Background: To deal with complexity in cancer care, computerized clinical decision support systems (CDSSs) are developed to support quality of care and improve decision-making. We performed a systematic review to explore the value of CDSSs using automated clinical guidelines, Artificial Intelligence, datamining or statistical methods (higher level CDSSs) on the quality of care in oncology. Materials and Methods: The search strategy combined synonyms for 'CDSS' and 'cancer.' Pubmed, Embase, The Cochrane Library, Institute of Electrical and Electronics Engineers, Association of Computing Machinery digital library and Web of Science were systematically searched from January 2000 to December 2019. Included studies evaluated the impact of higher level CDSSs on process outcomes, guideline adherence and clinical outcomes. Results: 11,397 studies were selected for screening, after which 61 full-text articles were assessed for eligibility. Finally, nine studies were included in the final analysis with a total population size of 7985 patients. Types of cancer included breast cancer (63.1%), lung cancer (27.8%), prostate cancer (4.1%), colorectal cancer (3.1%) and other cancer types (1.9%). The included studies demonstrated significant improvements of higher level CDSSs on process outcomes and guideline adherence across diverse settings in oncology. No significant differences were reported for clinical outcomes. Conclusion: Higher level CDSSs seem to improve process outcomes and guidelines adherence but not clinical outcomes. It should be noticed that the included studies primarily focused on breast and lung cancer. To further explore the impact of higher level CDSSs on quality of care, high-quality research is required.

Objective: The aim of our systematic review is to identify the effects of multidisciplinary team meetings (MDTM) for lung, breast, colorectal and prostate cancer. Methods: Our systematic review, performed following PRISMA guidelines, included studies examining the impact of MDTMs on treatment decisions, patient and process outcomes. Electronic databases PUBMED, EMBASE, Cochrane Library and Web of Science were searched for articles published between 2000 and 2020. Risk of bias and level of evidence were assessed using the ROBINS-I tool and GRADE scale. Results: 41 of 13,246 articles were selected, evaluating colorectal (21), lung (10), prostate (6) and breast (4) cancer. Results showed that management plans were changed in 1.6–58% of cases after MDTMs. Studies reported a significant impact of MDTMs on surgery type, and a reduction of overall performed surgery after MDTM. Results also suggest that CT and MRI imaging significantly increased after MDTM implementation. Survival rate increased significantly with MDTM discussions according to twelve studies, yet three studies did not show significant differences. Conclusions: Despite heterogeneous data, MDTMs showed a significant impact on management plans, process outcomes and patient outcomes. To further explore the impact of MDTMs on the quality of healthcare, high-quality research is needed.