区域高龄老人慢性病特征数据集

1.数据筛选：通过医卫通AI一体机结合多种专业医疗检测设备，在用户授权下依法合规采集试点区域内用户高龄患者问诊记录的核心字段（用户代码、性别、出生年月、主要疾病诊断、能力评估等）。
2.特征工程：1）年龄计算：基于出生日期计算当前年龄；2）疾病数量统计：统计“主要疾病诊断”字段中用顿号分隔的疾病种类数量；3）疾病分类：建立疾病分类词典，将诊断文本按系统进行分类（如心血管疾病、代谢疾病等）。
3.数据整合：将原始字段与计算出的年龄、疾病数量、疾病分类等衍生字段进行整合。
4.统计分析：计算慢性病患病率、共病比例等统计特征。

1. Data Screening: Core fields including user code, gender, date of birth, primary disease diagnosis, functional assessment, etc., from consultation records of elderly patients in the pilot area were collected legally and compliantly with explicit user authorization, using the Yiweitong AI all-in-one medical device combined with multiple professional medical testing equipment.
2. Feature Engineering: 1) Age Calculation: Calculate the current age based on the patient's date of birth; 2) Disease Quantity Statistics: Count the number of distinct disease types separated by Chinese enumeration commas in the "Primary Disease Diagnosis" field; 3) Disease Classification: Establish a disease classification dictionary to categorize diagnostic texts by body system (e.g., cardiovascular diseases, metabolic diseases, etc.).
3. Data Integration: Integrate the original raw fields with the derived features such as calculated age, disease count and disease classification.
4. Statistical Analysis: Calculate statistical features including chronic disease prevalence rate and comorbidity ratio, etc.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于区域高龄老人的慢性病特征，数据规模为12KB，每月更新，适用于老年慢性病管理、共病模式研究和公共卫生政策制定等场景。它通过多来源采集，利用医卫通AI一体机等设备获取问诊记录，并经过特征工程处理，包括计算年龄、统计疾病数量和分类，以支持慢性病患病率和共病比例等统计分析。数据集旨在为基于实证数据的老年健康服务改进提供支持，具有明确的行业应用价值。