Wait times and overcrowding are challenging emergency departments (EDs) around the world. Several countries with advanced healthcare systems cannot keep pace with patient demand, and Canada ranks among the longest wait times compared to peer-industrialized countries. In fact, the Canadian Institute for Health Information (CIHI) identified an 11% increase in ED wait times from 2015-2016 to 2016-2017. This translates to long wait times that deter patients from pursuing necessary care and increases their likelihood of leaving without being seen by an ED physician. In Newfoundland and Labrador (NL), this issue has precipitated strikingly serious situations regarding long wait times that have made the province a case-in-point for ED issues. To counter this, the investigators propose an innovative quality-improvement intervention called SurgeCon that includes a protocol-driven software platform and several other initiatives to reduce wait times and improve the sustainability of health systems without significant workforce changes. The investigators piloted SurgeCon at the ED in Carbonear, Newfoundland and Labrador (NL) and found there was a 32% reduction in ED wait time.

Emergency Department (ED) wait times and overcrowding is a national problem of considerable magnitude with few favorable solutions. Canadian EDs are failing to meet national targets and have some of the longest wait times compared to peer industrialized countries. For patients, long wait times mean pain or discomfort for hours before being seen. To address these challenges, the investigators propose "SurgeCon", a quality improvement platform to reduce ED wait times and improve patient satisfaction. This study will investigate the effects of SurgeCon on health system key performance outcomes and patient-reported experience and satisfaction. The study uses a comparative effectiveness-implementation hybrid design. This type of hybrid design has been recommended to help achieve rapid translational gains that can hasten the movement of interventions from research to practice to public health impact. In our hybrid design, the investigators will use a pragmatic stepped wedge cluster randomized trial (SW-CRT) design that enrols four 24/7 on-site ED physician support (category A) hospitals into a 31-month trial. At the beginning of the trial, participating sites will operate under a 'usual care' model as a control condition. Each site will transition from providing 'usual care' to the new 'care model' at predetermined periods during the study. At the end of the trial, each of the sites will have eventually transitioned to the SurgeCon enabled care model. Each cluster in this trial will be randomly assigned to an arm of the trial as is the case with most stepped wedge trials.

The platform includes an eHealth component, a training program for ED staff, and a series of quality improvement initiatives. SurgeCon optimizes patient flow and creates a more patient-centric environment; it monitors ED capacity in real-time and helps address overcrowding by prescribing a series of actions customized to maximize patient flow in response to the level of demand in the ED. SurgeCon was recently piloted in a rural hospital and was associated with dramatic improvements in ED efficiency. Our time series analysis showed a significant decrease in the number of patients who left the ED without being seen by a physician (LWBS) (12.1% to 4.6%, p<0.004), time to physician initial assessment (PIA) (104.3 minutes to 42.2 minutes, p<0.001), and length of stay in the ED (LOS) (199.4 minutes to 134.4 minutes p<0.002).

The investigators plan to implement and evaluate SurgeCon in other hospitals in Newfoundland and Labrador (NL) to determine whether these results can be reproduced in urban and other rural EDs. SurgeCon will be considered a completely successful intervention if it requires minimal resources from the ED/health system for its continued operation, improves patient satisfaction and outcomes, and creates better value ED services by reducing the cost of providing the services. The payer organization that will be a rewarding success is the Eastern Health regional health authority (EH) in NL. As the largest health authority in NL, EH is a key organization for the delivery of care and setting provincial standards. It is responsible for managing both rural and urban hospitals and reflects the diversity of institutions across the rest of Canada.

SurgeCon's evaluation and implementation strategy will include a four-stage iterative process: 1. Exploration (month 1-10); 2. Adoption (months 11-12, 17-18, 23-24 and 29-30); 3. Active Implementation (months 13-36); 4. Sustainment (months 19-48). To measure success, the investigators will use an innovative comparative effectiveness implementation hybrid design. The investigators will test the effects of SurgeCon on ED key performance indicators (LOS, PIA, and LWBS) and patient-reported experiences (PREMs), while also capturing data related to its implementation across participating EDs. Our innovative clinical trial (iCT) design will test the effectiveness of SurgeCon using a pragmatic stepped wedge cluster randomized controlled trial accompanied by a cost-effectiveness analysis. Our stepped-wedge iCT design will assign each hospital to a step through a random ordering process. In addition to ED key performance indicators (KPI) and PREMs, the investigators will also measure implementation outcomes related to SurgeCon's scalability, adaptability, sustainability and overall costs. Implementation outcomes will be evaluated by patients, providers/staff and health system managers using a mixed methods process. The hybrid evaluation/implementation design represents an integrated knowledge translation approach that will ensure research findings are eventually integrated into policy and practice. Moreover, a multidisciplinary research team including patient partners, decision-makers, frontline clinicians, and researchers will lead this research.

Inclusion Criteria:

• All individuals who visit any of the four selected emergency departments during the study period will be included.

Exclusion Criteria:

• none

De-identified data will be made available only for the people involved in data analysis. Reports generated by the analysis will be will only include aggregate level information and will be made available to other members of the research team and will be used for publications.