This study is testing a new mobile application called the OASES App, developed by the University of Milano-Bicocca. The App is designed to help frontline clinicians (nurses, clinical officers, and nursing assistants) provide faster and more accurate emergency care for patients with life-threatening conditions such as severe diarrhea, breathing difficulties, and seizures.

The OASES App guides clinicians step by step through internationally recognized emergency care guidelines, including triage, diagnosis, and treatment recommendations. It is intended to be used offline on a tablet, making it suitable for rural hospitals with limited resources.

This is a pilot study to understand whether the App improves the way clinicians manage simulated emergency cases compared to standard practice. About 16 clinicians at Dr. Ambrosoli Memorial Hospital, Kalongo, Uganda will take part in structured simulation exercises using realistic patient scenarios. Each participant will manage cases with and without the App, so that the two approaches can be compared.

The main goal is to evaluate whether the App helps clinicians follow evidence-based guidelines more consistently. Other goals include measuring accuracy of triage, diagnosis, and treatment decisions, as well as the time needed to complete cases and clinicians' perceptions of usability, trust, and feasibility.

No real patients will be involved in this study. All scenarios are simulations conducted in a safe, controlled environment. The results will help refine the App and inform the design of a larger study in the future.

Emergency conditions such as severe diarrhea, dyspnea, and seizures remain major causes of morbidity and mortality in low- and middle-income countries. Despite the availability of World Health Organization (WHO) and national guidelines, adherence to evidence-based emergency practices is often suboptimal in rural health facilities. Common challenges include limited training, high workload, and lack of decision-support resources.

The Organization for the Advancement and Support of Emergency Systems (OASES) App was developed in 2025 by the University of Milano-Bicocca as part of a quality improvement collaboration with Dr. Ambrosoli Memorial Hospital, Kalongo, Uganda. The App digitizes validated emergency care algorithms derived from WHO frameworks and Ugandan clinical guidelines. It incorporates the Interagency Integrated Triage Tool (IITT) and provides structured pathways for the management of diarrhea, dyspnea, and seizures in both adults and children. Designed for offline use on Android tablets, the App offers step-by-step decision support for frontline clinicians while also collecting structured clinical data.

This pilot trial uses a randomized, stratified crossover simulation design to evaluate the effectiveness, usability, and feasibility of the OASES App before clinical deployment. Approximately 16 outpatient department (OPD) clinicians at Dr. Ambrosoli Memorial Hospital (including nurses, clinical officers, and nursing assistants) will participate. Each clinician will complete a total of 12 standardized emergency case scenarios, divided into two sessions: one using the OASES App and one using standard practice without the App. To minimize learning effects, sessions will be separated by at least a three-day washout period.

The case scenarios are adapted from WHO training materials (such as Basic Emergency Care and Emergency Triage Assessment and Treatment guidelines) and reflect typical emergency presentations seen in the hospital's OPD. Each participant will manage six scenarios per study arm (two diarrhea, two dyspnea, two seizures), designed in matched pairs for comparability. Scenarios are facilitated by trained researchers and scored against gold-standard checklists derived from WHO and Ugandan guidelines.

The primary objective of the study is to assess whether use of the OASES App improves clinicians' adherence to evidence-based management steps during simulated emergencies. Secondary objectives include assessing triage accuracy, diagnostic accuracy, appropriateness of disposition decisions, completeness of history-taking and physical examination (process quality), time required to complete cases, and clinician perceptions of usability, trust, and feasibility.

The trial involves no real patients; all activities are conducted in controlled, simulation-based environments. Risks to participants are minimal and mainly related to potential discomfort in being assessed. Benefits include the opportunity to practice emergency scenarios and become familiar with digital decision-support tools.

Data are collected electronically using Kobo Toolbox, with facilitator checklists, participant responses, and structured usability surveys. Responses are scored independently by two blinded assessors, with discrepancies resolved by consensus or third-party adjudication. Data will be analyzed using mixed-effects models appropriate for a crossover design.

Findings from this pilot trial will provide preliminary evidence on the effectiveness and acceptability of the OASES App among frontline clinicians in a rural African hospital. Results will inform refinement of the App, guide study procedures, and support the design of a larger powered trial. At a broader level, the study aims to contribute to the evidence base for digital health solutions to strengthen emergency and acute care in resource-limited settings.

Inclusion Criteria:

• Nurses, clinical officers, or nursing assistants currently employed in the outpatient department (OPD) of Dr. Ambrosoli Memorial Hospital.
• Age ≥18 years.
• Willing and able to provide written informed consent.
• Available to participate in both simulation sessions.

Exclusion Criteria:

• Individuals unable or unwilling to participate in both scheduled simulation sessions.
• Individuals not currently employed in the OPD of Dr. Ambrosoli Memorial Hospital.

This pilot study collects simulation-based performance data from a small number of clinicians. Because the dataset is small and involves individual-level performance in a professional setting, sharing could pose confidentiality risks despite de-identification. Aggregate results will be provided, but individual-level data will not be shared.

Independent outcome assessors who score participants' responses against gold-standard checklists are blinded to study allocation. They do not know whether the responses come from the OASES App-assisted or standard practice sessions. Participants, facilitators, and investigators are not masked due to the nature of the simulation design.