Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India

Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and...
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Autor*in:	Kavita Aggarwal [verfasserIn] Sumit Jhajharia [verfasserIn] Tapaswini Pradhan [verfasserIn] Viyatprajna Acharya [verfasserIn] Saurav Patra [verfasserIn] Sri Krushna Mahapatra [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	haemolysis laboratory errors preanalytical errors quality indicator

Übergeordnetes Werk:	In: Journal of Clinical and Diagnostic Research - JCDR Research and Publications Private Limited, 2009, 15(2021), 10, Seite BC27-BC30
Übergeordnetes Werk:	volume:15 ; year:2021 ; number:10 ; pages:BC27-BC30

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.7860/JCDR/2021/51206.15531

Katalog-ID:	DOAJ019763549

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520			\|a Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase.
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allfields	10.7860/JCDR/2021/51206.15531 doi (DE-627)DOAJ019763549 (DE-599)DOAJ1b43f8c3afcd4cb8bfd650b5e6ecba9f DE-627 ger DE-627 rakwb eng Kavita Aggarwal verfasserin aut Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. haemolysis laboratory errors preanalytical errors quality indicator Medicine R Sumit Jhajharia verfasserin aut Tapaswini Pradhan verfasserin aut Viyatprajna Acharya verfasserin aut Saurav Patra verfasserin aut Sri Krushna Mahapatra verfasserin aut In Journal of Clinical and Diagnostic Research JCDR Research and Publications Private Limited, 2009 15(2021), 10, Seite BC27-BC30 (DE-627)789478048 (DE-600)2775283-5 0973709X nnns volume:15 year:2021 number:10 pages:BC27-BC30 https://doi.org/10.7860/JCDR/2021/51206.15531 kostenfrei https://doaj.org/article/1b43f8c3afcd4cb8bfd650b5e6ecba9f kostenfrei https://jcdr.net/articles/PDF/15531/51206_CE[Ra1]_F[SH]_PF1(JY_RK)_PFA(SC_AnK_KM)_PN(KM).pdf kostenfrei https://doaj.org/toc/2249-782X Journal toc kostenfrei https://doaj.org/toc/0973-709X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 10 BC27-BC30
spelling	10.7860/JCDR/2021/51206.15531 doi (DE-627)DOAJ019763549 (DE-599)DOAJ1b43f8c3afcd4cb8bfd650b5e6ecba9f DE-627 ger DE-627 rakwb eng Kavita Aggarwal verfasserin aut Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. haemolysis laboratory errors preanalytical errors quality indicator Medicine R Sumit Jhajharia verfasserin aut Tapaswini Pradhan verfasserin aut Viyatprajna Acharya verfasserin aut Saurav Patra verfasserin aut Sri Krushna Mahapatra verfasserin aut In Journal of Clinical and Diagnostic Research JCDR Research and Publications Private Limited, 2009 15(2021), 10, Seite BC27-BC30 (DE-627)789478048 (DE-600)2775283-5 0973709X nnns volume:15 year:2021 number:10 pages:BC27-BC30 https://doi.org/10.7860/JCDR/2021/51206.15531 kostenfrei https://doaj.org/article/1b43f8c3afcd4cb8bfd650b5e6ecba9f kostenfrei https://jcdr.net/articles/PDF/15531/51206_CE[Ra1]_F[SH]_PF1(JY_RK)_PFA(SC_AnK_KM)_PN(KM).pdf kostenfrei https://doaj.org/toc/2249-782X Journal toc kostenfrei https://doaj.org/toc/0973-709X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 10 BC27-BC30
