Background Personalized medicine requires the integration and analysis of vast amounts of patient data to realize individualized care. With Surgomics, we aim to facilitate personalized therapy recommendations in surgery by integration of intraoperative surgical data and their analysis with machine learning methods to leverage the potential of this data in analogy to Radiomics and Genomics. Methods We defined Surgomics as the entirety of surgomic features that are process characteristics of a surgical procedure automatically derived from multimodal intraoperative data to quantify processes in the operating room. In a multidisciplinary team we discussed potential data sources like endoscopic videos, vital sign monitoring, medical devices and instruments and respective surgomic features. Subsequently, an online questionnaire was sent to experts from surgery and (computer) science at multiple centers for rating the features’ clinical relevance and technical feasibility. Results In total, 52 surgomic features were identified and assigned to eight feature categories. Based on the expert survey (n = 66 participants) the feature category with the highest clinical relevance as rated by surgeons was “surgical skill and quality of performance” for morbidity and mortality (9.0 ± 1.3 on a numerical rating scale from 1 to 10) as well as for long-term (oncological) outcome (8.2 ± 1.8). The feature category with the highest feasibility to be automatically extracted as rated by (computer) scientists was “Instrument” (8.5 ± 1.7). Among the surgomic features ranked as most relevant in their respective category were “intraoperative adverse events”, “action performed with instruments”, “vital sign monitoring”, and “difficulty of surgery”. Conclusion Surgomics is a promising concept for the analysis of intraoperative data. Surgomics may be used together with preoperative features from clinical data and Radiomics to predict postoperative morbidity, mortality and long-term outcome, as well as to provide tailored feedback for surgeons. Graphical abstract

Background Digital innovations in medicine are disruptive technologies that can change the way diagnostic procedures and treatments are delivered. Such innovations are typically designed in teams with different disciplinary backgrounds. This paper concentrates on 2 interdisciplinary research teams with 20 members from the medicine and engineering sciences working jointly on digital health solutions. Objective The aim of this paper was to identify factors on the individual, team, and organizational levels that influence the implementation of interdisciplinary research projects elaborating on digital applications for medicine and, based on the results, to draw conclusions for the proactive design of the interdisciplinary research process to make these projects successful. Methods To achieve this aim, 2 interdisciplinary research teams were observed, and a small case study (response rate: 15/20, 75%) was conducted using a web-based questionnaire containing both closed and open self-report questions. The Spearman rank correlation coefficient was calculated to analyze the quantitative data. The answers to the open-ended questions were subjected to qualitative content analysis. Results With regard to the interdisciplinary research projects investigated, the influencing factors of the three levels presented (individual, team, and organization) have proven to be relevant for interdisciplinary research cooperation. Conclusions With regard to recommendations for the future design of interdisciplinary cooperation, management aspects are addressed, that is, the installation of a coordinator, systematic definition of goals, required resources, and necessary efforts on the part of the involved interdisciplinary research partners. As only small groups were investigated, further research in this field is necessary to derive more general recommendations for interdisciplinary research teams. Trial Registration German Clinical Trials Register, DRKS00023909, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00023909 ; German Clinical Trials Register, DRKS00025077, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00025077

BACKGROUND Digital innovations in medicine are disruptive technologies that can change the way diagnostic procedures and treatments are delivered. Such innovations are typically designed in teams with different disciplinary backgrounds. This paper concentrates on 2 interdisciplinary research teams with 20 members from the medicine and engineering sciences working jointly on digital health solutions. OBJECTIVE The aim of this paper was to identify factors on the individual, team, and organizational levels that influence the implementation of interdisciplinary research projects elaborating on digital applications for medicine and, based on the results, to draw conclusions for the proactive design of the interdisciplinary research process to make these projects successful. METHODS To achieve this aim, 2 interdisciplinary research teams were observed, and a small case study (response rate: 15/20, 75%) was conducted using a web-based questionnaire containing both closed and open self-report questions. The Spearman rank correlation coefficient was calculated to analyze the quantitative data. The answers to the open-ended questions were subjected to qualitative content analysis. RESULTS With regard to the interdisciplinary research projects investigated, the influencing factors of the three levels presented (individual, team, and organization) have proven to be relevant for interdisciplinary research cooperation. CONCLUSIONS With regard to recommendations for the future design of interdisciplinary cooperation, management aspects are addressed, that is, the installation of a coordinator, systematic definition of goals, required resources, and necessary efforts on the part of the involved interdisciplinary research partners. As only small groups were investigated, further research in this field is necessary to derive more general recommendations for interdisciplinary research teams. CLINICALTRIAL German Clinical Trials Register, DRKS00023909, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00023909 ; German Clinical Trials Register, DRKS00025077, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00025077