Effectiveness of Outreach Clinical Mentoring and Supportive Supervision on Biomedical Waste Management in Nasarawa State, North Central Nigeria: An Intervention Study


Authors : Ogwuche John Igoche; Okeke Chiemelu Ndubisi; Tijani Olije; Shekwonugaza Gwamna; Alpha Gimba Janjaro; Ruth Amarachi Ogbonna; Andrew Yakubu; Angela Onyoyibo Ogwuche

Volume/Issue : Volume 9 - 2024, Issue 6 - June

Google Scholar : https://tinyurl.com/5n998c8n

Scribd : https://tinyurl.com/72cru4sj

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUN1401

PlumX Metrics

Semantic Scholar

ResearchGate

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Introduction: Health care activities are essential because they restore health and save lives. At the same time however, they generate large quantity of wastes and by-products that need to be handled safely and disposed of properly. Proper health care waste handling is a worrisome issue around the world, especially in developing countries. This study is meant to determine the effect of clinical mentoring and supportive supervision on the knowledge of, attitude to and practice of biomedical waste management.  Method: A quasi-experimental study design with both qualitative and quantitative components was used. A multistage sampling technique was used to select 436 study participants who met the inclusion criteria. The data tools were pre-tested interviewer-administered questionnaires and supervisory check lists for the quantitative component on the one hand, and a focus group discussion guide for the qualitative component on the other hand. The interventions were in the form of both physical and virtual mentoring and routine supportive supervision. The participants in the control arm of the study did not receive mentoring or supportive supervision. The study lasted for 24 weeks, within which there were weekly, scheduled mentoring/supportive supervisory visits to only the facilities in the study arm.  Data Analysis: Quantitative data was collated, checked for completeness and analyzed using IBM Statistical Package for Social Sciences (version 23). Quantitative variables were described using frequencies, percentages, means and standard deviations. Chi-square test, Fisher’s exact test and Paired t test were used to test associations. At 95% confidence interval, p-value less than 0.05 was considered statistically significant. Qualitative data was analyzed using Nvivo statistiscal software, version 11.  Result: The mean age group of the study participants was 33.30(±8.97). More females (50.80%) than males (49.20%) participated in the study. Majority of the participants had tertiary education (88.45%). The predominant occupation was community health work (30.75%). In the study group, 66.4% of the respondents had poor knowledge score pre-intervention. This decreased significantly to 10.0% post-intervention (p<0.05). In the control arm of the study, there was no significant difference in the findings at the start and after the study. The proportion of respondents who had positive attitude score in the study arm, increased significantly from 40.3% before intervention to 77.8% after intervention (p<0.05). In a similar vein, the proportion with appropriate practice in the study arm also increased from 32.7% before intervention to 88.3% after intervention with a statistically significant difference. In the control arm, there was no significant difference in the findings at the beginning of the study compared to the findings at the end of the study. In the study arm, majority of the respondents who demonstrated poor knowledge of, attitude to and practice of health care waste management at the baseline focus group discussion sessions, showed significant improvement at the post-intervention sessions. In the control arm, there was no significant difference in the focus group discussion findings. Conclusion: The findings above are suggestive of the fact that the interventions were effective. There is, therefore, the need for the establishment of incentive schemes like clinical mentoring and regular supportive supervision of health care workers on health care waste management in order to safeguard human, animal and environmental health.

Keywords : Attitude, Biomedical Waste Management, Knowledge, Mentoring, Practice, Supportive Supervision.

References :

