Strengthening Laboratory Management in Reducing Hepatitis B Morbidity and Mortality
Keywords:
Hepatitis B, Preanalytic, analytical and post analyticalAbstract
Hepatitis B virus (HBV) infection is one of the threats in the medical world and requires guaranteed and valid laboratory analysis procedures, one of which is through the quality control (QC) mechanism. As part of laboratory management, QC has an impact on the validity of laboratory analysis results, especially related to HBV infection. The purpose of this study was to determine the level of knowledge of medical analysts before and after laboratory management training. The research method used comparative paired test analysis to obtain the significance and binary logistic regression to determine the most influential questions on the test. The results showed a significant increase in medical analyst knowledge after being given laboratory management material. Supported by a p value = 1.000 from the Hosmer and Lemeshow test and an overall prediction of 95.5% (positive: 92.0% and negative 97.6%), this training was very good in terms of goodness-of-fit and accurate. Material related to immunochromatography (ICT) method is an influential factor based on the analysis of test results. Medical analyst training, especially related to laboratory management in the context of HBV management, has a significant impact and can be continued and developed.
Downloads
References
Agresti, A. (2015). Foundations of linear and generalized linear models. Hoboken, NJ: Wiley. doi:https://doi.org/10.1002/9781118730034
Bursac, Z., Gauss, C., Williams, D., & Hosmer, D. (2017). Purposeful selection of variables in logistic regression. Source Journal of Biostatistics, 2(4), 1-8. doi:10.1515/jb.2008.2.4.173
Castenada, D., Gonzales, A., Alomari, M., Tandon, K., & Zervos, X. (2021). From Hepatitis A to E: A Critical Review of Viral Hepatitis. BMJ, 26(16), 1691-1715. doi:https://doi.org/10.3748/wjg.v27.i16.1691
Coffin, C., Fung, S., Alvarez, F., Cooper, C., Doucettee, K., Fournier, C., & Kelly, E. (2018). Management of Hepatitis B Virus Infection: 2018 Guidelines from the Canadian Association for the Study of Liver Disease and Association of Medical Microbiology and Infectious Disease Canada. Canadian LIver Journal, 1(4). doi:https://doi.org/10.3138/canlivj.2018-0008
Dugad, V., Deshmuk, S., Bhosale, A., Chaudhari, P., Bhar, P., Bindu, R., & Awake, P. (2022). Pre-Analytical And Post-Analytical Errors In The Clinical Laboratory: A Systematic Review. Journal of Pharmaceutical Negative Results, 13(9).
Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th ed.). CA: SAGE Publications.
Ghasemi, A., & Zhadiasl, S. (2012). Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. Int. J. Endocrinol Metab., 10(2), 486-489. doi:https://doi.org/10.5812/ijem.3505
Hendrawati, T., Tiana, R., Mulyani, S., & Minnatika, S. (2023). POLA PENYEBARAN PENYAKIT MENULAR BERDASARKAN KABUPATEN/KOTA DI JAWA TIMUR MENGGUNAKAN ANALISIS KORESPONDENSI. Jurnal Lebesgue, 4. doi:https://doi.org/10.46306/lb.v4i2.355
Hui, R., & Fung, J. (2023). World Hepatitis Day 2023: Are we close to the target? Indian J Med Res, 158(1), 1-4. doi:https://doi.org/10.4103/ijmr.ijmr_1250_23
Kahar, H. (2005). PENINGKATAN MUTU PEMERIKSAAN DI LABORATORIUM KLINIK RUMAH SAKIT. Indonesian Journal of Clinical Pathology and Medical Laboratory, 38-40.
Kemenkes. (2018). Laporan Riskesdas 2018. Badan Penelitian dan Pengembangan Kesehatan RI.
Kemenkes. (2020). Rencana Aksi Nasional Pengendalian Hepatitis 2020-2024. Jakarta: Direktorat Jenderal Pencegahan dan Pengendalian Penyakit.
Kemenkes. (2024). Angka Hepatitis B dan C di Indonesia Turun. Retrieved from Kementerian Kesehatan Republik Indonesia: https://kemkes.go.id/id/angka-hepatitis-b-dan-c-di-indonesia-turun
Lantz, B. (2015). Machine Learning with R: Expert techniques for predictive modeling. Birmingham: Packt Publishing. doi:https://doi.org/10.1002/mlr.v10.03
Menard, S. (2016). Applied Logistic Regression Analysis. CA: SAGE Publications. doi:https://doi.org/10.4135/9781483348964
Ngurah, G., & Putra, G. (2019). PENGARUH PELATIHAN RESUSITASI JANTUNG PARU TERHADAP KESIAPAN SEKAA TERUNA TERUNI DALAM MEMBERIKAN PERTOLONGAN PADA KASUS KEGAWATDARURATAN HENTI JANTUNG. Jurnal Keperawaran Politeknik Kesehatan Kemenkes Denpasar, 12(1), 12-22.
Nirmalasari, V., & Winarti, W. (2020). PENGARUH PELATIHAN (BHD) TERHADAP PENGETAHUAN DAN KETERAMPILAN MAHASISWA KESEHATAN MASYARAKAT. Jurnal Keperawatan Widya Gantari Indonesia, 4(2), 115-123. doi:https://doi.org/10.52020/jkwgi.v4i2.1909
Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). New York: Routledge. doi:https://doi.org/10.4324/9781003117452
Peng, J., Lee, K., & Ingersoll, G. (2020). An introduction to logistic regression analysis and reporting. Journal of Educational Research, 96(1), 3-14. doi:10.1080/00220670309598740
Plebani, M. (2015). Diagnostic Errors and Laboratory Medicine – Causes and Strategies. EJIFCC, 26(1), 7-14.
Razali, N., & Wah, Y. (2014). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 5(1), 21-33.
Stoltzfuz, J. (2018). Logistic regression: A brief primer. Academic Emergency Medicine, 18(10), 1099-1104. doi:10.1111/j.1553-2712.2011.01185.x
Tang, L., Covert, E., Wilson, E., & S., K. (2018). Chronic hepatitis B infection: A review. JAMA, 319(17), 1802-1813. doi:10.1001/jama.2018.3795.
WHO. (2021). Hepatitis B. Retrieved from World Health Organization: https://www.who.int/news-room/fact-sheets/detail/hepatitis-b
Wiraguna, I. (2024). Diagnosis hepatitis B melalui pemeriksaan laboratorium: sebuah tinjauan pustaka. Intisari Sains Medis, 15(3), 1164-1167. doi:https://doi.org/10.15562/ism.v15i3.2177
