Relationships Between Communication, Time Pressure, Workload, Task Complexity, Logistical Issues and Group Composition in Transdisciplinary Teams: A Prospective Observational Study Across 822 Cancer Cases

Introduction. Functional perspective of team decision-making highlights the importance of understanding the relationship between team interaction/communication during a given task, the internal factors that emanate from within a group (e.g. team composition), and the external circumstances (e.g. workload and time pressures). As an underexplored area, we explored these relationships in the context of multidisciplinary team (MDT) meetings (aka tumor boards). Materials and methods. Three cancer MDTs with 44 team members were recruited from 3 teaching hospitals in the United Kingdom. Thirty of their weekly meetings encompassing 822 case reviews were filmed. Validated instruments were used to assess each case: Bales’ Interaction Process Analysis that captures frequency of task-oriented and socio-emotional interactions/communication; and Measure of case-Discussion Complexity that captures clinical and logistic complexities. We also measured team size, disciplinary diversity, gender, time-workload pressure, and time-on-task. Partial correlation analysis controlling for team/tumor type and case complexity was used for analysis. Results. Clinical complexity positively correlated with task-oriented communication, e.g. gives opinion (r=0.51, p 0.05), however, case reviews with more males present were associated with more tension (r=0.09, p\u003c0.01) and less disagreements (r=-0.11, p\u003c0.01), while when more females present there were more disagreements (r=0.10, p\u003c0.01) and less tension (r=-0.11, p\u003c0.01). Discussion. To the best of our knowledge, this is the first study to assess the relationship between MDT interaction/communication and the external/internal factors. Smaller size, gender balanced teams with core disciplines present, and streamlining workload to reduce time-workload pressure, time-on-task effects, and logistical issues appear more conducive to building and maintain optimal MDTs. Our methodology could be applied to other MDT-driven areas of healthcare.