Automating the Competence Matrix of a Quality Control Laboratory with the Relational Database Management Framework—A Case Study with the Analytical Chemistry Unit of a National Regulatory Agency
This study analyzed the concept of time efficiency in the data management process associated with the personnel training and competence assessments in one of the quality control (QC) laboratories of Nigeria’s Foods and Drugs Authority (NAFDAC). The laboratory administrators were burdened with a lot of mental and paper-based record keeping because the personnel training’s data were managed manually, hence not efficiently processed. The Excel spreadsheet provided by a Purdue doctoral dissertation as a remedial to this challenge was found to be deficient in handling operations in database tables, and therefore did not appropriately address the inefficiencies. Purpose: This study aimed to reduce the time it essentially takes to generate, obtain, manipulate, exchange, and securely store data that are associated with personnel competence training and assessments. Method: The study developed a software system that was integrated with a relational database management system (RDBMS) to improve manual/Excel-based data management procedures. To validate the efficiency of the software the mean operational times in using the Excel-based format were compared with that of the “New” software system. The data were obtained by performing four predefined core tasks for five hypothetical subjects using Excel and the “New” system (the model system) respectively. Results: It was verified that the average time to accomplish the specified tasks using the “New” system (37.08 seconds) was significantly (p = 0.00191, α = 0.05) lower than the time measurements for the Excel system (77.39 seconds) in the ANACHEM laboratory. The RDBMS-based “New” system provided operational (time) efficiency in the personnel training and competence assessment process in the QC laboratory and reduced human errors.
References
[1]
Pierre-Louis, L. (2014) Pharmaceuticals Regulation—An Overview.
https://www.sciencedirect.com/topics/pharmacology-toxicology-and-pharmaceutical-science/pharmaceuticals-regulation
[2]
Selvaraj, G. and Hari, S. (2018) A Study on Competency Mapping among Operators. Indian Journal of Applied Research, 8, 45-47.
[3]
Getha-Taylor, H., Hummert, R., Nalbandian, J. and Silvia, C. (2013) Competency Model Design and Assessment: Findings and Future Directions. Journal of Public Affairs Education, 19, 141-171. https://doi.org/10.1080/15236803.2013.12001724
[4]
Gonsalvez, C.J. and Calvert, F.L. (2014) Competency-Based Models of Supervision: Principles and Applications, Promises and Challenges. Australian Psychologist, 49, 200-208. https://doi.org/10.1111/ap.12055
[5]
National Agency for Food and Drug Administration and Control (2004) NAFDAC Mandate. https://www.nafdac.gov.ng/about-nafdac/nafdac-organisation/nafdac-functions/
[6]
Okezue, M.A. (2022) Developing Multipronged Models to Enhance Effectiveness of the Management System of Quality Control Laboratories. Additional Focus on Synthesis and Characterization for 5 New Salts of Bedaquiline. Master’s Thesis, Purdue University Graduate School, West Lafayette.
https://hammer.purdue.edu/articles/thesis/DEVELOPING_MULTIPRONGED_MODELS_TO_ENHANCE_EFFECTIVENESS_OF_THE_MANAGEMENT_SYSTEM_OF_QUALITY_CONTROL_LABORATORIES_ADDITIONAL_FOCUS_ON_SYNTHESIS_AND_CHARACTERIZATION_FOR_5_NEW_SALTS_OF_BEDAQUILINE/19620642/1
[7]
Guerrero, C. (2021) Competencies of Medical Laboratory Personnel: Basis for Developing a Health Training Program. ScienceOpen Posters.
https://www.scienceopen.com/hosted-document?doi=10.14293/S2199-1006.1.SOR-.PPVQKVL.v1
https://doi.org/10.14293/S2199-1006.1.SOR-.PPVQKVL.v1
[8]
Sohne, G. (2008) Community Revenue Collection System. Journal Community Informatics, 4, 1-9.
https://www.semanticscholar.org/paper/Community-Revenue-Collection-System-Sohne/da2af9db9a802e746cd269d65d03e9b7929bbe07
[9]
Kim, H., Dykes, P.C., Thomas, D., Winfield, L.A. and Rocha, R.A. (2011) A Closer Look at Nursing Documentation on Paper Forms: Preparation for Computerizing a Nursing Documentation System. Computers in Biology and Medicine, 41, 182-189.
