# Lean Management Framework in Healthcare: Insights and Achievements on Hazardous Medical Waste
## 3 Materials and Methods  
This study employed a systematic review methodology to identify, screen, and analyze the recent scientific literature focused on medical and healthcare waste management. The search was conducted using the Web of Science Core Collection database. The search strategy was conducted using the following Boolean query terms: \"medical waste\" OR \"healthcare waste\". The full selection process is detailed in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram (Figure 1). Search filters were applied to include only articles and reviews published in English between 1 January 2020 and 5 April 2025. The full search was performed on 5 April 2025. Inclusion criteria consisted of publications focusing on waste in healthcare systems, while exclusion criteria eliminated articles unrelated to healthcare waste (e.g., electronic, industrial, or animal waste) and non-English texts. Bibliometric visualizations were conducted in VOSviewer version 1.6.20. For keyword co-occurrence analysis, a minimum node occurrence threshold of 10 was set. The clustering algorithm used was the linear-logarithmic modularity optimization, with the normalization method set to association strength. Fractional counting was applied for all co-authorship and keyword network analyses to ensure a proportional representation of multilateral collaborations and term prominence. Co-authorship maps used a minimum of 5 publications per country. Overlay and density visualizations were generated using default color scaling adjusted for interpretability in the 2021-2024 window. These settings ensured structural clarity, reproducibility, and thematic robustness across all bibliometric maps presented in Figures 2-6. Figure 1: PRISMA flow diagram for the selection of articles in bibliometric analysis. Created by authors based on BMJ model [83]. Figure 3: Temporal overlay visualization of keyword co-occurrence in HMW literature (2020–2025). Note: The color scale was adjusted to cover the interval of 2021–2024 to enhance the visual contrast between recent and earlier publications. A broader timespan would have resulted in uniform coloring, reducing interpretability. Figure 2: Co-occurrence map of keywords in HMW literature (\(N=1703\) records). Figure 4: Density visualization map of keyword co-occurrence in HMW literature. Figure 5: International co-authorship network in HMW research. Note: The color scale was adjusted to cover the interval of 2021–2024 to enhance the visual contrast between recent and earlier publications. A broader timespan would have resulted in uniform coloring, reducing interpretability. A total of 29,327 records were initially identified through the database search. No additional records were retrieved from registers, and no duplicates were detected. After an initial screening based on titles and abstracts, 1345 records were excluded due to being assigned to unrelated categories (e.g., Zoology, Philosophy, Astronomy, Archaeology, International Relations, Food Science, Linguistics, and Mathematical Physics). This left 27,982 articles for further eligibility assessment. In the final stage of the screening process, each of the remaining 27,982 article titles was examined individually to assess its relevance. A total of 26,279 records were excluded based on three key criteria. First, most articles (\(n\) = 26,006) were unrelated to the healthcare or medical waste context, instead referring to agricultural, food, industrial, animal, or electronic waste. Second, a subset of 59 articles used the word \"waste\" in unrelated medical contexts (e.g., wasting disease, muscle wasting), thus falling outside the scope of this analysis. Third, 214 articles were published in languages other than English and were excluded to maintain linguistic consistency within the bibliometric review. As a result, a total of 1703 studies met the inclusion criteria and were retained for the final analysis.