allfields_unstemmed	10.7860/JCDR/2021/51206.15531 doi (DE-627)DOAJ019763549 (DE-599)DOAJ1b43f8c3afcd4cb8bfd650b5e6ecba9f DE-627 ger DE-627 rakwb eng Kavita Aggarwal verfasserin aut Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. haemolysis laboratory errors preanalytical errors quality indicator Medicine R Sumit Jhajharia verfasserin aut Tapaswini Pradhan verfasserin aut Viyatprajna Acharya verfasserin aut Saurav Patra verfasserin aut Sri Krushna Mahapatra verfasserin aut In Journal of Clinical and Diagnostic Research JCDR Research and Publications Private Limited, 2009 15(2021), 10, Seite BC27-BC30 (DE-627)789478048 (DE-600)2775283-5 0973709X nnns volume:15 year:2021 number:10 pages:BC27-BC30 https://doi.org/10.7860/JCDR/2021/51206.15531 kostenfrei https://doaj.org/article/1b43f8c3afcd4cb8bfd650b5e6ecba9f kostenfrei https://jcdr.net/articles/PDF/15531/51206_CE[Ra1]_F[SH]_PF1(JY_RK)_PFA(SC_AnK_KM)_PN(KM).pdf kostenfrei https://doaj.org/toc/2249-782X Journal toc kostenfrei https://doaj.org/toc/0973-709X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 10 BC27-BC30
allfieldsGer	10.7860/JCDR/2021/51206.15531 doi (DE-627)DOAJ019763549 (DE-599)DOAJ1b43f8c3afcd4cb8bfd650b5e6ecba9f DE-627 ger DE-627 rakwb eng Kavita Aggarwal verfasserin aut Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. haemolysis laboratory errors preanalytical errors quality indicator Medicine R Sumit Jhajharia verfasserin aut Tapaswini Pradhan verfasserin aut Viyatprajna Acharya verfasserin aut Saurav Patra verfasserin aut Sri Krushna Mahapatra verfasserin aut In Journal of Clinical and Diagnostic Research JCDR Research and Publications Private Limited, 2009 15(2021), 10, Seite BC27-BC30 (DE-627)789478048 (DE-600)2775283-5 0973709X nnns volume:15 year:2021 number:10 pages:BC27-BC30 https://doi.org/10.7860/JCDR/2021/51206.15531 kostenfrei https://doaj.org/article/1b43f8c3afcd4cb8bfd650b5e6ecba9f kostenfrei https://jcdr.net/articles/PDF/15531/51206_CE[Ra1]_F[SH]_PF1(JY_RK)_PFA(SC_AnK_KM)_PN(KM).pdf kostenfrei https://doaj.org/toc/2249-782X Journal toc kostenfrei https://doaj.org/toc/0973-709X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 10 BC27-BC30
allfieldsSound	10.7860/JCDR/2021/51206.15531 doi (DE-627)DOAJ019763549 (DE-599)DOAJ1b43f8c3afcd4cb8bfd650b5e6ecba9f DE-627 ger DE-627 rakwb eng Kavita Aggarwal verfasserin aut Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase. haemolysis laboratory errors preanalytical errors quality indicator Medicine R Sumit Jhajharia verfasserin aut Tapaswini Pradhan verfasserin aut Viyatprajna Acharya verfasserin aut Saurav Patra verfasserin aut Sri Krushna Mahapatra verfasserin aut In Journal of Clinical and Diagnostic Research JCDR Research and Publications Private Limited, 2009 15(2021), 10, Seite BC27-BC30 (DE-627)789478048 (DE-600)2775283-5 0973709X nnns volume:15 year:2021 number:10 pages:BC27-BC30 https://doi.org/10.7860/JCDR/2021/51206.15531 kostenfrei https://doaj.org/article/1b43f8c3afcd4cb8bfd650b5e6ecba9f kostenfrei https://jcdr.net/articles/PDF/15531/51206_CE[Ra1]_F[SH]_PF1(JY_RK)_PFA(SC_AnK_KM)_PN(KM).pdf kostenfrei https://doaj.org/toc/2249-782X Journal toc kostenfrei https://doaj.org/toc/0973-709X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 10 BC27-BC30
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source	In Journal of Clinical and Diagnostic Research 15(2021), 10, Seite BC27-BC30 volume:15 year:2021 number:10 pages:BC27-BC30
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title_sort	analysis of errors in a clinical laboratory of a tertiary care hospital, odisha, india
title_auth	Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India
abstract	Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase.
abstractGer	Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase.
abstract_unstemmed	Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase.
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Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. 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Analysis of Errors in a Clinical Laboratory of a Tertiary Care Hospital, Odisha, India

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