Buhr H J, Klinger C, Lehmann K S, Strahwald B, Rieger A
Haus der Bundespressekonferenz, Deutsche Gesellschaft für Allgemein- und Viszeralchirurgie e. V., Schiffbauerdamm 40, 10117, Berlin, Deutschland.
Institut für medizinische Informationsverarbeitung, Biometrie und Epidemiologie, LMU München, München, Deutschland.
Chirurg. 2019 Apr;90(4):287-292. doi: 10.1007/s00104-019-0936-y.
Algorithms are increasingly being developed on the basis of large data sets, also in the field of health, whether for predicting treatment outcomes or life-expectancy. In surgery it is also becoming increasingly more important to analyze complications at an early stage and to subsequently reduce them. The aim is to improve the quality of treatment and quality of life and thus to improve patient well-being. The German Society for General and Visceral Surgery (DGAV) has developed 12 StuDoQ registers in which pseudonymized data from a total of 150,000 patients are recorded. Risk models were developed and validated at the Institute for Medical Information Processing, Biometry and Epidemiology (IBE) of the Ludwig Maximilian University in Munich using the collected data from the StuDoQ|colon cancer and StuDoQ|rectal cancer registers. Based on the collected patient data, the risk calculator determines the statistical probability of the individual complication profile of the patient who is to undergo surgery. The aim is to support surgeons and patients in the decision making process for the individual procedure. The surgeon with his individual experience ultimately remains responsible for the patient.
算法越来越多地基于大数据集进行开发,在健康领域也是如此,无论是用于预测治疗结果还是预期寿命。在外科手术中,早期分析并发症并随后减少并发症也变得越来越重要。目的是提高治疗质量和生活质量,从而改善患者的福祉。德国普通和内脏外科学会(DGAV)开发了12个StuDoQ登记册,记录了总共150,000名患者的化名数据。风险模型是在慕尼黑路德维希·马克西米利安大学医学信息处理、生物统计学和流行病学研究所(IBE)使用从StuDoQ|结肠癌和StuDoQ|直肠癌登记册收集的数据开发和验证的。基于收集到的患者数据,风险计算器确定即将接受手术的患者个体并发症情况的统计概率。目的是在个体手术的决策过程中支持外科医生和患者。外科医生最终仍要凭借其个人经验对患者负责。