慢性非传染性疾病（以下简称“慢性病”）导致的疾病负担仍在不断增加，深刻地影响着公众健康和社会经济发展。传统的慢性病健康管理，缺乏诊断标准和健康干预的合理介入时机，且需方主动性缺失的瓶颈日益凸显。将健康主动性概念引入并构建主动健康指数（proactive health index，PHI），有望成为优化慢性病健康管理的有效手段。随着全球进入数字化变革的关键时期，我国健康战略已明确维护和保障人民健康应发挥科技创新和信息化的引领支撑作用，数字健康为慢性病健康管理的发展带来战略机遇。该文在数字化慢性病防控的发展背景下，分析我国慢性病健康管理当前存在的主要瓶颈，明确构建慢性病健康管理诊断标准的重要性，提出PHI的概念及构建以解决慢性病健康管理的关键问题，并从政府端、家庭医生端和公众端对PHI的应用场景进行了部署与展望，以期为提升居民健康管理主动性，优化慢性病健康管理的效果提供思路。
关键词：主动健康指数
;
数字健康
;
健康管理
;
慢性病
Abstract
The disease burden caused by chronic non-communicable diseases continues to grow, with profound implications for public health and socio-economic development. The traditional health management of chronic diseases lacks diagnostic criteria and reasonable intervention time, and the bottleneck of the lack of residents' initiative is increasingly prominent. The construction of proactive health index (PHI) is expected to be an effective means to improve the health management of chronic diseases. As the world enters a critical period of digital transformation, China's health strategy has made clear that technological innovation and information technology should play a leading role in maintaining people's health, and digital health brings strategic opportunities for the development of chronic disease health management. In the context of the development of digital chronic disease prevention and control, this study analyzes the main bottlenecks existing in China's chronic disease health management, clarifies the importance of establishing diagnostic criteria for chronic disease health management, proposes the concept of PHI, and introduces the construction of PHI to solve the key problems of chronic disease health management. The application scenarios of PHI are deployed and prospected from the government side, the family physician side and the public side, in order to provide ideas for improving residents' health management initiative and enhancing the effectiveness of chronic disease health management.
Keywords：proactive health index
;
digital health
;
health management
;
chronic disease
GAO Xiang, LI Xiaoguang, ZHOU Liang, WANG Hui. Reflection and exploration of digital chronic disease management based on the proactive health index. Journal of Shanghai Jiao Tong University (Medical Science)[J], 2023, 43(2): 137-142 doi:10.3969/j.issn.1674-8115.2023.02.001
WANG Hui was responsible for the conception and design of the research; GAO Xiang was responsible for thesis writing and revision; LI Xiaoguang and ZHOU Liang were responsible for providing theoretical guidance. All the authors have read and agreed to the submission of the final manuscript.
利益冲突声明
所有作者声明不存在利益冲突。
COMPETING INTERESTS
All authors disclose no relevant conflict of interests.
World Health Organization. Noncommunicable diseases[EB/OL]. (2021-09-16) [2022-01-14]. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.
GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990—2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet, 2020, 396(10258): 1204-1222.
The Information Office of the State Council. The Information Office of the State Council held a press conference on the Report on the Status of Nutrition and Chronic Diseases of Chinese Residents (2020) [EB/OL]. (2020-12-24) [2022-01-15]. http://www.gov.cn/xinwen/2020-12/24/content_5572983.htm.
GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990—2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet, 2020, 396(10258): 1223-1249.
The State Council. The State Council issued the Outline of the Healthy China 2030 Plan[EB/OL]. (2016-10-25) [2022-01-25]. http://www.gov.cn/gongbao/content/2016/content_5133024.htm.
RODRIGUEZ J A, SHACHAR C, BATES D W. Digital inclusion as health care: supporting health care equity with digital-infrastructure initiatives[J]. N Engl J Med, 2022, 386(12): 1101-1103.
YE T T, ZHAO Y W, WANG X S, et al. Research on community chronic disease management model based on the concept of "active health"[J]. Health Economics Research, 2021, 38(8): 45-48.
DE JONG C, VAN BOVEN J F M, DE BOER M R, et al. Improved health status of severe COPD patients after being included in an integrated primary care service: a prospective cohort study[J]. Eur J Gen Pract, 2022, 28(1): 66-74.
ZHANG Q Q, JIN H, SHI S S, et al. Proactive care in China: implementation status and recommendation strategies for various undertaking bodies [J]. Chinese General Practice, 2022, 25(31): 3923-3927, 3932.
FU Q Q, JIN H, LI L, et al. Research status of health literacy assessment tools from the perspective of active health and its enlightenment to China[J]. Chinese General Practice, 2022, 25(31): 3933-3943.
CHEN C, GONG X, WANG X L, et al. Evaluation of the implementation and effect of the healthcare cloud information platform for diabetes self-management: a case study in Shanghai[J]. Int J Health Plann Manage, 2019, 34(3): 986-997.
FU L L, TAN Q S, MAO X F. Practice and thinking of medical science popularization from the perspective of "active health"[J]. Chinese Journal of Health Management, 2022, 16(1): 66-68.
BENTHIEN K S, RASMUSSEN K, NIELSEN C P, et al. Proactive Health Support: a randomised controlled trial of telephone-based self-management support for persons at risk of hospital admission[J]. Age Ageing, 2022, 51(10): afac212.
WALDMAN S A, TERZIC A. Health care evolves from reactive to proactive[J]. Clin Pharmacol Ther, 2019, 105(1): 10-13.
The State Council. Circular of the State Council on Printing and Distributing the National Scientific and Technological Innovation Plan for the 13th Five-Year Plan[EB/OL]. (2016-07-28) [2022-05-07]. http://www.gov.cn/zhengce/content/2016-08/08/content_5098072. htm.
GAO X, TAN S Y, LI X G, et al. Dilemma analysis of health management among community residents and countermeasures based on the proactive health index[J]. Chinese Journal of General Practitioners, 2023, 22(1): 24-28.
ROTHMAN K, KELLER A. The effect of joint exposure to alcohol and tobacco on risk of cancer of the mouth and pharynx[J]. J Chronic Dis, 1972, 25(12): 711-716.
CHEN T Q, GUESTRIN C. XGBoost: a scalable tree boosting system[C]//Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. August 13‒17, 2016, San Francisco, California, USA. New York: Association for Computing Machinery, 2016: 785-794.
ZHU J F. Research on performance evaluation of local governments in China: analysis based on generalized fuzzy comprehensive evaluation model[D]. Shanghai: Shanghai Jiao Tong University, 2011.
BARTHOLOMEW L K, PARCEL G S, KOK G. Intervention mapping: a process for developing theory- and evidence-based health education programs[J]. Health Educ Behav, 1998, 25(5): 545-563.
YUAN L, GAO X, LI X G, et al. Machine learning empowers health risk assessment in general practice application scenarios[J]. Chinese Journal of General Practitioners, 2023, 22(1): 19-23.
The State Council. Notice of the General Office of the State Council on Printing and Distributing the 14th Five-Year National Health Plan[EB/OL]. (2022-04-27) [2022-05-07]. http://www.gov.cn/zhengce/zhengceku/2022-05/20/content_5691424.htm.
