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Neuron-specific enolase (NSE) derived from neurons and peripheral neuroendocrine cells is a biomarker for neuroendocrine tumors and for prognostication in comatose cardiac arrest survivors. However, as platelets and erythrocytes contain NSE, hemolysis causes falsely elevated NSE. We used native serum and hemolysate derived from the same patients to make serial dilutions, and subsequently measured NSE (mNSE) and hemolytic index (HI) in each dilution. An algorithm suitable for the laboratory information system was developed based on the mNSE, HI and the estimated gradient of hemolytic interference from 30 patients. We estimated the associated uncertainty of the corrected NSE (cNSE) results based on the observed range of the gradient and derived an equation for cNSE for samples with limited hemolysis (i.e. 5 < HI ≤ 30): cNSE = mNSE − HI × (0.34 ± 0.23) µg/L. By semi-quantitatively grading the contribution from limited hemolysis, a texted result noting the hemolysis-associated degree of uncertainty can accompany the cNSE result. The major challenge of hemolysis when using serum NSE as a biomarker can be managed using an automated algorithm for correction of NSE results based on degree of hemolysis. However, laboratorians and clinicians should be aware of the limitations associated with in vivo hemolysis. [ABSTRACT FROM AUTHOR]

Introduction 16 million German-language free-text laboratory test results are the basis of the daily diagnostic routine of 17 laboratories within the University Hospital Erlangen. As part of the Medical Informatics Initiative, the local data integration centre is responsible for the accessibility of routine care data for medical research. Following the core data set, international interoperability standards such as FHIR and the English-language medical terminology SNOMED CT are used to create harmonised data. To represent each non-numeric laboratory test result within the base module profile ObservationLab, the need for a map and supporting tooling arose. State of the Art Due to the requirement of a n:n map and a data safety-compliant local instance, publicly available tools (e.g., SNAP2SNOMED) were insufficient. Concept and Implementation Therefore, we developed (1) an incremental mapping-validation process with different iteration cycles and (2) a customised mapping tool via Microsoft Access. Time, labour, and cost efficiency played a decisive role. First iterations were used to define requirements (e.g., multiple user access). Lessons Learned The successful process and tool implementation and the described lessons learned (e.g., cheat sheet) will assist other German hospitals in creating local maps for inter-consortia data exchange and research. In the future, qualitative and quantitative analysis results will be published. [ABSTRACT FROM AUTHOR]

This study explores how patient’s laboratory result are accessed in pediatric emergency departments. The rapid turnaround of laboratory results and their timely access by the medical team are crucial for effective patient management and care decision-making. This study revealed a systematic access prioritization to the Electronic Health Record, led by physicians, followed by nurses, and then other healthcare staff Despite efforts to streamline access through computerized laboratory results, optimized laboratory turnaround time and integration of final results into the electronic health record remain key challenges. Delays in accessing analysis results issued by the central hospital laboratory are consistently experienced across various laboratory types, indicating broader systemic workflow issues rather than inefficiencies specific to individual laboratories. [ABSTRACT FROM AUTHOR]

Objectives To determine the extent and distribution of laboratory workforce shortages within the nation's medical laboratories. Methods The Vacancy Survey was conducted through collaboration between the American Society for Clinical Pathology (ASCP) Institute for Science, Technology and Public Policy in Washington, DC, and the Evaluation, Measurement, and Assessment Department and ASCP Board of Certification in Chicago, IL. Data were collected through an internet survey distributed to individuals who were able to report on staffing and certifications for their laboratories. Results Results of the ASCP 2022 Vacancy Survey show increased overall vacancy rates for laboratory positions in all departments compared with 2020. Overall retirement rates for laboratory professionals increased across most departments. Conclusions Current Vacancy Survey data show continued increases in the numbers of laboratory vacancies and retirements as well as changes in certification requirements, with trends amplified during the pandemic continuing into the present. Qualitative analysis results showed that there is an urgent need to focus not only on recruitment but—equally important—on retention of laboratory professionals. [ABSTRACT FROM AUTHOR]

