《长春市结核病定点医院信息化管理平台》的设计与应用

Xiao-kun LI,Yan-li YUAN,Guang-xu YANG, Yuan-yuan WU

Chinese Journal of Antituberculosis（2020）

Cited 0|Views9

Abstract

将长春市传染病医院院内的医院信息系统(HIS系统)及所辖县/区级定点医院区域网数据衔接搭建起来,形成医疗服务一体化的《长春市结核病定点医院信息化管理平台》,以实现长春地区肺结核患者发现、管理、治疗、转归的信息化和数字化,提高结核病防控模式的运行速度.2018年开始设计并在市级定点医院(长春市传染病医院)建立市级管理平台数据中心,搭建应用服务和数据库服务,与院内HIS系统链接直接获取患者的基本信息,通过PC端完善患者的诊疗信息;同时利用并通过应用程序(APP)+微信客户端的方式,实时接收下级耐药门诊、各县/区结核病防治所11个区域网数据信息.建立VPN通道,对接省级系统平台核准国家实时数据、掌握我市疫情统计学变化.县/区级结核病防治所及耐药门诊等11个部门通过此平台可实时获取本辖区内在市级定点医院诊疗患者的完整资料,完成后续精准治疗管理.2018年12月《长春市结核病定点医院信息化管理平台》建立完成,2019年4月通过HIS系统端口及PC端口与院内局域网对接,自动储存长春市传染病医院住院部及门诊发现的肺结核患者(普通及耐药患者)的基本信息与诊疗资料.2019年9月VPN通道成功与下级耐药门诊对接,耐药门诊医生利用数据库可实时掌握新耐药患者及复诊耐药患者的基本及诊疗信息,缩短纳入管理的时间及提高治疗的精准度.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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