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BACKGROUND AND OBJECTIVE: There is increasing emphasis in cancer care globally for care to be reviewed and managed by multidisciplinary teams (ie, in tumor boards). Evidence and recommendations suggest that the complexity of each patient case needs to be considered as care is planned; however, no tool currently exists for cancer teams to do so. We report the development and early validation of such a tool. METHODS: We used a mixed-methods approach involving psychometric evaluation and expert review to develop the Measure of case-Discussion Complexity (MeDiC) between May 2014 and November 2016. The study ran in six phases and included ethnographic interviews, observations, surveys, feasibility and reliability testing, expert consensus, and multiple expert-team reviews. RESULTS: Phase-1: case complexity factors identified through literature review and expert interviews; Phase-2: 51 factors subjected to iterative review and content validation by nine cancer teams across four England Trusts with nine further items identified; Phase 3: 60 items subjected to expert review distilled to the most relevant; Phase 4: item weighing and further content validation through a national UK survey; Phases 5 and 6: excellent interassessor reliability between clinical and nonclinical observers, and adequate validity on 903 video case discussions achieved. A final set of 27 factors, measuring clinical and logistical complexities were integrated into MeDiC. CONCLUSIONS: MeDiC is an evidence-based and expert-driven tool that gauges the complexity of cancer cases. MeDiC may be used as a clinical quality assurance and screening tool for tumor board consideration through case selection and prioritization.

BACKGROUND: Multidisciplinary teams (MDT) formulate expert informed treatment recommendations for people with cancer. We set out to examine how the factors proposed by the functional perspective of group decision making (DM), that is, interaction process, internal factors (factors emanating from within the group such as group size), external circumstances (factors coming from the outside of the team), and case-complexity affect the quality of MDT decision making. METHODS: This was a cross-sectional observational study. Three cancer MDTs were recruited with 44 members overall and 30 of their weekly meetings filmed. Validated observational instruments were used to measure quality of DM, interactions, and complexity of 822 case discussions. RESULTS: The full regression model with the variables proposed by the functional perspective was significant, R2 = 0.52, F(20, 801) = 43.47, P < .001, adjusted R2 = 0.51. Positive predictors of DM quality were asking questions (P = .001), providing answers (P = .001), team size (P = .007), gender balance (P = .003), and clinical complexity (P = .001), while negative socioemotional reactions (P = .007), gender imbalance (P = .003), logistical issues (P = .001), time-workload pressures (P = .002), and time spent in the meeting (P = .001) were negative predictors. Second half of the meetings also saw significant decrease in the DM quality (P = .001), interactions (P = .001), group size (P = .003), and clinical complexity (P = .001), and an increase in negative socioemotional reactions (P = .001) and time-workload pressures (P = .001). DISCUSSION: To the best of our knowledge, this is the first study to attempt to assess the factors proposed by the functional perspective in cancer MDTs. One novel finding is the effect of sociocognitive factors on team DM quality, while another is the cognitive-catch 22 effect: while the case discussions are significantly simpler in the second half of the meeting, there is significantly less time left