http://www.proquest.com/docview/1033165112/abstract/43D684298CF419BPQ/1
https://doi.org/10.1016/j.compbiomed.2010.08.006
[10]
AL-Rawajfah, O.M., Aloush, S. and Hewitt, J.B. (2015) Use of Electronic Health- Related Datasets in Nursing and Health-Related Research. Western Journal of Nursing Research, 37, 952-983. https://doi.org/10.1177/0193945914558426
[11]
Okezue, M.A., Adeyeye, M.C., Byrn, S.J., Abiola, V.O. and Clase, K.L. (2020) Impact of ISO/IEC 17025 Laboratory Accreditation in Sub-Saharan Africa: A Case Study. BMC Health Services Research, 20, Article No. 1065.
https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-020-05934-8
https://doi.org/10.1186/s12913-020-05934-8
[12]
Melissa, B. (2021) How to Switch from Excel to SQL.
https://mode.com/blog/learn-sql-using-excel
[13]
Gupta, Y. (2020) Excel V/S MySQL. Data Science Simplified.
https://medium.com/dssimplified/excel-v-s-mysql-de32b78e7988
[14]
Azam, A., Alam, K.A. and Umair, A. (2019) Spreadsheet Smells: A Systematic Mapping Study. 2019 International Conference on Frontiers of Information Technology (FIT), Islamabad, 16-18 December 2019, 345-3455.
https://doi.org/10.1109/FIT47737.2019.00071
[15]
Powell, S.G., Baker, K.R. and Lawson, B. (2009) Errors in Operational Spreadsheets: A Review of the State of the Art. 2009 42nd Hawaii International Conference on System Sciences, Waikoloa, 5-8 January 2009, 1-8.
[16]
Rahman, S., Bendre, M., Liu, Y., Zhu, S., Su, Z., Karahalios, K., et al. (2021) NOAH: Interactive Spreadsheet Exploration with Dynamic Hierarchical Overviews. Proceedings of the VLDB Endowment, 14, 970-983.
https://doi.org/10.14778/3447689.3447701
[17]
World Health Organization (2016) Guidance on Good Data and Record Management Practices. WHO Technical Report Series No. 996.
https://www.gmp-compliance.org/files/guidemgr/WHO_TRS_996_annex05.pdf
[18]
Soegoto, E.S., Wardana, M.E. and Oktafiani, D. (2021) Implementation of Management Information System at Health Agencies. Journal of Physics: Conference Series, 1764, Article ID: 012191. https://doi.org/10.1088/1742-6596/1764/1/012191
[19]
Newbrander, W.C. and Thomason, J.A. (1988) Computerizing a National Health System in Papua New Guinea. Health Policy and Planning, 3, 255-259.
https://doi.org/10.1093/heapol/3.3.255
[20]
Rathnayake, W.D.W.T. (2021) Pharmacy Management System for the Central Pharmacy—Pokunuwita. https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4312
[21]
Sarker, N.C. (2018) Online Inventory and Order Management System for Pharmacy. http://dspace.uiu.ac.bd/handle/52243/469
[22]
Mostafa, S.A., AbuSalim, S.W. and Saringat, M.Z. (2020) A Comparative Study of Data Management Systems. Journal of Soft Computing and Data Mining, 1, 10-16.
https://doi.org/10.30880/jscdm.2020.01.01.002
[23]
Batra, S. and Sachdeva, S. (2021) Pre-Processing Highly Sparse and Frequently Evolving Standardized Electronic Health Records for Mining. Handbook of Research on Disease Prediction through Data Analytics and Machine Learning. IGI Global.
https://doi.org/10.4018/978-1-7998-2742-9.ch002
[24]
Tashkandi, A., Wiese, I. and Wiese, L. (2018) Efficient In-Database Patient Similarity Analysis for Personalized Medical Decision Support Systems. Big Data Research, 13, 52-64. https://www.sciencedirect.com/science/article/pii/S2214579617303088
https://doi.org/10.1016/j.bdr.2018.05.001
[25]
Li, H., Zhao, Z., Cheng, Y., Lu, W., Du, X. and Pan, A. (2019) Efficient Time-Interval Data Extraction in MVCC-Based RDBMS. World Wide Web, 22, 2633-2653.