The rapid acquisition of larg volumes of thin-section CT images has created a considerable need and interest for 3D postprocessing during the interpretation of medical imaging. As a result of the increasing number of postprocessing applications, requiring diagnostic radiologists to perform postprocessing is no longer realistic. This article is a comprehensive review of medical resources regarding establishing a postprocessing radiology laboratory. Besides, leadership and managerial aspects have been covered through a professional business lens. In large-volume settings, a dedicated 3D postprocessing lab ensures the quality, reproducibility, and efficiency of images. Adequate staffing is necessary to fulfill the postprocessing requirements. Educational and experience requirements for 3D technologists may vary among different running laboratories. To evaluate the establishment and running of a 3D lab, it is beneficial to implement diagnostic radiology cost-effectiveness tools. Although establishing a 3D lab has many benefits, certain challenges should be considered. Outsourcing or offshoring may serve as alternatives for establishing a postprocessing laboratory. Building and operating a 3D lab is a significant change in healthcare facilities, and it is crucial for organizations to be aware of the strong resistance toward alternatives the status quo, known as the status quo trap. The change process has essential steps, and skipping the steps creates an illusion of speed but never produces satisfactory results. The organization should ensure the engagement of all interested parties in the whole process. Moreover, a clear vision and proper communication of the vision are vital, and it is crucial to value small wins and ensure expectation clarity in leading the lab during the process. [ABSTRACT FROM AUTHOR]

Background: A summary of clinical findings and laboratory data is collected in patient summary sheets. The aim of this study was to determine the frequency of laboratory data reported in the summary sheets based on the classification of diagnoses in ICD-10. Methods: A descriptive-cross sectional study was performed on summary sheets of patients admitted to the pediatric ward from March 2015 to February 2016.The laboratory data of these sheets were extracted using a data collection form. Because of high number of data in each sheet and given that, depending on the diagnosis, the reported laboratory data were different, to simplify the presentation of the results the data were categorized based on patients’ diagnoses which were coded by ICD-10. Results: A total of 10224 laboratory data were extracted, which included 47 unique data elements. The highest number of laboratory data was related to hematology (N = 14) and the lowest number was related to urine and stool analysis (N = 6). Conclusions: Laboratory data are recorded in summary sheets in accordance with patient's diagnosis. Therefore, it is possible to process the existing summary sheets and extract the registration rules, then implement these rules in hospital information systems to generate electronic summary sheets.

The UCLA Immunogenetics Center is an Immunogenetics and Histocompatibility laboratory that performs testing for multiple transplant programmes within and outside of UCLA. The single antigen bead (SAB) test is a high complexity luminex bead test used to assess pretransplant and post-transplant patients for the presence of pathogenic human leucocyte antigen donor-specific antibody associated with allograft rejection. Efficient reporting of the SAB test has been difficult as data analysis and reports are generated in the laboratory information system (LIS) and uploaded to the electronic medical record (EMR) as PDFs. To solve this, we recently developed a state of the art reporting workflow allowing discrete reporting of SAB data (antibody specificity, mean fluorescent intensity and interpretative comments) from the LIS HistoTrac to UCLA Health System's EMR EPIC:CareConnect. However, a proportion of tests did not report to the EMR appropriately. Baseline system performance data evaluated over a 10-week period showed that ~4.5/100 tests resulted in EPIC as 'preliminary result' or 'in process' instead of 'final result' with only common cause variation. Quality improvement methods were employed to improve the process with the SMART Aim of reporting 100% of tests as 'final result'. Pareto analysis identified two errors accounting for 79% of common system-level failures-status errors and interface errors. We hypothesised that addressing the status error would reduce or eliminate the interface errors. We used the Model For Improvement to test a reprogramming intervention. Status and interface errors were completely resolved through the process improvement. Continuous monitoring revealed a system-level shift with only ~1.9/100 tests resulting inappropriately. Through the audit process, the remaining common system-level failures were identified and resolved. Therefore, 100% of tests result to EPIC as 'final result'. The study demonstrates that high complexity SAB bead data can be efficiently reported EPIC:CareConnect from HistoTrac as discrete data.

