Application and Analysis of Big Data Mining in Health Management of Chronic Diseases Based on the Internet of Things

Objective: To analyze the application effects of big data mining in the health management of chronic diseases under the premise of the Internet of Things (IoT). Methods: A total of 188 high-risk individuals with chronic diseases in the jurisdiction from January 2022 to January 2024 were selected and evenly divided using a random number table. The observation group underwent big data mining management under the premise of IoT, while the reference group received conventional health management. The management effects of the two groups were compared. Results: The management indicators of the observation group were superior to those of the reference group. After management, the self-management ability scores of the observation group were higher than those of the reference group, the psychological status scores were lower than those of the reference group, and the management satisfaction was higher than that of the reference group (P < 0.05). Conclusion: Implementing big data mining management under the premise of IoT for high-risk individuals with chronic diseases can improve their file establishment rate, as well as the rates of early warning and screening for chronic diseases. It can also enhance the self-management ability of high-risk individuals, correct their adverse psychological conditions, and achieve high management satisfaction.

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