  1. Chima GN, Ezekwe IC, Digha NO. An assessment of medical waste management in health institutions in Yenagoa, South-South, Nigeria. World Review of Science, Technology and Sustainable Development. 2011; 8(2-4):224-33.
  2. United Nations General Assembly. Transforming our world: the 2030 agenda for sustainable development. United Nations; 2015. (Accessed at http://www.un.org/ga/ search/view_doc.asp.symbol=A/RES/70/1&Lang=E on 15 May 2016).
  3. Deshmukh PV, Rathod RH. Biomedical Waste Management : A review. International
  4. 18. Erekpitan O, Ola-Adisa YP, Elijah M, Yohanna CS. Knowledge, attitude/beliefs and practice of medical waste management: an appraisal of Jos North LGA, Plateau State, Nigeria. International journal of research in humanities and social studies. 2019; 2(12): 43-56.
  5. . Philips E.k, Simwale  OJ, Chung MJ, Parker G, Perry J. Risk Of Blood-borne Pathogen Exposure Among Zambian Healthcare Workers: Journal Of Infection And Public Health. 2012; 5:242-249.
  6. Gautam VR, Sharma M. Biomedical waste management: incineration versus environmental safety. Indian Journ of Med and Microbiol. 2010; 28(3): 19119-2.
  7. WHO. Workplace Occupational Safety and Health. Official Newsletter.2017; 12(1): 1-2.
  8. Babanyara YY, Ibrahim DB, Garba T, Bogoro AG, Abubakar MY. Poor Medical Waste Management practices and its risks to human health and the environment: a literature review. Int J Environ. Health Sci Eng. 2013;(7):1-8.
  9. David LK, Joann GE, Dorothea MG, Sean CL. Sample Size Determination. Jekel’s Epidemiology, Biostatistics, Preventive Medicine and Public Health. Elsevier Saunders Publishers. 4th edition, 2014: 153-161.
  10. Patra P. Sample Size in Clinical Research: The Number We Need. International Journal of Medical Science.  Public Health. 2012; 1: 5 – 9.
  11. Olaifa A, Govender R, Ross A. Knowledge, attitude and practice of health care workers about health care waste management at a district hospital in Kwa Zulu-Natal. South African Family Practice, 2018; 60(5): 137 – 145.
  12. Kumar R, Khan EA, Ahmed J, Khan Z. Health care waste management in Pakistan: current situation and training options. Jayub Med Coll Abbottabad. 2010; 22(4):101-105.
  13. Deress T, Jemal M, Girma M, Adane K. Knowledge, attitude and practice of waste handlers about medical waste management in Debre Markos town health care facilities, northwest Ethiopia. BMC Res Notes, 2019;12:146-151.
  14. Azuike EC, Echendu A, Achunam N. Healthcare Waste Management: What do the health workers in a Nigerian tertiary hospital know and practice. Science Journal of Public Health.2015; 3(1) 114 – 118.
  15. Stanley HO, Orakwuemma CS, Onumajuru BO. Assessment of solid waste disposal in Yenagoa. Asian Journal of Advanced Research and Reports, 2018;1(4): 1-14.
  16. Pensiri A, Husna R, Mongkolchai A. Assessment of knowledge, attitude and practice in respect of medical waste management among healthcare workers in clinics, Journal of Environmental and Public Health. 2020; 2(3): 12-33.
  17. Stanley HO, Orakwuemma CS, Onumajuru BO. Assessment of solid waste disposal in Yenagoa. Asian Journal of Advanced Research and Reports, 2018;1(4): 1-14.
  18. Deress T, Jemal M, Girma M, Adane K. Knowledge, attitude and practice of waste handlers about medical waste management in Debre Markos town health care facilities, northwest Ethiopia. BMC Res Notes, 2019;12:146-151.
  19. Philips E.k, Simwale  OJ, Chung MJ, Parker G, Perry J. Risk Of Blood-borne Pathogen Exposure Among Zambian Healthcare Workers: Journal Of Infection And Public Health. 2012; 5:242-249.
  20. WHO. Workplace Occupational Safety and Health. Official Newsletter.2017; 12(1): 1-2.
  21. National Bureau of Statistics, National Population Commission, Federal Ministry of Health. National Nutrition and Health Survey 2018: Report on the Nutrition and Health Situation of Nigeria 2018: 111-153.
  22. WHO. International Statistical Classification of Diseases and Related Health Problems (ICD-10) in Occupational Health. 2018. ( Accessed at: http://healthsystems 2020 .org  on the 17th of October 2018).
  23. Masum A, Willian TO, Mosharraf HS. Assessment of Occupational and Environmental Safety Associated with Medical Waste Disposal in Developing Countries: A Qualitative Approach. Safety Science. 2011; 49(8):1200-1207.
  24. Awodele O, Adewoye AA, Oparah AC. Assessment of medical waste management in seven hospitals in Lagos, Nigeria. BMC public health. 2016;16(1):269-273.
  25. Mathur V, Dwivedi S, Hassan MA. Knowledge, attitude and practice of biomedical waste management among health care personnel: a cross sectional study. Indian Journal of Com Med. 2011; 36: 143-145.
