Determining Contemporary Barriers to Effective Multidisciplinary Team Meetings in Neurological Surgery: A Review of the Literature

-OBJECTIVE: The integration of multidisciplinary team meetings (MDTMs) for neurosurgical care has been accepted worldwide. Our objective was to review the literature for the limiting factors to MDTMs that may introduce bias to patient care.-METHODS: The Preferred Reporting Items for Systematic Reviews and Meta -Analysis was used to perform a literature review of MDTMs for neuro-oncology, pituitary oncology, cerebrovascular surgery, and spine surgery and spine oncology. Limiting factors to productive MDTMs and factors that introduce bias were identified, as well as determining whether MDTMs led to improved patient outcomes.-RESULTS: We identified 1264 manuscripts from a PubMed and Ovid Medline search, of which 27 of 500 neuro-oncology, 4 of 279 pituitary, and 11 of 260 spine surgery articles met our inclusion criteria. Of 224 cerebrovascular manuscripts, none met the criteria. Factors for productive MDTMs included quaternary/ter-tiary referral centers, nonhierarchical environment, regularly scheduled meet-ings, concise inclusion of nonmedical factors at the same level of importance as patient clinical information, inclusion of nonclinical participants, and use of clinical guidelines and institutional protocols to provide recommendations. Our review did not identify literature that described the use of artificial intelligence to reduce bias and guide clinical care.-CONCLUSIONS: The continued implementation of MDTMs in neurosurgery should be recommended but cautioned by limiting bias.

Automated summary

This study reviewed the literature on multidisciplinary team meetings (MDTMs) in neurosurgical care and identified limiting factors that may introduce bias to patient care. Productive MDTMs were found to involve quaternary/tertiary referral centers, a nonhierarchical environment, regularly scheduled meetings, inclusion of nonmedical factors, and use of clinical guidelines and institutional protocols. However, the use of artificial intelligence to reduce bias was not described in the literature.