Effectiveness of Multidisciplinary (MDT) Team Activation Models and Algorithms in Collaborative Care for Pediatric Cancer Patients in Hospital

Multidisciplinary Teams (MDTs) have been widely recognized as a critical approach to improving the quality, safety, and overall outcomes of healthcare services, particularly in oncology (Prades et al., 2015; Soukup et al., 2018). However, the implementation of MDTs across hospital settings shows significant variation, particularly regarding team activation mechanisms (Lamb et al., 213; Taylor et al., 2019). Most existing literature focuses on MDTs as collaborative structures or discussion forums, while MDT activation mechanisms as systematic, protocol-driven decisions are rarely studied (Fleissig et al., 2006). In routine practice, MDT activation is often ad hoc, relying heavily on individual clinician experience without the support of standardized algorithms or decision rules. This situation has the potential to lead to inefficiencies, delayed decision-making, fragmented care pathways, and inconsistent adherence to clinical guidelines (Pillay et al., 2016). Pediatric cancer care, in particular, requires highly coordinated efforts across multiple disciplines (e.g., oncology, surgery, nursing, pharmacy, and psychosocial support) to optimize diagnostic accuracy, reduce treatment delays, and enhance clinical outcomes (Pritchard-Jones et al., 2020). While MDTs or tumor boards are widely recommended in pediatric oncology guidelines, their activation in routine practice remains inconsistent. Many hospitals still rely on ad hoc consultations or rigid, fixed-schedule meetings, which may not align with the dynamic and urgent needs of pediatric patients (Hahlweg et al., 2 and Hong et al., 2014). Trigger-based activation models and clinical algorithms offer a systematic approach to mobilize MDT expertise precisely when clinical, pathway, or digital thresholds are met (Kawamoto et al., 2005; Sutton et al., 2020). This review will generate evidence to inform the design of a context-adaptive MDT activation model for pediatric cancer care, with explicit relevance to both high-resource and resource-constrained hospital settings.