End-Users
Event Type
Oral Presentations
TimeWednesday, April 1411:40am - 12:00pm EDT
LocationEducation and Simulation
DescriptionBackground
Hand sanitizer stations have become increasingly important due to the ongoing pandemic. While most designs have worked well for general use, the sudden increase in the need to use sanitizer has changed the way people interact with these stations. Hand sanitizer stations that were in current use were scheduled for replacement due to unavailability of current hand sanitizer refills by the supplier. With the new changes in context of use and larger need for sanitizer accessibility to more parts of the hospital, a usability assessment of commercially available hand sanitizer station was requested. Four end-user groups were identified (Nursing, Infection Control, Environmental Services, and Human Factors) to individually assess the usability of five separate possible replacement hand sanitizing stations. This assessment provided initial insight into the usage, acceptance, compliance, and concerns of the new proposed hand sanitizer stations.

Method
This work was conducted in two phases: 1) rapid expert assessment and 2) frontline user assessment.
Human Factors Rapid Assessments
Initial reports were generated by the Human Factors team highlighting the initial impressions of the hand sanitizer stations. The hand sanitizer stations were assessed using ergonomic/anthropometric design principles. Insights were arranged into a Systems Engineering Initiative for Patient Safety (SEIPS) framework to categorize recommendations.
Decision Matrix Development
A decision matrix is a decision-making tool that is used to choose between two or more choices of the product\system being considered. This is done by identifying criteria\characteristics of importance and weighing them in order of importance. Thereafter, the products being considered were ordered in terms of how well they performed against others in each criterion. A decision matrix should be used when all options must be narrowed down to one choice and the final decision takes several characteristics or criteria into consideration.
To help evaluate the hand sanitizer station, a list of 9 criteria was generated using insight from the rapid assessments and operational insights from non-clinical project managers. A forced decision matrix was created to rank the relative importance of the criteria 1 (most important) to 9 (least important). Then, the best sanitizer station for each criterion was chosen by consensus from each stakeholder i.e., the end users, the project managers and the Human Factors team. Finally, the sum of each stations’ weighted score provided an overall score for each sanitizer station.

Two types of survey forms were constructed feedback from the end-user groups, the responses were then transcribed by a Human Factors researcher into a decision matrix. The first survey form had staff pick a winner (or two) for each of the 9 criteria (Intuitiveness, Visibility, Ease of Use, Feel, Odor, Refill, Packaging of Refill Cartridge, Durability and Safety of User). The second survey had staff rank the criteria from 1 (most important) to 9 (least important).

Frontline User Assessment
Participants
Three main groups identified as major end-users of the hand sanitizer stations were Nursing (n=14), Infection Control (IC, n=7), and Environmental Services (EVS, n=11). Even though it was expected that all groups would use the hand sanitizer station, it was expected that each end-user group would differ when prioritizing the criteria defined. By adding the criteria rankings for each group, we got the appropriate weights to measure by in the decision matrix. This report incorporates the group priorities separately and in aggregate. In addition to the clinical participants, staff from Human Factors and project management (n=3) also weighed in for a total subject pool of n=35.
End-User Feedback
The five hand sanitizer stations were affixed to a board and any identifying labels were covered (Image 3) toto limit bias participants may experience during the study. Participants were encouraged to replace each stations’ sanitizer cartridge and use each station in any order. The two surveys were then filled out and any additional comments or recommendations they had were added to the bottom of the surveys. Each participant took to 5-10 minutes to interact with each station and fill out the survey.

Data Analysis
The surveys were transcribed and organized by group. The decision matrix was made for each group using the sums, averages, and modes of each criteria. When the averages of two criteria were the same the mode acted as a filter to properly sort each criterion from 1 through 9. These rankings created the weights for the decision matrix. The average number of times a station was selected was used instead of a winner-take-all approach to show a broader spectrum of results within each group.
Each group was assessed individually to show the differences between end-user groups. An aggregate score of the three groups and Human Factors is then provided at the end.
Results
The four end-user groups had selected conflicting priority levels of hand sanitizer criteria. A closer look at the decision matrix scores across all groups shows that out of all five sanitizer stations (A, B, C, D, and E) sanitizer stations A was rated the best for infection control (score = 9.7), registered nurses (score = 7), and the human factors team (score = 9.8). The EVS team rated E highest (score = 11.8) followed by A.

An average rating score between all four groups (Nurses, Infection Control, EVS and Human Factors) showed that A (score = 7.6) and E (score = 6.8) had the highest rated sanitizer stations. With A having a slightly better score than E (Figure 1).

The quantitative results from participants showed that A (score = 7.6) and E (score = 6.8) were the highest rated hand sanitizer stations overall, with A scoring highest for infection control, registered nurses and the human factors team, and E scoring highest for EVS.
The qualitative results show that E had a relatively high number of positive comments, D was the most divisive and B was the most disliked with the highest number of negative comments. The A also did relatively well with no red flags and two positive comments.
Authors
Human Factors Consultant
Human Factors Usability Lead