  26. Ajmal S, Ajmal M. Knowledge and Practices of Biomedical Waste Management among Paramedic Staff of Jinnah Hospital, Lahore. Biologia. 2017; 63: 59–66.
  27. Md Mustafa A, Vikas J, Pradeep C, Manasa RV. Biomedical waste management: Effect of educational intervention among health care workers in Bangalore city hospital. National Journal of Community Medicine. 2016; 7(8):686 – 689.
  28. United Nations Development Programme. Work for Human Development. Briefing Note for Countries on the 2015 Human Development Report. Nigeria. Human Development Report; 2015. (Accessed at: http://hdr.undp. org/sites/all/themes/hdr_theme/country-notes/NGA on 7th June, 2016).
  29. World Bank. Service delivery indicators health survey 2013–2014 harmonized public use data. Ref. NGA_2013_SDI-H_v01_M_v01_A_PUF. Dataset downloaded from http://microdata.worldbank.org/ index.php/ catalog/2559. Accessed 16 Aug 2016.
  30. Benue State Environmental Sanitation Authority Law 2005. Official Gazette, 2005; 30(14): 13-14.
  31. Chartier Y, Emmanuel J, Pieper U, Pruss A. Safe Management of Wastes from Healthcare Activities, World Health Organization (WHO), Geneva, Switzerland. 2nd edition, 2014. ( Accessed at: http://healthsystems2020.org  on the 8th of October 2015).
  32. Chartier Y, Emmanuel J, Pieper U, Pruss A. Safe Management of Wastes from Healthcare Activities, World Health Organization (WHO), Geneva, Switzerland. 2nd edition, 2014. ( Accessed at: http://healthsystems2020.org  on the 8th of October 2015).
  33. Food, Medicine and Healthcare Administration and Control Authority (FMHACA), Healthcare Waste Management Directive, FMHACA, Addis Ababa, Ethiopia, 2005. (accessed at: http: //www.emohg.gov.org on the 12th of September 2010).
  34. Federal Ministry of Health (FMoH), Healthcare Waste Management National Guidelines, Hygiene and Environmental Health Development, FMoH, Addis Ababa, Ethiopia, 2008.(accessed at: http//www.bmcresnote.biomedcentral.com on the 15th of May 2016)
  35. Federal Environmental Protection Authority (FEPA), Technical Guidelines on the Environmentally Sound Management of Biomedical and Healthcare Wastes, FEPA, Addis Ababa, Ethiopia, 2004. (accessed at: http: //www.document1.worldbank.org on the 5th of February 2009).
  36. Mane V, Nimbannavar SM, Yuvaraj BY. Knowledge, attitude and practices on biomedical waste and its management among healthcare workers at a tertiary care hospital in Koppal, Karnataka, India. International Journal of Community Medicine and Public Health. 2016; 3(10): 2953–2957.
  37. Chartier Y, Emmanuel J, Pieper U, Pruss A. Safe Management of Wastes from Healthcare Activities, World Health Organization (WHO), Geneva, Switzerland. 2nd edition, 2014. ( Accessed at: http://healthsystems2020.org  on the 8th of October 2015).
  38. Patwary MA, O’Hare WT, Street G, Elahi KM, Hossain SS, Sarke MH. Country report: quantitative asssessment of medical waste generation in the Capital City of Bangladesh. Waste Manag. 2009; 29(8):2392–7.
  39. Kumar R, Somrongthong R,Ahmed J. Effect of medical waste management trainings on behaviour change among doctors versus nurses and paramedical staff in Pakistan .J Ayub Med Coll Abbotabad. 2016;28(3):493-496.
  40. Saini S, Nagarajan SS, Sarma RK. Knowledge, Attitude and Practice of Biomedical Waste Management amongst staff of a tertiary level hospital in India. Journal of the Academy of Hospital Administration, 2005; 17(2): 1-12.
  41. Mugivhisa LL, Dlamini N, Olowoyo JO. Adherence to safety practices and risks associated with healthcare waste management at an academic hospital, Pretoria, South Africa. Afri Health Sci. 2020; 20(1): 453-68.
  42. Mosafa GM, Sherief WI. Development of a waste management protocol based on assessment of knowledge and practice of healthcare personnel in surgical departments. Waste Management, 2008; 29(2): 159-162.
  43. Massrouje HTN. Medical wastes and health workers in Gaza governorates. Eastern Mediterranean Health Journal, 2001; 7(6): 1017-1024.
  44. Vishal B, Swarn L, Mahesh M, Arvind A: Knowledge Assessment of Hospital Staff Regarding Biomedical Waste Management in a Tertiary Care Hospital. Nat J Community Med 2012; 3(2): 197-200.
  45. Suwarna M, Ramesh G. Study about awareness and practices about health care waste management among hospital staff in a medical college hospital, Bangalore. IJBMS. 2015; 6(1): 64-69.
  46. Lakshmi BS, Kumar P: Awareness about biomedical waste management among health care personnel of some important medical centres in Agra. Int J Eng Res Tech 2012; 1(7) 1-5.

