BACKGROUND
Waiting has become an unfortunate reality for parents seeking care for their child in the emergency department (ED). Long wait times are known to increase morbidity and mortality. Providing patients with information about their wait time increases satisfaction and sense of control. There are very few patient-facing AI tools currently in use in EDs, especially tools that are designed with patients and caregivers.
OBJECTIVE
Our aim was to utilize insights from parents and healthcare providers to inform the design of an AI tool that provides personalized wait time and health information to parents during their child’s ED visit.
METHODS
The study followed a human-centered design methodology. The study was conducted in a large tertiary care, urban academic children’s hospital. Data were collected by demographic surveys, semi-structured interviews, card sorting, structured observations and prototype testing from parents and triage nurses. Quantitative data from demographic surveys and card sorting were analyzed using descriptive statistics, including means, medians and interquartile ranges. Qualitative data from semi-structured interviews and observations were analyzed using a content analysis and creating an empathy map. The analysis informed the design of the tool. The tool was implemented in the ED and improved through iterative rounds of testing and improvement.
RESULTS
Between May 30, 2023-August 30, 2023, 64 semi-structured interviews were conducted with parents in the waiting room and 5 interviews were conducted with triage nurses. Parents were primarily mothers (59%), college/university graduates (58%) and had a preferred language of English (80%). 100% of parents had a smart phone and 97% used apps on their smart phone. Children were a median of 7 months (IQR 4-12 months) and had a median of 4 lifetime visits to the ED (IQR 1->5). The qualitative analysis revealed three key themes. Themes informed the development of the wait time AI tool to meet the needs and preferences of parents, aiming to (1) reduce anxiety and uncertainty by providing information, (2) provide a better understanding of the ED process, and (3) communicate a sense of progress. The tool was designed to be an informative and reassuring companion to parents, offering real-time updates, educational content, and a clear visual representation of their ED journey.
CONCLUSIONS
This study employed a human-centred design approach to explore parents' experience waiting in the pediatric ED to develop an AI tool to improve the waiting experience. By prioritizing parents' experiences and insights, we have created a solution that addresses the logistical challenges of communicating wait times and contributes to a more compassionate and efficient healthcare environment. The implementation of this tool has given patients and families the control and certainty they were lacking by providing information about their wait time. The missing gap in developing and implementing technological innovations in the clinical space is a design approach to ensure solutions are based on clinical need, user-centeredness, and testing with patients and healthcare providers to ensure acceptability and usability.