With the ever-increasing focus on sustainable development, recycling waste and renewable use of waste products has earned immense consideration from academics and policy-makers. The serious pollution, complex types, and strong infectivity of medical waste (MW) have brought serious challenges to management. Although several researchers have addressed the issue of the MW by optimizing MW management networks and systems, there is still a significant gap in systematically evaluating the efficiency of MW recycling systems. Therefore, this paper proposes a two-stage data envelopment analysis (DEA) approach that combines the virtual frontier and the global bounded adjustment measure (BAM-VF-G), considering both undesirable inputs and outputs. In the first stage, the BAM-G model is used to evaluate the efficiency of MW recycling systems, and the BAM-VF-G model is used to further rank super-efficient MW recycling systems. In the second stage, two types of efficiency decomposition models are proposed. The first type of models decomposes unified efficiency into production efficiency (PE) and environment efficiency (EE). Depending upon the systems structure, the second type of models decomposes unified efficiency into the efficiency of the MW collection and transport subsystem (MWCS) and the efficiency of the MW treatment subsystem (MWTS). The novel approach is used to measure the efficiency of the MW recycling systems in China's new first-tier cities (CNFCs), and we find that: (1) Foshan ranks the highest in efficiency, followed by Qingdao and Dongguan, with efficiency values of 0.3593, 0.1765, and 0.1530, respectively. (2) EE has always been lower than PE and is a critical factor influencing the overall efficiency of MW recycling systems in CNFCs. (3) The MWCS lacks resilience, with an efficiency 0.042 lower than that of the MWTC. Following the outbreak of COVID-19, the efficiency of the MWCS has been decreasing year by year, reaching only 0.762 in 2021, which is a decline of 0.111 compared to 2017.