Objective: With data drawn from Beijing's New Rural Cooperative Medical System (NRCMS), the rule characteristics of disease risks are mined in terms of risk factors and risk measurements aiming to discover valuable knowledge within the vast amounts of Beijing's NRCMS data and provide administrators with a more scientific basis for decision making. Methodology: The association rule algorithm is utilized to recover both potentially valuable knowledge and decision-making information from Beijing's NRCMS data. Results: The main objects of healthcare in Beijing from 2012 to 2014 include: circulatory diseases in patients 41 years of age or older, pediatric respiratory disease prevention, reproductive healthcare for women of childbearing age, and the prevention and treatment of diabetes in female patients; in county-level hospitals with a relatively low average level of consumption, injuries still resulted in high expenses; the primary post-NRCMS reimbursement level-3 and level-4 high-risk groups were patients of 41-65 years of age. Conclusion: According to the ranking of rule supports, the highest support rule in Beijing is the circulatory diseases of middle-aged patients, especially patients that are hospitalized in county-level medical institutions; the second highest support comes from the utilization of fertility services for women of childbearing age. Suggestions: It is recommended that the rule support rankings should be combined to actively and implement with emphasis major prevention and healthcare services, lower disease risk factors, control NRCMS reimbursement costs, promote the sustainable development of NRCMS, adopt a classified management of mined rules, and establish a decision-making knowledge base.