Feasibility and Efficacy of Ambulance-Based m-Health for Pediatric Emergencies (FEAMER) Trial

Background:

Almost half of all 6.2 million deaths in children worldwide are caused by acute illnesses such as pneumonia, diarrhea, and injuries, and occur disproportionately in low- and middle-income countries (LMICs). These acute illnesses are mostly treatable if diagnosed and managed in a timely fashion. According to estimates, about half of these children can be saved through better emergency care.

Emergency medical care at the scene and during transportation is, therefore, critical to improving health outcomes. The "Chain of Survival" for cardiac arrest, the "Golden hour" of trauma, and the "FAST" program for stroke rely heavily on high-quality Emergency Medical Systems (EMS). For many emergency conditions, triage and care decisions during transportation play a critical role in the eventual outcome. EMS staff well-trained in pediatric acute/emergency care are scarce, even in high-income countries, and essentially non-existent in LMICs.

There is a critical need - globally, but particularly in LMICs - to address this expertise gap during the most critical time period while a child is transported to a fixed emergency care facility. Such solutions can contribute to potentially saving thousands of children every year.

Formal EMS systems consist of a universal access number (such as 911) that connects the community to ambulances equipped with the necessary supplies, protocols, and, most importantly, trained healthcare providers through specialized call centers. In low-resource settings, the contribution of effective transportation to health outcomes becomes far more significant. Studies show that the lack of EMS contributed to two-thirds of all trauma deaths, 52% of maternal and perinatal deaths, and 20% of newborn deaths in LMICs. Mobile health technology available today has the potential to bridge the expertise gap in prehospital settings rapidly. While there is a sound theoretical basis for such intervention, there is no evidence on the use of ambulance-based teleconsultation (ABT) for children.

Pakistan, the setting of this study, ranks third in the number of deaths among children. On average, every twelfth child who dies worldwide is a Pakistani child. Unpublished data from Karachi, Pakistan, shows a very high acuity level amongst children transported by ambulances. The only modern ambulance service and our partner in this project, Sindh Integrated Emergency \& Health Services (SIEHS), transported 36,501 children between Jan 1, 2018, and Dec 31, 2019. Of these, 12,200 (33%) were triaged as serious or life-threatening emergencies using the globally accepted standard called the Medical Priority Dispatch System.

The current process of care of the critically ill child: Currently, when a family calls the SIEHS Universal Access Number (1021), the call taker/dispatcher team in the Command-and-Control Center (CCC) asks a set of standard questions to determine the patient's location and estimate the potential severity of their condition. The dispatcher then locates the nearest ambulance and passes on the location information and severity code to the ambulance crew. Upon arrival at the scene, EMTs provide emergency care in accordance with established clinical protocols until they reach the destination hospital. The ambulance staff "signs out" patients to the hospital staff, sharing their history and any treatment provided.

Through this study, the investigators aim to test the efficacy of ABT by measuring a change in the outcome measure of PEWS for acutely ill children from the scene of injury/illness to the pediatric emergency department (PED) through a cluster-randomized trial.

Study Procedures:

We will randomly assign 60 ambulances to control and ABT intervention groups (30 each) using a stratified random sampling design. We will assign 30 ambulances, five from each of the six administrative zones of SIEHS, to receive the ABT setup. We will compare changes in PEWS as noted by EMTs at the scene of illness/injury and the PEWS noted by triage nurses in the emergency department between the ABT and control groups.

Sample Size:

For this study, a total of 600 children will be enrolled. All EMTs at the SIEHS (~272 currently) and all telemedicine physicians at CLF(24 currently) will be included in delivering the intervention. For pediatric patients, we based our sample size calculation on the ability to detect a clinically significant difference as captured by a medium to large effect size (0.6-0.8). We estimate that a total sample size of 600 patients will be required for the study (300 in each arm) to detect a medium to significant difference with a standard deviation of 2.0-3.0, a power of 80%, and a significance level of 0.05 (two-sided).

Recruitment:

Patients transported by the intervention ambulances will be enrolled in the intervention arm, while those transported by the control ambulances will be in the control arm. The distribution of patients to these ambulances is random based on the location of the patient and the ambulance at the time of the emergency call. Upon arrival, a trained EMT will approach the parents/guardians, make an initial assessment for eligibility, explain the study intervention, and recruit them to the interventional or control group.

Parents will be consented to by the EMTs. EMTs who will obtain consent will receive training on effective communication and the appropriate approach to obtaining consent from parents for research studies. Based on our preliminary qualitative study findings, we will obtain written consent followed by an opt-out strategy.

The right to withdraw from the study will be respected. Parents can withdraw from the study by contacting the research through a telephone contact number they will receive during the consent process. Additionally, the research team will contact all participants after 72 hours and offer them another opportunity to withdraw from the study. If participants do not withdraw during the call by the study team or by the data lock date, their data will be de-identified and included in the analysis.

Equipment Installation:

The SIEHS, CLF, and AKU (Aga Khan University) teams (in coordination with our human-factor engineering consultant, PD) are responsible for the selection and installation of equipment. The study investigators have equipped ambulances in the intervention arm for real-time, bi-directional, audio-video communication, allowing virtual interactions between EMTs, patients, caretakers, and TMPs; 1- An IP phone with a 4G router supports the communication and connection with the TMPs, 2- To ensure hand-free interaction with the patients, all EMTs wear a headset to communicate with the TMPs, 3- The 360 rotation camera has been installed to allow live video transmission to TMP. The video stream has been integrated into the pre-existing telemedicine platform at CLF through their proprietary software. 4- A tablet with a Qualtrics form has been installed in the ambulance for recording consent and PEWS data. 5- A 4G internet device with a router is present in all ambulances to allow constant signals.

Investigators have utilized existing data privacy standards at CLF to ensure password-protected login, role-based access control, secure Hypertext Transfer Protocol (HTTP) encryption, and data transfer through a virtual private network (VPN). All installed equipment undergoes a quality check and is certified in accordance with local standards before use. If device troubleshooting is required, technical assistance is provided in person or remotely, as needed. Equipment evaluation is collected in the SIEHS equipment checklist, and the following variables are assessed: phone, camera, and tablet.

Data Collection:

We will use the Modified Brighton PEWS as the outcome indicator to test the effectiveness of ABT on patient outcomes. The standard PEWS table has been added to the current clinical form of SIEHS and triage form at CLF EDs. EMTs will obtain consent, calculate the PEWS score, communicate the initial PEWS scores to the SIEHS command and control center, and enter them in the Qualtrics form provided by the WCM. At the time of drop off, the second set of PEWS will be entered on Qualtrics by the EMT, and the child will be handed over to the hospital. Every morning, the SMRS data coordinator will email an Excel spreadsheet of all cases transferred by SMRS to CLF hospitals. Simultaneously, CLF will calculate the triage PEWS and share it with the study coordinator at WCM. The difference in PEWS score (primary outcome), as measured by EMTs from initial evaluation, drop-off evaluation, and ED triage, will be calculated and compared between patients receiving regular care and those receiving ABT consultation.