摘要
[目的/意义]提高农民工健康医疗知识的信息素养,均衡健康医疗信息服务资源。[方法/过程]通过分析农民工健康医疗信息需求特征,构建农民工健康医疗大数据智慧服务模型,选取DISCERN评价工具为健康医疗信息价值评价的标准,使用SVM与Logistic结合的方式建立农民工个人患病概率预测模型,并以广州市荔湾区农民工患尘肺病为例,进行实证检验。[结果/结论]基于农民工个人患尘肺病概率预测模型,结合相关指标变化趋势和变化率,农民工的性别、年龄、职业、行业、收入(月)、文化程度、来穗工作时间(年)、食肉量(日)、食蛋量(日)、饮奶量(日)、生活环境、睡觉时长(日)、工作环境、工作时长(日)、劳动强度这15个指标与农民工患尘肺病具有密切关系;可以基于农民工个人患病概率实现个性化精准信息服务。
[Purpose/significance]This paper intends to improve information literacy of migrant workers’health care knowledge and balance health care information service resource.[Method/process]By analyzing characteristics of migrant workers’health care information needs this paper builds a smart service model of migrant workers’health care big data selects the DISCERN evaluation tool as the standard for evaluating health care information value uses the combination of SVM and Logistic to establish a predictive model of individual disease probability for migrant workers and takes migrant workers with pneumoconiosis in Liwan District of Guangzhou City as an example to carry out an empirical test.[Result/conclusion]Based on the predictive model of individual pneumoconiosis probability for migrant workers combined with the change trend and change rate of related indicators the 15 indicators of migrant workers’gender age occupation industry income(month)education level working time(year)meat consumption(day)egg consumption(day)milk consumption(day)living environment sleep time(day)working environment working time(day)and labor intensity are closely related to migrant workers’pneumoconiosis.Personalized precise information service can be realized based on individual disease probability for migrant workers.
作者
刘金辉
Liu Jinhui(Library of Huizhou Health Sciences Polytechnic,Huizhou Guangdong 516025)
出处
《情报探索》
2021年第11期67-73,共7页
Information Research
基金
2020年国家社会科学基金项目课题“重大突发公共卫生事件舆情中的信息不对称与社会情绪治理研究”(项目编号:20CZZ042)成果之一。
关键词
健康医疗
大数据管理
智慧推送
信息服务
农民工
health care
big data management
smart push
information service
migrant worker