Introduction: Health care activities are essential because they restore health and save lives. At the same time however, they generate large quantity of wastes and by-products that need to be handled safely and disposed of properly. Proper health care waste handling is a worrisome issue around the world, especially in developing countries. This study is meant to determine the effect of clinical mentoring and supportive supervision on the knowledge of, attitude to and practice of biomedical waste management.  Method: A quasi-experimental study design with both qualitative and quantitative components was used. A multistage sampling technique was used to select 436 study participants who met the inclusion criteria. The data tools were pre-tested interviewer-administered questionnaires and supervisory check lists for the quantitative component on the one hand, and a focus group discussion guide for the qualitative component on the other hand. The interventions were in the form of both physical and virtual mentoring and routine supportive supervision. The participants in the control arm of the study did not receive mentoring or supportive supervision. The study lasted for 24 weeks, within which there were weekly, scheduled mentoring/supportive supervisory visits to only the facilities in the study arm.  Data Analysis: Quantitative data was collated, checked for completeness and analyzed using IBM Statistical Package for Social Sciences (version 23). Quantitative variables were described using frequencies, percentages, means and standard deviations. Chi-square test, Fisher’s exact test and Paired t test were used to test associations. At 95% confidence interval, p-value less than 0.05 was considered statistically significant. Qualitative data was analyzed using Nvivo statistiscal software, version 11.  Result: The mean age group of the study participants was 33.30(±8.97). More females (50.80%) than males (49.20%) participated in the study. Majority of the participants had tertiary education (88.45%). The predominant occupation was community health work (30.75%). In the study group, 66.4% of the respondents had poor knowledge score pre-intervention. This decreased significantly to 10.0% post-intervention (p<0.05). In the control arm of the study, there was no significant difference in the findings at the start and after the study. The proportion of respondents who had positive attitude score in the study arm, increased significantly from 40.3% before intervention to 77.8% after intervention (p<0.05). In a similar vein, the proportion with appropriate practice in the study arm also increased from 32.7% before intervention to 88.3% after intervention with a statistically significant difference. In the control arm, there was no significant difference in the findings at the beginning of the study compared to the findings at the end of the study. In the study arm, majority of the respondents who demonstrated poor knowledge of, attitude to and practice of health care waste management at the baseline focus group discussion sessions, showed significant improvement at the post-intervention sessions. In the control arm, there was no significant difference in the focus group discussion findings. Conclusion: The findings above are suggestive of the fact that the interventions were effective. There is, therefore, the need for the establishment of incentive schemes like clinical mentoring and regular supportive supervision of health care workers on health care waste management in order to safeguard human, animal and environmental health.

Keywords : Attitude, Biomedical Waste Management, Knowledge, Mentoring, Practice, Supportive Supervision.

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe