Laboratory Information Management System Research Articles

A SARS-CoV-2 minimum data standard to support national serology reporting.

Healthcare laboratory systems produce and capture a vast array of information, yet do not always report all of this to the national infrastructure within the United Kingdom. The global COVID-19 pandemic brought about a much greater need for detailed healthcare data, one such instance being laboratory testing data. The reporting of qualitative laboratory test results (e.g., positive, negative or indeterminate) provides a basic understanding of levels of seropositivity. However, to better understand and interpret seropositivity, how it is determined and other factors that affect its calculation (i.e., levels of antibodies), quantitative laboratory test data are needed. 36 data attributes were collected from 3 NHS laboratories and 20 CO-CONNECT project partner organisations. These were assessed against the need for a minimum dataset to determine data attribute importance. An NHS laboratory feasibility study was undertaken to assess the minimum data standard, together with a literature review of national and international data standards and healthcare reports. A COVID serology minimum data standard (CSMDS) comprising 12 data attributes was created and verified by 3 NHS laboratories to allow national granular reporting of COVID serology results. To support this, a standardised set of vocabulary terms was developed to represent laboratory analyser systems and laboratory information management systems. This paper puts forward a minimum viable standard for COVID-19 serology data attributes to enhance its granularity and augment the national reporting of COVID-19 serology laboratory results, with implications for future pandemics.

The Implementation of Enterprise Resource Planning Informatics Department Education Laboratory

In preparing for the accreditation of units, study programs, and tertiary institutions to achieve a superior rating, Universitas Atma Jaya Yogyakarta (UAJY) often faces challenges in gathering and accessing the necessary resources. These difficulties stem from the accreditation preparation process, ineffective resource management, a lack of data integration, and restricted resource access. Taking advantage of advancements in information technology, UAJY has adopted the ERP Laboratory Information Management System (LIMS) to effectively manage the resources within its educational laboratories. These laboratories serve as a vital support unit in fulfilling the Tri Dharma of Higher Education and play a significant role in enhancing the learning process at the university. Enterprise Resource Planning (ERP) is a strategic tool that can provide organizations with a competitive edge by synchronizing, integrating, and optimizing data. The implementation of ERP LIMS serves as a solution for better resource management within the UAJY Informatics Department's educational laboratories.

Abstract 4427: Do changes in lipid metabolism link obesity to pancreatic cancer

Abstract The near equal incidence and mortality rates of pancreatic cancer, combined with projections that pancreatic cancer will become the second-most common cancer-related deaths by 2050, underscore the need to identify patients with early disease and interrupt this trajectory. Obesity, weight gain and waistline have been implicated in increasing the risk of pancreatic cancer. Although metabolomic analyses of pancreatic cancer patients have established correlations between phospholipids, lysophospholipids with treatment outcomes, the association between metabolites, obesity, and pancreatic cancer remains largely understudied. The objective of this pilot study was to determine differences in serum metabolites in obese and overweight pancreatic cancer patients compared with healthy non-obese subjects. Our long-term goal is to develop serum marker(s) that may be used to prevent advanced pancreatic cancer and thus improve outcomes for these patients. Serum was obtained from healthy subjects (n=11; BMI range from 18-25), overweight (n=9; 25-30) and obese (n=7; >30) pancreatic cancer patients from an IRB approved study. Males (n=12) and females (n=15) were represented in the study. Global metabolic profiles were determined using Ultrahigh performance liquid chromatography-tandem mass spectroscopy. Raw data was extracted, peaks were identified and processed at Metabolon using the Laboratory Information Management System. Comparison between overweight pancreatic cancer patients and healthy controls identified 403 biochemicals (111 upregulated and 292 downregulated; p <0.05) and 93 biochemicals (40 upregulated and 53 downregulated; 0.05<p<0.10). Comparison of the differences in biochemicals between obese pancreatic cancer patients and healthy controls showed changes in 293 biochemicals (71 upregulated and 222 downregulated; p <0.05) and 123 biochemical changes at 0.05<p<0.10 (42 increased and 81 decreased). 38 (p <0.05) and 47 (0.05<p<0.10) differential levels of biochemicals were identified when obese and overweight pancreatic cancer patients were compared. Random forest analysis showed that the 30 top ranking biochemicals were involved in lipid metabolism, amino acid metabolism, nucleotide metabolism, peptide, xenobiotics, and carbohydrate metabolism. These data suggest an association between changes in lipid metabolism may be another link between obesity and pancreatic cancer. This project was funded in part by VA-Merit Award (I01 BX003876). Citation Format: Rita Ghosh, Deepa Ajit, Jillian Woodworth, Danielle Fritze, Francisco G. Cigarroa, Glenn A. Halff, Addanki Pratap Kumar. Do changes in lipid metabolism link obesity to pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4427.

Development and evaluation of three automated media pooling and molecular diagnostic systems for the detection of SARS-CoV-2.

Pooled testing combined with molecular diagnostics for the detection of SARS-CoV-2 is a promising method that can increase testing capacities and save costs. However, pooled testing is also associated with the risks of decreased test sensitivity and specificity. To perform reliable pooled testing, we developed and validated three automated media pooling and molecular diagnostic systems. These pooling systems (geneLEAD-PS, Panther-PS, and Biomek-PS) comprised existing automated molecular detection platforms, corresponding automated media pooling devices, and laboratory information management systems. Analytical sensitivity analysis and mock sample evaluation were performed, and the obtained data were used to determine the sizes of the pool for the validation study. In the validation study, a total of 2,448, 3,228, and 6,420 upper respiratory samples were used for geneLEAD-PS, Panther-PS, and Biomek-PS, respectively, and the diagnostic performances were compared with the reference RT‒PCR assay. A pool size of 6 for geneLEAD-PS and a pool size of 4 for Panther-PS and Biomek-PS were selected for the validation studies. All three systems showed high positive percent agreement values of ≥90.5% and negative percent agreement values of ≥99.8% for any specimen type. Pooled testing resulted in a 65%-71% reduction in cost per sample. The testing capacities of geneLEAD-PS, Panther-PS, and Biomek-PS were 144 samples in 3 hours, 384 samples in 5.5 hours, and 376 samples in 4 hours, respectively. The developed pooling systems showed robust diagnostic performances and will increase the testing capacities of molecular diagnostic tests while saving costs and may contribute to infection control of COVID-19.IMPORTANCEDuring the COVID-19 pandemic, there have been surges in demand for accurate molecular diagnostic testing and laboratory supply shortages. Pooled testing combined with highly sensitive molecular testing, which entails mixing multiple samples as a single sample, is a promising approach to increase testing capacities while reducing the use of consumables. However, pooled testing is associated with risks that compromise diagnostic performance, such as false negatives due to dilution of positive samples or false positives due to cross-contamination. To perform reliable pooled testing, three different pooling systems (an automated pooling device, an automated molecular detection platform, and a laboratory information management system) were developed to accurately interpret pooled testing results. These three systems were validated using multiple clinical samples and showed high concordance with individual testing. The developed pooling systems will contribute to increasing reliable molecular testing capacities while using fewer consumables and saving costs.

MALDI-MS in first-line screening of newborns for sickle cell disease: results from a prospective study in comparison to HPLC.

Newborn screening (NBS) for sickle cell disease (SCD) requires a robust, high-throughput method to detect hemoglobin S (HbS). Screening for SCD is performed by qualitative methods, such as isoelectric focusing (IEF), and both qualitative and quantitative methods such as high performance liquid chromatography (HPLC), capillary electrophoresis (CE), and tandem mass spectrometry (MS/MS). All these methods detect HbS, as well as low-level or absent HbA, and also other variants of hemoglobin. HPLC is considered as a reference method for NBS, because of its high sensitivity and specificity in detecting HbS. NeoSickle®, a fully automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform, combined with automated sample processing, a laboratory information management system and NeoSickle® software for automatic data interpretation, has increased the throughput of SCD testing. The purpose of this study was to compare the performances of NeoSickle® and HPLC. A prospective study was conducted including 9,571 samples from the NBS program to compare MALDI-MS using NeoSickle® with an HPLC method. Correlation between the two methods was studied. For the MALDI-MS method, sensitivity, specificity, NPV, and PPV were calculated. We found over 99.4 % correlation between the HPLC and MALDI-MS results. NeoSickle® showed 100 % of sensitivity and specificity in detecting SCD syndrome, leading to positive and negative predictive values of 100 %. NeoSickle® is adapted to NBS for SCD, and can be used in first-line high-throughput screening to detect HbS, and beta-thalassemia major warning. When HbS is detected, second-line use of another specific method as HPLC is necessary.

The LILY Database: Linking Lithology to IODP Physical, Chemical, and Magnetic Properties Data

AbstractDuring each expedition of the International Ocean Discovery Program and its precursor, the Integrated Ocean Drilling Program (jointly referred to as IODP), vast arrays of data are collected from drill cores. These data, which are accessible from the IODP LIMS (Laboratory Information Management System) database, include physical, chemical, and magnetic properties collected semi‐continuously along cores using automated track systems, as well as a variety of analyses conducted on discrete subsamples taken from the cores. In addition, the lithology of all cores is described based on visual characteristics of the surface of split cores, visual examination of smear slides and thin sections, and compositional or mineralogical information derived from geochemical analyses. We extract basic lithologic information from this complex array of descriptive information and then tie that information to all other measurements. This new database is referred to as LIMS with Lithology (LILY). LILY currently contains over 34 million data from 89 km of core recovered on 42 expeditions conducted 2009–2019. Some uses of LILY include identifying the abundance of different lithologies, finding data from core intervals with a specific lithology, assessing the efficacy of coring systems in different lithologies, or characterizing and analyzing physical, chemical, and magnetic properties based on lithology. We illustrate the use of LILY by computing the grain density by lithology from over 24,000 moisture and density measurements and then use those grain densities, along with the large IODP bulk density dataset, to compute a new high‐resolution porosity dataset with over 3.7 million new porosity estimates.

A Retrospective Observational Study to Assess the Quality Management System in a Molecular Diagnostic Laboratory of a COVID-19 Dedicated Hospital in Delhi, India

Introduction: A molecular diagnostic laboratory is the cornerstone of Coronavirus Disease-2019 (COVID-19) disease diagnosis, as the patient’s treatment and management protocol depend on molecular results. Therefore, the laboratory conducting these tests must adhere to quality management process to increase the accuracy and validity of the generated reports. Rajiv Gandhi Super Speciality Hospital established its molecular diagnostic set-up at the beginning of the pandemic. Hence, this study aims to generate quality management data to help improve weak points. Aim: To assess the quality management system for COVID-19 diagnosis. Materials and Methods: This retrospective observational study was conducted at Rajiv Gandhi Super Speciality Hospital in Delhi, India. A total of 14,561 samples were collected over six months, from February 2021 to July 2021. Data from all samples received during this period for COVID-19 ReverseTranscriptase Polymerase Chain Reaction (RT-PCR) testing were included. Data were retrospectively collected from the electronic Laboratory Information Management System (LIMS). Quality variables were analysed over six months from July to December 2021 and classified into preanalytical, analytical, and postanalytical variables. Quality Indicators (QIs) were selected from a common model of QIs set by the International Federation of Clinical Chemistry and Laboratory Medicine. The results were presented in percentages, and descriptive statistics were analysed using Statistical Package for Social Sciences (SPSS) software. Results: During the six-month study period, the molecular laboratory received 14,561 samples. Among the preanalytical variables, sample leakage was the most common cause of sample rejection (134 samples, 0.92%), followed by the non generation of Specimen Referral Form (SRF) identification (76 samples, 0.52%), and non compliance with triple packaging (44 samples, 0.3%). Other preanalytical aspects assessed included incomplete patient identification (17 samples, 0.11%), insufficient sample quantity (12 samples, 0.08%), missing forms/samples (7 samples, 0.04%), samples in the wrong vials/ empty Viral Transport Media (VTM) tubes (5 samples, 0.03%), and incomplete LIMS entry (2 samples, 0.01%). Internal Quality Control (QC) was not obtained in 55 samples (0.37%), and two incidents of cross-contamination resulted in false-positive results. Among the postanalytical factors, 11 samples (0.07%) could not be dispatched within the stipulated time frame. Conclusion: The assessment of the quality management system revealed some areas for improvement, emphasising the importance of adhering to QC processes for the smooth operation of diagnostic laboratories, especially those involved in critical reporting. The assessment of QIs helped monitor laboratory parameters effectively.

EXTENSIVELY DRUG RESISTANT (XDR) SALMONELLA TYPHI RED FLAG FOR CLINICIANS AT KARACHI

Background: Salmonella typhi cause enteric fever which is a grave community health problem with increasing antibiotic resistance. Salmonella typhi is responsible for 10.9 million morbidities and 116800 mortalities worldwide with the greatest burden falling on third world countries. It is common among children with incidence rate of typhoid fever 573.2 per 100,000 in aged 2-5years and 451.7 cases per 100,000 children per year among 2-15years old in Pakistan. Early detection of Salmonella typhi and selection of appropriate antibiotics are important to mitigate the morbidity and fatality rate related to these kinds of infections. We have conducted this study to assess the extensively drug resistance in isolates of Salmonella typhi in Karachi, Pakistan. Material and Methods: This cross-sectional study was done at private set up, Karachi from 2019-2021. This study was ethically approved from hospital management. Data related to phenotypic detection of antimicrobial susceptibility was obtained from LIMS (Laboratory Information Management System). According to record both in-door and out-door patients were included in the study. The collected data was scrutinized by using descriptive statistics performed with SPSS version 24. Chi-square was used to test for statistical significance (P ≤ 0.05). Results: Total 10564 samples were extracted from data, out of which 4582 samples were found positive for growth of different microorganisms. Salmonella typhi were positive in 1500 cases and only 412 samples were exhibiting XDR Salmonella typhi. Maximum cases of XDR Salmonella typhi were detected in age group 5-10 years with 38.8%. There were 61% male and 39% female. Conclusion: Our study explains that cases of enteric fever as a result of Salmonella typhi are swarming in all cities of Pakistan and particularly at Karachi. XDR is not restricted to Karachi but it is the tip of the iceberg. There is an urgent need to detect these cases timely and start appropriate treatment to overcome complications. Keywords: Salmonella typhi, XDR, Antimicrobial susceptibility, Ceftriaxone, Azithromycin.

Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.

National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.

Cryoconveyor protocols in correlation light and electron microscopy: From multilevel imaging to modeling of biophysical effects and “cryotheranostics”

This paper is a technical and methodological note, the purpose of which is to introduce into the practice of biological research methods of cryomicroscopy in a conveyor mode, starting from small magnifications and ending with the limits of magnification/resolution of scanning electron cryomicroscopy. The protocol described can be applied to the samples with low sample preparation complexity without ultratomy or the sample processing typical for transmission electron microscopy methods. According to this protocol samples are analyzed in a single microcuvette (chip) indexed by laboratory information management system and sequentially moved from the non-destructive low-resolution optical microscopy instruments (such as lensless cryomicroscopes) and optical super-resolution methods (some microinterferometers and MIMs with cryotables) to the CryoSEM/CryoESEM level (in programmable environments and atmospheres). Methods of correlation lensless cryomicroscopy and scanning microscopy (including those with the subsequent transition to microanalysis) were introduced; CryoCUVEM and CryoCIREM methods in the ultraviolet and infrared range, respectively; microinterferometry methods using a multi-beam reflected light interferometer (based on the MII-11 platform with several changes); the development of CryoCDICEM systems based on the optical path of an inverted metallographic microscope with a DIC attachment and a LED emitter was also initiated. The advantages of cryoconveyor analysis protocols are ensuring the sample safety in a single cuvette-chip and the possibility of establishing spatial colocalization between the data of optical and electron microscopy (including in the CLEM/CryoCLEM mode), as well as providing a comprehensive non- destructive sample analysis in the sequential study of the microscopic systems with the possibility of varying the subsequent stages of high-resolution microscopy, depending on the results obtained at the previous stages of lower resolution microscopic studies.

The impact of laboratory automation on efficiency and accuracy in healthcare settings

Automated sample processing systems, such as handlers, have played a role in expediting specimen handling, especially during emergencies. Additionally, automated analyzers have contributed to increased testing efficiency by enabling high throughput screening and quicker access to information. This article explores how the use of automated technology in laboratories has greatly improved efficiency and accuracy in healthcare settings. By examining the integration of automated systems for processing samples and conducting tests this review highlights the impact automation has had on outcomes. One notable benefit is reduced turnaround times, streamlined workflows, and enhanced precision in diagnostic testing. The incorporation of laboratory information management systems (LIMS) has further improved efficiency through data integration and real-time monitoring. Accuracy is an aspect of processes, and automated systems meticulously adhere to predefined protocols, resulting in reduced error rates and consistently reliable results. The introduction of intelligence (AI) has enhanced accuracy, particularly in image analysis within the pathology and radiology fields. Effective clinical management of laboratory automation entails technology selection planning for implementation and ongoing monitoring. Interoperability between systems, continuous education on advancements, and efficient workforce management are all crucial components for successful implementation. Despite challenges faced along the way, adopting laboratory automation is essential for optimizing laboratories' workflows while delivering timely information. The review consistently affirms laboratory automation's valid influence in improving efficiency and accuracy within healthcare environments.

A comprehensive LC-MS/MS method for the simultaneous measurement of 24 adrenal steroids: From research to clinical practice

Steroids are essential in the differential diagnosis of congenital adrenal hyperplasia (CAH) subtypes; however, they may confuse physicians with multifarious results. In this study, we established a liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous measurement of 24 steroids and developed a steroid metabolite pathway-based report to aid physicians in understanding these results. Solid-phase extraction was used to concentrate and purify target plasma steroids. The linearity, precision, recovery, and matrix effects were thoroughly evaluated. PowerBuilder was used to transfer the results from LC-MS/MS to the graphic report in a laboratory information management system (LIS) and was applied to different subtypes of CAH. Twenty-four steroids were separated and analyzed in one sample preparation and two injections using LC-MS/MS. The linearity of the steroids was excellent, with coefficients of linear regression greater than 0.99. The relative recovery ranged from 90.0 to 107.1 %, whereas the intra- and total coefficient variations were 1.6 ∼ 8.7 % and 2.0 ∼ 9.9 %, respectively. Matrix effects were compensated after internal standard correction. A graphic combination report mode was established and used to effectively identify CAH subtypes. In conclusion, a useful LC-MS/MS method and graphic combination report of 24 steroids based on their metabolite pathways were established.

Using <em>OpenBIS</em> as Virtual Research Environment: An ELN-LIMS Open-Source Database Tool as a Framework within the <em>CRC 1411 Design of Particulate Products</em>

The digital transformation and consequent use of new digital technologies not only have a substantial impact on society and companies, but also on science. Analog documentation as we have known it for centuries will eventually be replaced by intelligent and FAIR (Findable, Accessible, Interoperable, and Reusable) systems. In addition to the actual research data and results, metadata now plays an important role not only for individual, independently existing projects, but for future scientific use and interdisciplinary research groups and disciplines as well. The solution presented here, consisting of an electronic laboratory notebook and laboratory information management system (ELN-LIMS) based on the openBIS (open Biology Information System) environment, offers interesting features and advantages, especially for interdisciplinary work. The Collaborative Research Centre (CRC) 1411 ‘Design of Particulate Products’ of the German Research Foundation is characterized by the cooperation of different working groups of synthesis, characterization, and simulation, and therefore serves as a model environment to present the implementation of openBIS. OpenBIS, as an open source ELN-LIMS solution following FAIR principles, provides a common set of general entries with the possibility of sharing and linking (meta-)data to improve the scientific exchange between all users.

Utilising routine clinical laboratory data to support quality improvement in health care: Application of a national acute kidney injury alert system as a proof of concept.

Acute kidney injury (AKI) is a global health issue known to cause avoidable harm and death. Improvement in its prevention and management is therefore considered an important goal for the health-care sector. The work here aimed to develop a tool which could be used to robustly and reliably measure, monitor, and compare the effectiveness of health-care interventions related to AKI across the Welsh NHS, a mechanism which did not exist previously. Using serum creatinine (SCr) as a biomarker for AKI and a validated national data-set collected from the all Wales Laboratory Information Management System, work involved applying Donabedian's framework to develop indicators with which to measure outcomes related to AKI, and exploring the potential of statistical process control (SPC) techniques for analysing data on these indicators. Rate of AKI incidence and 30-day AKI-associated mortality are proposed as valid, feasible indicators with which to measure the effectiveness of health-care interventions related to AKI. The control chart, funnel plot, and Pareto chart are proposed as appropriate, robust SPC techniques to analyse and visualise variation in AKI-related outcomes. This work demonstrates that routinely collected large SCr data offer a significant opportunity to monitor and therefore inform improvement in patient outcomes related to AKI. Moreover, while this work concerns utilisation of SCr data for improvement in AKI strategies, it is a proof of concept which could be replicated for other routinely collected clinical laboratory data, to improve the prevention and/or management of the conditions to which they relate.

Development and evaluation of the automated multipurpose molecular testing system PCRpack for high-throughput SARS-CoV-2 testing

ABSTRACT Increasing the reliable testing capacity for SARS-CoV-2 is important for the diagnosis and control of COVID-19. We developed an automated, customizable, easy-to-implement molecular testing system, named PCRpack, for the high-throughput testing of SARS-CoV-2. PCRpack includes a liquid handling instrument enclosed in a negative-pressure clean booth (Biomek i5), a laboratory information management system (SimpPCR), other equipment, and documents that are needed for testing operation. An in vitro diagnostic assay was employed to detect SARS-CoV-2. System performance was evaluated based on liquid handling accuracy and precision, analytical sensitivity, clinical diagnostic performance, and testing capacity per day. Clinical diagnostic performance was determined against the reference extraction-based reverse transcription-PCR assay using 3,965 upper respiratory samples. Analytical sensitivity analysis showed a lower limit of detection of 1,000 genome copies/mL of sample. The accuracy and precision of sample or reagent dispensing in PCRpack ranged from −2.24% to 0.73% and 0.83% to 4.52%, respectively. In the evaluation of clinical samples, PCRpack showed a positive percent agreement of 96.6% and a negative percent agreement of 100% compared with the reference assay. The average turnaround times per 94 samples and the maximum numbers of tests within an 8-hour shift of one operator were 2 hours and 28 minutes vs 2 hours and 1 minute and 564 vs 376 samples for PCRpack and the manual method, respectively. The developed PCRpack system shows high liquid handling and clinical diagnostic performance and is a promising testing system for increasing the SARS-CoV-2 testing capacity and testing future emerging pathogens. IMPORTANCE Accurate and fast molecular testing is important for the diagnosis and control of COVID-19. During patient surges in the COVID-19 pandemic, laboratories were challenged by a higher demand for molecular testing under skilled staff shortages. We developed an automated multipurpose molecular testing system, named PCRpack, for the rapid, high-throughput testing of infectious pathogens, including SARS-CoV-2. The system is provided in an all-in-one package, including a liquid handling instrument, a laboratory information management system, and other materials needed for testing operation; is highly customizable; and is easily implemented. PCRpack showed robust liquid handling performance, high clinical diagnostic performance, a shorter turn-around time with minimal hands-on time, and a high testing capacity. These features contribute to the rapid implementation of the high-performance and high-throughput molecular testing environment at any phase of the pandemic caused by SARS-CoV-2 or future emerging pathogens.

Improved Biorepository to Support Sickle Cell Disease Genomics and Clinical Research: A Practical Approach to Link Patient Data and Biospecimens from Muhimbili Sickle Cell Program, Tanzania.

In Africa, sickle cell disease phenotypes' genetic contributors remain understudied due to the dearth of databases that pair biospecimens with demographic and clinical details. The absence of biorepositories in these settings can exacerbate this issue. This article documents the physical verification process of biospecimens in the biorepository, connecting them to patient clinical and demographic data and aiding in the planning of future genomic and clinical research studies' experience from the Muhimbili Sickle Cell Program in Dar es Salaam, Tanzania. The biospecimen database was updated with the current biospecimen position following the physical verification and then mapping this information to its demographic and clinical data using demographic identifiers. The biorepository stored 74,079 biospecimens in three -80°C freezers, including 63,345 from 5159 patients enrolled in the cohort between 2004 and 2016. Patients were identified by a control (first visit), entry (when confirmed sickle cell homozygous), admission (when hospitalized), and follow-up numbers (subsequent visits). Of 63,345 biospecimens, follow-ups were 46,915 (74.06%), control 8067 (12.74%), admission 5517 (8.71%), and entry 2846 (4.49%). Of these registered patients, females were 2521 (48.87%) and males were 2638 (51.13%). The age distribution was 1-59 years, with those older than 18 years being 577 (11.18%) and children 4582 (88.82%) of registered patients. The notable findings during the process include a lack of automated biospecimen checks, laboratory information management system, and tubes with volume calibration; this caused the verification process to be tedious and manual. Biospecimens not linked to clinical and demographic data, date format inconsistencies, and lack of regular updating of a database on exhausted biospecimens and updates when biospecimens are moved between positions within freezers were other findings that were found. A well-organized biorepository plays a crucial role in answering future research questions. Enforcing standard operating procedures and quality control will ensure that laboratory users adhere to the best biospecimen management procedures.

Development of Web-Based Computer Laboratory Management Information System at SMKS Pertiwi Batam

Development of Computer Laboratory Management Information System at SMKS Pertiwi Batam is an application to support the performance of related institutions. Lack of data collection and the absence of supporting applications and data that is still stored in the form of archives and computers manually. Information systems are designed based on websites using the codeigniter programming language and MySQL database. While the development of the research system uses the waterfall method with the stages of requirements, design, implementation, verification, and maintenance. This information system serves as a means of sharing information about the inventory of computer laboratory equipment, the use of computer laboratories, and schedules regarding the use of computer laboratories. With this information system, the agency will be easier in collecting inventory data, using and scheduling computer laboratories. As well as the need to make monthly reports on computer laboratory data.

Managing andmonitoring a pandemic: showcasing a practical approach forthe genomic surveillance ofSARS-CoV-2.

With the rapidly growing amount of biological data, powerful but also flexible data management and visualization systems are of increasingly crucial importance. The COVID-19 pandemic has more than highlighted this need and the challenges scientists are facing. Here, we provide an example and a step-by-step template for non-IT personnel to easily implement an intuitive, interactive data management solution to manage and visualize the high influx of biological samples and associated metadata in a laboratory setting. Our approach is illustrated with the genomic surveillance for SARS-CoV-2 in Germany, covering over 11 600 internal and 130 000 external samples from multiple datasets. We compare three data management options used in laboratories: (i) simple, yet error-prone and inefficient spreadsheets, (ii) complex and long-to-implement laboratory information management systems and (iii) high-performance database management systems. We highlight the advantages and pitfalls of each option and outline why a document-oriented NoSQL option via MongoDB Atlas can be a suitable solution for many labs. Our example can be treated as a template and easily adapted to allow scientists to focus on their core work and not on complex data administration.

Comparing transfusion practice at multiple hospitals using electronically collected and analysed data.

Comparisons of transfusion practice between organisations are time-consuming using manual methods for data collection. We performed a feasibility study to determine whether large-scale transfusion data from three English hospitals could be combined to allow comparisons of transfusion practice. Clinical, laboratory and transfusion data from patients discharged between 1 April 2016 and 31 March 2017 were extracted from Patient Administration Systems (PAS), Laboratory Information Management Systems (LIMS), and electronic transfusion systems at three NHS hospitals, which are academic medical centres based in large cities outside London. A centralised database and business intelligence software were used to compare the data. The dataset contained 748 982 episodes of patient care with 91 410 blood components transfused. The study confirms the results of previous studies finding peaks in the ages of transfusion in the 0-4 years age range, in women of childbearing ages, and in males over 60 years. The number of components transfused per 1000 bed days was used as a standardised comparator. Red cell utilisation was 42.4, 40.4 and 49.5 units/1000 bed days and platelet utilisation 11.69, 7.76, and 11.66 units/1000 bed days. 60.5% (6848/11 310) of Group O D negative red cell units were transfused to non-group O D negative recipients. An analysis of component usage highlighted variations in practice, for example platelet usage for cardiac surgery varied from 2.4% to 7.3% across the three hospitals. This feasibility study demonstrates that large electronic datasets from hospitals can be combined to identify areas for targeted interventions to improve transfusion practice.

SHOT UK Collaborative Reviewing and Reforming IT Processes in Transfusion (SCRIPT) survey: Laboratory information management systems: Are we ready for digital transformation?

To understand the use, functionality and interoperability of laboratory information management systems (LIMS) in UK transfusion laboratories. LIMS are widely used to support safe transfusion practice. LIMS have the potential to reduce the risk of laboratory error using algorithms, flags and alerts that support compliance with best practice guidelines and regulatory standards. Reporting to Serious Hazards of Transfusion (SHOT), the United Kingdom (UK) haemovigilance scheme, has identified cases where the LIMS could have prevented errors but did not. Shared care of patients across different organisations and the development of pathology networks has raised challenges relating to interoperability of IT systems both within, and between, organisations. A survey was distributed to all SHOT-reporting organisations to understand the current state of LIMS in the UK, prevalence of expertise in transfusion IT, and barriers to progress. Survey questions covered LIMS interoperability with other IT systems used in the healthcare setting. A variety of LIMS and version numbers are in use in transfusion laboratories, LIMS are not always updated due to resource constraints. Respondents identified interoperability and improved functionality as the main requirements for transfusion safety. A nationally agreed set of minimum standards for transfusion LIMS is required for safe practice. Adequate resources, training and expertise should be provided to support the effective use and timely updates of LIMS. A single LIMS solution should be in place for transfusion laboratories working within a network and interoperability with other systems should be explored to further improve practice.