ANALYSIS OF TRIGLYCERIDE TEST CONTROL RESULTS USING THE SIGMA MATRIX METHOD IN THE LABORATORY OF HEART HOSPITAL DIAGRAM
Keywords:
Bias, CV, Quality control, Sigma matrix, QGIAbstract
Quality control in triglyceride tests is carried out to improve the quality of test results and prevent irregularities, so that the accuracy and accuracy of test results can be guaranteed and trusted. Accuracy and accuracy are shown by the coefficient of variation and bias. Sigma matrix is a method to measure the performance of a process by analyzing the root of the problem and showing the number of error factors that occur. This study aims to analyze the results of triglyceride examination control using the sigma matrix method at the Diagram Heart Hospital Laboratory. The research methodology in this study is quantitative descriptive with a cross sectional design using a sample of triglyceride quality control data for the period March to May 2023 with 2 levels of control, namely normal and pathogenic. Sigma matrix analysis involves coefficient of variation (CV), bias and Total Allowable Error (TEa). In this study, the lowest sigma value was in April 2023 level 1 of 4.95 in the good category and the highest sigma value was in March level 1 of 11.73 which was included in the worldclass category, so there was no need to do QGI. The triglyceride control value in this study did not show any deviation at the level of the sigma and QGI matrix, so that the precision and accuracy of the triglyceride test results can be guaranteed in quality.
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References
(CLIA), C. L. I. A. (2022). 2024 CLIA Proposed Acceptance Limits for Proficiency Testing. Westgard QC. https://www.westgard.com/2019-clia-requirements.htm
Aggarwal, K., Patra, S., Acharya, V., Agrawal, M., & Mahapatra, S. K. (2019). Application of six sigma metrics and method decision charts in improvising clinical Chemistry laboratory performance enhancement. International Journal of Advances in Medicine, 6(5), 1524. https://doi.org/10.18203/2349-3933.ijam20194155
Annisa, V. (2021). Good Laboratory Practice (GLP) in The European Union. Indonesian Journal of Pharmaceutical Education, 2(1), 1–9. https://doi.org/10.37311/ijpe.v2i1.11781
Cevlik, T., & Haklar, G. (2023). SIX SIGMA EVALUATION OF 17 BIOCHEMISTRY PARAMETERS USING BIAS CALCULATED FROM INTERNAL QUALITY CONTROL AND EXTERNAL QUALITY ASSURANCE DATA. J Med Biochem, 42, 1–7. https://doi.org/10.5937/jomb0-43052
Hidayati, L., & Maradhona, Y. (2018). Six Sigma for Evaluation of Quality Control in Clinical Laboratory. International Journal of Public Health and Clinical Sciences, 5(4), 2289–7577. http://publichealthmy.org/ejournal/ojs2/index.php/ijphcs/article/view/657
Indonesia, D. T. L. M. (2020). Hematologi Teknologi Laboratorium Medik (E. A. Maharani (ed.)). EGC.
Konoralma, K., Tumbol, M. V. ., & Septyaningsih, N. P. (2018). Gambaran Pemantapan Mutu Internal Pemeriksaan Glukosa Darah di Laboratorium RSU GMIM Pancaran Kasih Manado. Jurnal Analis Kesehatan Poltekkes Kemenkes Manado, 1(2), 337–346. https://ejurnal.poltekkes-manado.ac.id/index.php/ps2017/article/view/497
Kumar, B. V., & Mohan, T. (2020). Sigma Metrics as a Tool for Evaluating the Performance of Internal Quality Control in a Clinical Chemistry Laboratory. Journal of Laboratory Physicians, 10(2). https://doi.org/10.4103/JLP.JLP
Kusmiati, M., Nurpalah, R., & Restaviani, R. (2022). Presisi dan Akurasi Hasil Quality Control Pada Parameter Pemeriksaan Glukosa Darah ddi Laboratorium Klinik Rumah Sakit X Kotta Tasikmalaya. Journal of Indonesian Medical Laboratory and Science, 3(1), 27–37.
Maharani, E. A., Erviani, R., Fajruni’mah, R., & Astuti, D. (2022). Penggunaan Six Sigma Sebagai Evaluasi Kontrol Kualitas pada Hemalotogy Analyzer Sysmex XN-1000. JURNAL RISET KESEHATAN POLTEKKES DEPKES BANDUNG, 14(2), 263–269. https://doi.org/10.34011/juriskesbdg.v14i2.2106
Mao, X., Shao, J., Zhang, B., & Wang, Y. (2018). Evaluating analytical quality in clinical biochemistry laboratory using six sigma. Biochemia Medica, 28(2 Special Issue), 1–4. https://doi.org/10.11613/BM.2018.020904
Pangerapan D, P. O. (2018). Hubungan Antara Mutu Pelayanan Dengan Kepuasan Pasien Di Poliklinik Penyakit Dalam Rumah Sakit Umum GMIM Pancaran Kasih Manado. JKK (Jurnal Kedokteran Klinik), 2(1), 9–18.
Pratama, R. A., Yulianti, D. K., & Setiawan, D. (2021). Aplikasi Metrik Sigma dalam Pemantapan Mutu Internal pada Pemeriksaan Ureum disalah satu Laboratorium Rumah Sakit Kabupaten Pangandaran. Journal of Indonesian Medical Laboratory and Sience, 175–184.
Purnama, T., Fety, Y., & Atri. (2021). Analisis Quality Control Pemeriksaan Hemoglobin pada Alat Hematology Analyzer. Jurnal MediLab Mandala Waluya, 5(1), 7.
Putra, G. P. A. F. S., Prihatiningsih, D., & Subhaktiyasa, P. G. (2020). Analisis Pemantapan Mutu Internal Pemeriksaan Trombosit di Laboratorium Klinik UPTD. Puskesmas Abiansemal I. Jurnal Analis Laboratorium Medik, 5(2), 28–34. http://e-journal.sari-mutiara.ac.id/index.php/ALM/article/view/2152/1471
Ricos, C., Avarez, V., Cava, F., Garcia-Lario, J., Hernandez, A., Jimenez, C., Minchinela, J., Perich, C., & Simon, M. (2014). Desirable Biological Variation Database Specification. Westgard QC. https:/www.westgard.com/biodatabase1.htm
Salsabella, A., & Aryani, T. (2022). Sigma Matrix of Ureum and Creatinine in Some Laboratories : Overview. Medicra (Journal of Medical Laboratory Science Technology), 5(1), 40–46. https://doi.org/10.21070/medicra.v5i1.1628
Teshome, M., Worede, A., & Asmelash, D. (2021). Total clinical chemistry laboratory errors and evaluation of the analytical quality control using sigma metric for routine clinical chemistry tests. Journal of Multidisciplinary Healthcare, 14, 125–136. https://doi.org/10.2147/JMDH.S286679
Tuntun Siregar, M., Sri Wulan, W., Setiawan, D., & Nuryati, A. (2018). Kendali Mutu. Kementrian Kesehatan Republik Indonesia. https://patologiklinik.com/2019/02/10/download-kendali-mutu-bahan-ajar-tlm/
Zhou, B., Wu, Y., He, H., Li, C., Tan, L., & Cao, Y. (2020). Practical application of Six Sigma management in analytical biochemistry processes in clinical settings. Journal of Clinical Laboratory Analysis, 34(1), 1–10. https://doi.org/10.1002/jcla.23126
