The aim of this study was to describe the frequency of team-simulations and number of recurrent participants in the 30 facilities during SBBC implementation and investigate association to maternal death.
Study design and participants
This study is part of the SBBC stepped-wedge cluster randomised controlled implementation trial, which ran from March 1, 2021, to December 31, 2023 (22).
The study population included all healthcare workers and parturient women in the 30 healthcare facilities in five regions of Tanzania with a high burden of newborn and maternal deaths (23).
The training component of the SBBC program aims to strengthen competencies in day-of-birth emergency care through frequent individual skill-training and in-situ facilitator led team-simulation training sessions.
Study interventions
The SBBC program encompasses four main components: simulation training interventions, continuous QI efforts, innovative clinical tools, and systems for sustainability and scalability.
Training of facilitators and healthcare workers
Through the SimBegin® program, facilitators were trained to conduct simulation sessions for the team with reflection-based and structured debriefings, to identify learning needs and plan proper training interventions, and to train new facilitators. The SimBegin® program is designed to be highly scalable to increase accessibility and efficiency of simulation training. The goal is to establish a sustainable system for simulation training by training selected individuals to a level where they can train new facilitators. The SimBegin® program has a three steps design: Level 1 (becoming a facilitator), Level 2 (becoming a mentor) and Level 3 (becoming SimBegin® course faculty) training, with practicing of facilitator skills between each level (23, 24). The implementation of SimBegin® in SBBC followed an implementation strategy and a training cascade model, aiming to stimulate frequent interprofessional simulation sessions at the facilities.
The flexibility of the SimBegin® program enabled us to conduct the initial training of the national facilitators online. Travelling restrictions due to the ongoing COVID 19 pandemic, prohibited simulation experts from Norway to travel abroad.
Initially, 15 members from the Tanzanian Midwifery Association (TAMA), Pediatric Associations of Tanzania (PAT), and Association of Obstetricians and Gynaecology (AGOTA) were selected to become national facilitators (completed SimBegin® Level 2 and 3), responsible for cascading the SBBC trainings and to mentor local facility champions at the SBBC facilities (Fig. 1). The training of national facilitators and facility champions also included Helping Babies Breathe (HBB) and Helping Mothers Survive Bleeding after Birth (HMS BAB) training and the use of SBBC clinical tools (25–27). Four pre-written scenarios were provided, two HBB newborn resuscitation scenarios and two HMS BAB scenarios. In addition, scenarios addressing active management of third stage of labour, eclampsia and antepartum haemorrhage were designed during the study period.
Continuous quality improvement and the Circle of Learning
The local facility champions facilitated continuous QI loops utilising simulation-based training following strategies illustrated in the Circle of Learning model (Fig. 2) (28). The circle of learning strategies aim to “bridge cognitive and skill-based learning with real-life clinical experience” (23). The model leans towards theories related to experiential learning, competency- based education and training efficiency (29, 30). Kolb is about experiential learning, and his circle is also appropriate to explain what we do in simulations (experience – reflection). Competency-based education is a movement away from exams (knowledge tests) – trainees are able to do things (master) – a combination of knowledge, skills and attitude.
QI areas were identified through weekly review of the SBBC facilities’ own clinical data. A list of 52 quality indicators were provided every week and discussed in facility champion or national facilitator led debriefing sessions using a deliberate practice approach (31). Through these discussions, clinical gaps were identified and categorized into sections: knowledge, individual skills, or team skills. Appropriate training interventions were planned, executed, and translated into clinical care.
SBBC innovative tools
SBBC introduced several innovative tools designed to improve quality of care and to support the training interventions. The innovations were co-created by clinicians in Tanzania, researchers and engineers from Norway, and produced by Laerdal Global Health, Stavanger, Norway.
Clinical tools:
Moyo is a fetal heart rate monitor designed for intermittent or continuous monitoring. Moyo aims to detect fetal distress, to support timely decision-making, and reduce midwives’ workload (32–34). NeoBeat is a newborn heart rate monitor designed to detect heart rate, guiding resuscitation attempts, and to support timely decision-making (35). The Upright bag is a vertical bag-mask newborn ventilation device designed to improve mask seal and ventilation quality (36).
Training tools:
The NeoNatalie Live simulator is a newborn resuscitation simulator that provides feedback on the quality of ventilation, airway management, and time to first ventilation. The simulator records and uploads all training activities to a database (18). MamaNatalie is a wearable simulator designed to practice the third stage of labour and complications like retained placenta and PPH (21). Both simulators were used for individual skill-training and team simulations. No clinical tools were introduced for the maternal population, only the novel training component and the data-driven QI.
Sustainability and scalability
A close collaboration with local, regional, and national health authorities was established before the start of the program. The SBBC tools were distributed to all included facilities, and all training content aligned with national obstetric and newborn care guidelines. Each SBBC facility established a dedicated ”training corner” in the labour ward. A mentorship program, aiming to develop and support the national facilitators continuously, were established. The facility champions and the maternity ward staff at the facilities received supervision visits from the national facilitators every third month where they received mentoring on clinical topics, clinical data, training, simulation, and the facilitator role.
Data collection and management
This study utilises observational data from March 01, 2021 through December 31, 2023, from the 30 SBBC sites. The overall data collection and management is described in the SBBC study protocol and the primary paper (22, 23). Every healthcare facility had two data collectors collecting routine provider registered clinical data on daily basis by using a case report file installed on mobile phones or tablets. Pre-implementation data collection started March 1st, 2021 at all sites. Start of SBBC implementation in the different regions is indicated in Table 1.
The facility champions documented training activities in a facility-based training database on a regular basis. These data provided information about the simulation sessions. The database also documented how simulation training activities and continuous QI processes were implemented in the SBBC facilities.
Statistical analysis
Numerical data were presented as numbers, means with standard deviations and medians, categorical data as numbers and proportions. The main analysis objective was to study the association between the number of trainings one month and maternal deaths the following month. A Poisson regression mixed model approach was used to analyse this relationship over time, taking into account dependency within regions and facilities. A logarithm transformation of the number of trainings was used for appropriate model fit. Furthermore, an ordinary Poisson regression model with period (1, 2 and 3) as categorical predictor variable was used to model the change in total number of trainings in the three periods following introduction of SimBegin® level 1, 2 and 3, respectively. SPSS version 29.0.1.0 (171) and R version 4.3.3 were used for statistical analysis. A p-value ≤ 0.05 was considered significant.