Medical waste management in private clinics in Surabaya and factors affecting it

Susi A. Wilujeng*, Enri Damanhuri, Mochammad Chaerul

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Health care services generate solid wastes that impose environmental risk if not properly managed, especially the one categorized as hazardous. The compliance of those facilities to the regulation regarding waste management-from the source by waste reduction, segregation, storage, transportation, treatment, and burial- is important to be investigated to identified whether it has been conducted properly. This study was conducted in 17 representative clinics by sampling their solid waste for five consecutive days, observing whether the operation of their solid waste management is conforming the related regulations, and performing logistic regression analysis to develop the correlation between independent variables (sanitary officer that specifically responsible for managing waste; routine budget allocated for waste management; standard operational procedure (SOP) for waste management; and waste management training for staffs) and dependent variables (color-coded waste containment; symbol assignment on waste container; and waste storage location). The results show that the medical waste generation rate was 0.070 kg/patient/day. Composition of the waste from clinics comprised of 21% sharps, 42% infectious, and 37% general waste. The process of solid waste segregation, collection, and storage has not complied with the standard regulated by the government. Logistic regression analysis shows that for implementation of color-coded container the affecting factors are budget and SOP; for the availability of waste storage is staff training; while for symbol assignment there seem to be no significant factors affecting it.

Original languageEnglish
Pages (from-to)34-39
Number of pages6
JournalInternational Journal of GEOMATE
Issue number55
Publication statusPublished - Mar 2019


  • Binary logistics regression
  • Health care clinics
  • Medical waste
  • Solid waste management
  • Surabaya City


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