| 基于大数据老年多重慢性病风险预测模型构建探究 |
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| 引用本文： | 罗瑶,邓学学,徐晓茹,方荣华.基于大数据老年多重慢性病风险预测模型构建探究[J].中华全科医学,2021,19(12):1979-1982. |
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| 作者姓名： | 罗瑶 邓学学 徐晓茹 方荣华 |
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| 作者单位： | 1.四川大学华西医院特需医疗中心, 四川 成都 610041 |
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| 基金项目： | 四川省科学技术厅重点研发项目2020YFS0151四川大学护理发展专项基金一般项目HXHL19021 |
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| 摘 要： | 人口老龄化已成为一个重大的世界性社会问题。我国65岁以上老年人口超过2.54亿，老年慢性病患病率及共病率高，导致其生活质量下降，致残率、死亡率增高和医疗费用支出的明显增长，给家庭和社会带来沉重的负担。目前基于物联网、大数据、人工智能等新技术已在医疗行业应用，传统的慢性病管理受到挑战。发展智慧医疗是医疗卫生改革的战略需要，也是行业革新的必然趋势，正逐渐成为疾病诊断和风险预测的源动力。开发准确有效的早期诊断及筛检技术，建立完善的疾病普查制度和风险评估、预警体系等是慢性病防治的关键点。国外已开发了乳腺癌、肺癌、糖尿病等疾病风险评估模型，但这些模型并不完全适合中国人群开展疾病风险评估及测量，因此有必要构建符合中国人群自身特点的疾病风险评估模型。如何突破传统的慢性病管理模式，构建精准医疗决策的解决方案成为医疗界共同关注的科学问题。在慢性病管理的实践中，多重慢性病危险因素分级及分层是核心难题。基于大数据云平台，利用机器学习技术进行医疗数据挖掘，形成老年慢性病干预评估的指标评价体系，从而实现创新性的老年慢性病管理模式。该模式将突破老年慢性病管理的难点和瓶颈，促使慢性病的预防/干预关口前移，实现精准管理。
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| 关 键 词： | 慢性病管理 大数据 机器学习 老年人 风险预测 |
| 收稿时间： | 2020-08-24 |
Research on the establishment of a risk prediction model for multiple chronic diseases in the elderly based on big data |
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| Affiliation: | International Medical Center, West China Hospital/West China School of Nursing, Sichuan University, Chengdu, Sichuan 610041, China |
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| Abstract: | The aging of population has become a major worldwide social problem. The elderly population in China had exceeded 254 million. High morbidity and co-morbidity of chronic diseases in the elder have led to reduce quality of their life, the increase of disability rate, mortality rate and obviously increased medical expenditures, which bring heavy burden to family and society. At present, based on the application of new technologies, such as internet of things, big data and artificial intelligence in the medical industry, traditional chronic disease management will be challenged. The development of smart medicine is the strategic need of medical health reform, as well as the inevitable trend of industry innovation, and gradually becomes the source power of disease diagnosis and risk prediction. Developing accurate and effective early diagnosis and screening technology, establishing perfect disease general survey system, risk assessment and early warning system are the key points to prevent and treat chronic diseases. Foreign countries have developed disease risk assessment models for breast cancer, lung cancer, diabetes and other diseases, but these models are not fully suitable for Chinese population to carry out disease risk assessment and measurement, so it is necessary to build disease risk assessment models that are in line with the characteristics of Chinese population. How to go beyond the traditional chronic disease management system and construct the solution of precision medical decision has become a scientific problem concerned by the medical community. In the process of practicing of chronic disease management, the classification and stratification of multiple chronic disease risk factors are the core problems. Based on a large amount of collected medical data, using machine learning technology to build a prediction model for risk assessment of multiple chronic diseases in the elderly and conducts medical data mining, and to form an index evaluation system for intervention evaluation of chronic diseases in the elderly. This model will break through the difficulties and choke point of chronic disease management, and promote the prevention/intervention of chronic diseases to move forward, and achieve accurate management in the elderly. |
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