Standardizing evaluation of patient-specific 3D printed models in surgical planning: development of a cross-disciplinary survey tool for physician and trainee feedback.

BACKGROUND: 3D printed models are becoming increasingly popular in healthcare as visual and tactile tools to enhance understanding of anatomy and pathology in medical trainee education, provide procedural simulation training, and guide surgical procedures. Patient-specific 3D models are currently being used preoperatively for trainee medical education in planning surgical approaches and intraoperatively to guide decision-making in several specialties. Our study group utilized a modified Delphi process to create a standardized assessment for trainees using patient-specific 3D models as a tool in medical education during pre-surgical planning. METHODS: A literature review was conducted to identify survey questions administered to clinicians in published surgical planning studies regarding the use of patient-specific 3D models. A core study team reviewed these questions, removed duplicates, categorized them, mapped them to overarching themes, and, where applicable, modified individual questions into a form generalizable across surgical specialties. The core study panel included a physician, physician-scientist, social scientist, engineer/medical student, and 3D printing lab manager. A modified Delphi process was then used to solicit feedback on the clarity and relevance of the individual questions from an expert panel consisting of 12 physicians from specialties including anesthesiology, emergency medicine, radiology, urology, otolaryngology, and obstetrics/gynecology. When the Radiological Society of North America (RSNA)/American College of Radiology (ACR) 3D Printing Registry Data Dictionary was released, additional survey questions were reviewed. A final cross-disciplinary survey of the utility of 3D printed models in surgical planning medical education was developed. RESULTS: The literature review identified 100 questions previously published in surveys assessing patient-specific 3D models for surgical planning. Following the review, generalization, and mapping of survey questions from these studies, a list of 24 questions was generated for review by the expert study team. Five additional questions were identified in the RSNA/ACR 3D Printing Registry Data Dictionary and included for review. A final questionnaire consisting of 20 questions was developed. CONCLUSIONS: As 3D printed models become more common in medical education, the need for standardized assessment is increasingly essential. The standardized questionnaire developed in this study reflects the interests of a variety of stakeholders in patient-specific 3D models across disciplines.