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Background: the aim of this paper is to quantify multidisciplinary team meeting (MDT) impact on the decisional clinical pathway of thoracic cancer patients, assessing the modification rate of the initial out-patient evaluation. Methods: the impact of MDT was classified as follows: confirmation: same conclusions as out-patient hypothesis, modification: change of out-patient hypothesis, implementation: definition of a clear clinical track/conclusion for patients that did not receive any clinical hypothesis, further exams required: the findings that emerged in the MDT meeting require further exams. Results: one thousand consecutive patients evaluated at MDT meetings were enrolled. Clinical settings of patients were: early stage lung cancer (17.4%), locally advanced lung cancer (27.4%), stage IV lung cancer (9.8%), mesothelioma (1%), metastases to the lung from other primary tumors (4%), histologically proven or suspected recurrence from previous lung cancer (15%), solitary pulmonary nodule (19.2%), mediastinal tumors (3.4%), other settings (2.8%). Conclusions: MDT meetings impact patient management in oncologic thoracic surgery by modifying the out-patient clinical hypothesis in 10.6% of cases, the clinical settings with the highest decisional modification rates are &ldquo, solitary pulmonary nodule&rdquo, and &ldquo, proven or suspected recurrence&rdquo, with modification rates of 14.6% and 13.3%, respectively.

Purpose To perform a clinical audit to assess adherence to standard clinical practice for the diagnosis, treatment, and follow-up of patients undergoing radiotherapy for rectal cancer treatment in four European countries. Materials and methods Multi-institutional, retrospective cohort study of 221 patients treated for rectal cancer in 2015 at six European cancer centres. Clinical indicators applicable to general radiotherapy processes were evaluated. All data were obtained from electronic medical records. Results The audits were performed in the year 2017. We found substantial inter-centre variability in adherence to standard clinical practices: 1) presentation of cases at departmental clinical sessions (range, 0–100%) or multidisciplinary tumour board (50–95%); 2) pretreatment MRI (61.5–100%) and thoracoabdominal CT (15.0–100%). Large inter-centre differences were observed in the mean interval between biopsy and first visit to the radiotherapy department (range, 21.6–58.6 days) and between the first visit and start of treatment (15.1–38.8 days). Treatment interruptions ≥ 1 day occurred in 43.9% (2.5–90%) of cases overall. Treatment compensation was performed in 2.1% of cases. Treatment was completed in the prescribed time in 55.7% of cases. Conclusions This multi-institutional clinical audit revealed that most centres adhered to standard clinical practices for most of the radiotherapy processes-related variables assessed. However, the audit revealed marked inter-centre variability for certain quality indicators, particularly inconsistent record keeping. Multiple targets for improvement and/or harmonisation were identified, confirming the value of routine clinical audits to detect potential deviations from standard clinical practice.

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., 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. We used a mixed‐methods approach involving psychometric evaluation and expert review to develop the Measure of case‐Discussion Complexity (MeDiC).

Purpose To review the impact of a weekly multidisciplinary neuroradiology imaging review on the management of patients undergoing radiotherapy. Methods A prospective study of the management of 118 patients (30=head and neck, 40=skull base, central nervous system=48) was conducted over a 12-month period from January 2018 through January 2019. After review of each patient's history and relevant imaging, a radiation oncologist completed a form detailing the changes that were made in diagnosis and management. Imaging source (external and internal examinations), availability of outside reports, report timeliness, the value of reports, changes in interpretation, changes in clinical management, and changes in prognosis were documented. Changes in interpretation and management were designated as major or minor depending on the significance of the change. The managing radiation oncologist indicated whether the imaging review conference substituted for a peer-to-peer consultation with a neuroradiologist. Results Nearly half (47%) of all patients had a change in interpretation. Of those, 32% of patients had a major change in interpretation, while 14% had a minor change in interpretation. The existence of the multidisciplinary imaging review conference prevented a peer-to-peer consultation (interruption) by the radiation oncologists to the neuroradiologists in 90% of the cases presented. Further analysis was performed. Conclusion The involvement of neuroradiologists in a joint radiation oncology imaging review conference resulted in changes in diagnostic imaging interpretation that led to significant changes in management, expected prognosis, and workflow.

Multidisciplinary oncology team meetings (MDMs) or tumor boards, like other MDMs in healthcare, facilitate the incorporation of diverse clinical expertise into treatment planning for patients. Decision-making (DM) in relation to treatment planning in MDMs is carried out repeatedly until all patients put forward for discussion have been reviewed. Despite continuing financial pressure and staff shortages, the workload of cancer MDMs, and therefore meeting duration continue to increase (up to 5 h) with patients often receiving less than 2 min of team input. This begs the question as to whether the current set-up is conducive to achieve optimal DM, which these multi-specialty teams were set out to achieve in the first place. Much of what it is known, however, about the effects of prolonged cognitive activity comes from various subfields of science, leaving a gap in applied knowledge relating to complex healthcare environments. The objective of this review was thus to synthesize theory, evidence and clinical practice in order to bring the current understanding of prolonged, repeated DM into the context of cancer MDMs. We explore how and why time spent on a task affects performance in such settings, and what strategies can be employed by cancer teams to counteract negative effects and improve quality and safety. In the process, we propose a pragmatic framework of repeated DM that encompasses the strength, the process and the cost-benefit models of self-control as applied to real-world contexts of cancer MDMs. We also highlight promising research avenues for closing the research-to-practice gap. Theoretical and empirical evidence reviewed in this paper suggests that over prolonged time spent on a task, repeated DM is cognitively taxing, leading to performance detriments. This deterioration is associated with various cognitive-behavioral pitfalls, including decreased attentional capacity and reduced ability to effectively evaluate choices, as well as less analytical DM and increased reliance on heuristics. As a short to medium term improvement for ensuring safety, consistently high quality of care for all patients, and the clinician wellbeing, future research and interventions in cancer MDMs should address time-on-task effects with a combination of evidence-based cognitive strategies. We propose in this review multiple measures that range from food intake, short breaks, rewards, and mental exercises. As a long term imperative, however, capacity within cancer services needs to be reviewed as well as how best to plan workforce development and service delivery models to achieve population coverage whilst maintaining safety and quality of care. Hence the performance detriments that arise in healthcare workers as a result of the intensity (time spent on a task) and complexity of the workload require not only more research, but also wider regulatory focus and recognition.

Background: We describe a prototype implementation of a platform that could underlie a Precision Oncology Rapid Learning system. Results: We describe the prototype platform, and examine some important issues and details. In the Appendix we provide a complete walk-through of the prototype platform. Conclusions: The design choices made in this implementation rest upon ten constitutive hypotheses, which, taken together, define a particular view of how a rapid learning medical platform might be defined, organized, and implemented. Keywords: Natural language processing, Precision oncology, Controlled natural language, Nanopublication, Treatment reasoning, Rapid learning, Tumor boards, Targeted therapies, Cancer Commons, Deloitte Touche Tohmatsu (Firm)