https://doi.org/10.1007/s11280-018-0552-7
[26]
Paul, A.K., Wang, B., Rutman, N., Spitz, C. and Butt, A.R. (2020) Efficient Metadata Indexing for HPC Storage Systems. 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), Melbourne, 11-14 May 2020, 162-171. https://doi.org/10.1109/CCGrid49817.2020.00-77
[27]
Gai, L. (2020) Leveraging Neighborhood Summaries for Efficient RDF Queries on RDBMS. arXiv: 2001.08329. http://arxiv.org/abs/2001.08329
[28]
Gard, M., Hasterok, D. and Halpin, J.A. (2019) Global Whole-Rock Geochemical Database Compilation. Earth System Science Data, 11, 1553-1566.
https://doi.org/10.5194/essd-11-1553-2019
[29]
Daphine, A. (2013) An Automated Library Management System: A Case Study of Kashenyi Vocational Senior Secondary School.
https://ir.kiu.ac.ug/handle/20.500.12306/13387
[30]
Albalkhi, A. (2012) Repetitive Querying of Large Random Heterogeneous Datasets in RDBMS Using Materialized Views. Master’s Thesis, University of Windsor, Windsor. https://scholar.uwindsor.ca/etd/311
[31]
Azeez, N., Dasylva, A. and Omisore, O. (2018) RDBMS Query for Authenticating Access to Patient Information. Computer Science & Telecommunications, 54, 44-56.
https://www.researchgate.net/publication/341946386
[32]
Coetzee, L.M., Tepper, M.E., Perelson, L., Glencross, D.K. and Cassim, N. (2020) Timely Delivery of Laboratory Efficiency Information, Part II: Assessing the Impact of a Turn-Around Time Dashboard at a High-Volume Laboratory. African Journal of Laboratory Medicine, 9, a948. https://hdl.handle.net/10520/EJC-1d3b5bf122
https://doi.org/10.4102/ajlm.v9i2.948
[33]
Mayer, D.A., Rasmussen, L.V., Roark, C.D., Kahn, M.G., Schilling, L.M. and Wiley, L.K. (2021) ReviewR: A Light-Weight and Extensible Tool for Manual Review of Clinical Records. JAMIA Open, 5, ooac071.
[34]
Sánchez-de-Madariaga, R., Munoz, A., Castro, A.L., Moreno, O. and Pascual, M. (2018) Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases. Journal of Visualized Experiments, 1, e57439. https://doi.org/10.3791/57439
[35]
Ravikiran, A. (2021) Understanding the Difference between SQL and MySQL.
https://www.simplilearn.com/tutorials/sql-tutorial/difference-between-sql-and-mysql
[36]
Reese, G., Yarger, R., King, T. and Williams, H.E. (2002) Managing & Using MySQL: Open Source SQL Databases for Managing Information & Web Sites. O’Reilly Media, Sebastopol.
[37]
R Core Team (2018) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
[38]
Danziger, J.N. and Kraemer, K.L. (1985) Computerized Data-Based Systems and Productivity among Professional Workers: The Case of Detectives. Public Administration Review, 45, 196-209. https://doi.org/10.2307/3110149
[39]
Hubaish, A.M.A., Addeeb, B.M., Al-Serouri, A., Mughalles, S. and Ghaleb, Y. (2022) The Impact of Computerized Health Information System on Medical & Administrative Decisions, Sana’a Hospitals, Yemen (2017-2020). E-Health Telecommunication Systems and Networks, 11, 47-66.
http://www.scirp.org/Journal/Paperabs.aspx?paperid=117867
https://doi.org/10.4236/etsn.2022.112004
[40]
Leiwo, J. and Heikkuri, S. (1998) An Analysis of Ethics as Foundation of Information Security in Distributed Systems. Proceedings of the Thirty-First Hawaii International Conference on System Sciences, Kohala Coast, 9 January 1998, 213-222.
