近视防控临床诊疗和医疗资源数据

当前，全球近视患病率高发，已成为重大公共卫生问题。<<近视防治指南(2024年版)>>显示，我国近视患病率达53.6%，高度近视患者占比显著增加，是不可逆性致盲主因之一。现有防控手段难以满足精准防控需求，相关研究缺乏对近视患者人群特征、诊疗模式、医疗资源利用的系统性刻画，标准化近视数据集的建设，正是破解上述困境的核心抓手。
本项目整合近视患者诊疗和医疗资源利用情况的数据，包含：人口学信息、就诊信息、诊断信息、病例信息、生命体征信息、眼科检查信息、药品医嘱信息、非药品医嘱信息。对繁杂无序的诊疗数据开展匿名化、标准化、结构化处理，转化为可直接用于分析的标准化数据集。基于高质量数据集，可针对疾病精准诊断、药械疗效量化评估、行业发展趋势研判等关键方向，开展科学系统的预测分析，为临床研究、公共卫生政策制定及眼视光产品开发等提供支撑。

Currently, the high global prevalence of myopia has become a major public health concern. According to the *Guideline for Myopia Prevention and Control (2024 Edition)*, the prevalence of myopia in China reaches 53.6%, and the proportion of patients with high myopia has increased significantly, making it one of the leading causes of irreversible blindness. Existing prevention and control measures struggle to meet the demands of precise prevention and control, and relevant studies lack systematic characterization of the population characteristics, diagnosis and treatment models, and medical resource utilization of myopia patients. The development of standardized myopia datasets is the core solution to these dilemmas.

This project integrates data on the diagnosis, treatment and medical resource utilization of myopia patients, including: demographic information, visit records, diagnostic information, case records, vital signs data, ophthalmic examination data, medication prescription information, and non-medication prescription information. We conduct anonymization, standardization and structuring on the complex and unstructured clinical data, transforming them into standardized datasets that are directly available for analysis. Based on these high-quality datasets, scientific and systematic predictive analysis can be carried out in key areas such as precise disease diagnosis, quantitative evaluation of drug and device efficacy, and research on industry development trends, providing support for clinical research, public health policy formulation, and ophthalmic optometry product development, among other applications.

搜集汇总

背景与挑战

背景概述

该数据集整合了近视患者的临床诊疗和医疗资源利用数据，涵盖人口学、就诊、诊断、检查、医嘱等多类信息，旨在构建标准化、结构化的数据集以支持近视精准防控。数据经过匿名化处理和标准化转换，并利用自然语言处理与AI大模型技术从文本中提取结构化字段，如合并症状和用药情况。该数据集为临床研究、公共卫生政策制定及眼视光产品开发提供了高质量的数据基础，有助于系统刻画患者特征和诊疗模式。