Misra Saheli Chatterjee, Mukhopadhyay Kaushik
Pediatrics ESIC PGIMSR & ESIC Medical College, Diamond Harbour Road, Joka, Kolkata, 104, West Bengal, India.
Pharmacology, AIIMS Kalyani, NH-34Connector, Basantapur, Saguna, 741245, West Bengal, India.
Pediatr Res. 2023 Jan;93(2):357-365. doi: 10.1038/s41390-022-02320-4. Epub 2022 Sep 30.
Big data in pediatrics is an ocean of structured and unstructured data. Big data analysis helps to dive into the ocean of data to filter out information that can guide pediatricians in their decision making, precision diagnosis, and targeted therapy. In addition, big data and its analysis have helped in the surveillance, prevention, and performance of the health system. There has been a considerable amount of work in pediatrics that we have tried to highlight in this review and some of it has been already incorporated into the health system. Work in specialties of pediatrics is still forthcoming with the creation of a common data model and amalgamation of the huge "omics" database. The physicians entrusted with the care of children must be aware of the outcome so that they can play a role to ensure that big data algorithms have a clinically relevant effect in improving the health of their patients. They will apply the outcome of big data and its analysis in patient care through clinical algorithms or with the help of embedded clinical support alerts from the electronic medical records. IMPACT: Big data in pediatrics include structured, unstructured data, waveform data, biological, and social data. Big data analytics has unraveled significant information from these databases. This is changing how pediatricians will look at the body of available evidence and translate it into their clinical practice. Data harnessed so far is implemented in certain fields while in others it is in the process of development to become a clinical adjunct to the physician. Common databases are being prepared for future work. Diagnostic and prediction models when incorporated into the health system will guide the pediatrician to a targeted approach to diagnosis and therapy.
儿科学中的大数据是结构化和非结构化数据的海洋。大数据分析有助于深入数据海洋,筛选出可指导儿科医生进行决策、精准诊断和靶向治疗的信息。此外,大数据及其分析有助于卫生系统的监测、预防和绩效提升。我们试图在本综述中突出儿科学领域已开展的大量工作,其中一些已被纳入卫生系统。随着通用数据模型的创建以及庞大“组学”数据库的整合,儿科学各专科的工作仍在不断推进。负责儿童护理的医生必须了解相关成果,以便能够发挥作用,确保大数据算法在改善患者健康方面产生临床相关效果。他们将通过临床算法或借助电子病历中的嵌入式临床支持警报,将大数据及其分析结果应用于患者护理。影响:儿科学中的大数据包括结构化、非结构化数据、波形数据、生物数据和社会数据。大数据分析已从这些数据库中揭示出重要信息。这正在改变儿科医生看待现有证据并将其转化为临床实践的方式。目前已获取的数据在某些领域得到应用,而在其他领域则仍在开发过程中,以成为医生的临床辅助工具。正在为未来的工作准备通用数据库。诊断和预测模型纳入卫生系统后,将指导儿科医生采取靶向诊断和治疗方法。