Background and Aim: Iranian hospitals are provided with hospital information systems (HISs) from different vendors, which make it hardly possible to summarize laboratory data in an consistent manner. Therefore, there is a need to design a minimum data set of laboratory data that will define standard criteria and reduce potential medical errors. The purpose of this study was to design a minimum data set (MDS) of laboratory data for an electronic summary sheet to be used in the pediatric ward of Iranian hospitals. Methods: This study consists of three phases. In the first phase, out of 3997 medical records from the pediatric ward, 604 summary sheets were chosen as sample. The laboratory data of these sheets were examined and the recorded tests were categorized. In the second phase, based on the types of diagnosis we developed a list of tests. Then we asked the physicians of the ward to select which ones should be documented for each patient's diagnosis. In the third phase, the tests that were reported in 21%–80% of the records, and were verified by the same percentage of physicians, were evaluated by the experts' panel. Results: In the first phase, 10,224 laboratory data were extracted. Of these, 144 data elements reported in more than 80% of the records, and more than 80% of experts approved them to be included in the MDS for patients' summary sheet. After data elements were investigated in the experts' panel, 292 items were chosen for the final list of the data set. Conclusions: This MDS was designed such that, if implemented in hospital information systems, it could automatically enable registering data in the summary sheet when patient's diagnosis is registered. [ABSTRACT FROM AUTHOR]

Abstract Background and Aim Iranian hospitals are provided with hospital information systems (HISs) from different vendors, which make it hardly possible to summarize laboratory data in an consistent manner. Therefore, there is a need to design a minimum data set of laboratory data that will define standard criteria and reduce potential medical errors. The purpose of this study was to design a minimum data set (MDS) of laboratory data for an electronic summary sheet to be used in the pediatric ward of Iranian hospitals. Methods This study consists of three phases. In the first phase, out of 3997 medical records from the pediatric ward, 604 summary sheets were chosen as sample. The laboratory data of these sheets were examined and the recorded tests were categorized. In the second phase, based on the types of diagnosis we developed a list of tests. Then we asked the physicians of the ward to select which ones should be documented for each patient's diagnosis. In the third phase, the tests that were reported in 21%–80% of the records, and were verified by the same percentage of physicians, were evaluated by the experts' panel. Results In the first phase, 10,224 laboratory data were extracted. Of these, 144 data elements reported in more than 80% of the records, and more than 80% of experts approved them to be included in the MDS for patients' summary sheet. After data elements were investigated in the experts' panel, 292 items were chosen for the final list of the data set. Conclusions This MDS was designed such that, if implemented in hospital information systems, it could automatically enable registering data in the summary sheet when patient's diagnosis is registered.

Point-of-care testing is widely used in a variety of clinical settings. While this testing provides immediate and actionable clinical information, it is prone to error in both the interpretation and reporting of results. Point-of-care urinalysis presents unique opportunities for errors, ranging from variation in visual interpretation to input of results. The data included here represent the results from 63,279 urinalyses from 36,780 unique patients performed over a span of three years at an academic medical center and its associated clinics. The data include the patient age/legal sex, methodology (instrument and test strip used), and the available test results (color, clarity, glucose, bilirubin, ketones, specific gravity, blood, pH, protein, urobilinogen, nitrite, and leukocyte esterase). Additionally, we include the method of interface between the testing instrumentation and our electronic medical record (EMR). These fell into one of three broad categories: “Interfaced” (results directly transmitted from the urinalysis instrument to the EMR via specialized data interface), “Manual” (results input by selecting from a drop-down menu in the laboratory information system), and “Enter/Edit” (results typed freely into a text field in the EMR). Analysis of this data was primarily a direct comparison of detectable errors (typos, uninterpretable results, and results outside the reportable range) as a function of the method of entry into the EMR. Secondary analysis comparing the impact of restricting drop-down menu options for urine color and clarity was also performed. These data are of use to others as they are diverse in terms of the test performed and the method of interface. Others may wish to analyze these data when making decisions as to how to perform and report these tests and when estimating risks of error with various methods of data entry.

With increasing access to electronic health records, patients may encounter dermatopathology reports more readily. Dermatopathologists should consider their impact and interactions with transgender patients, who may face specific health and healthcare inequities. Rendering accurate diagnosis for skin diseases requires accurate information about patient's sex assigned at birth and gender identity. Understanding how sex and gender identity data flow between electronic health records, laboratory information systems, insurance billing systems, and patients will be important to avoid patient misgendering, to render accurate diagnoses, to maintain consistency in dermatopathology reports, and to avoid insurance billing denials. Dermatopathologists have important roles to build patient trust in the healthcare system and to help dermatologists diagnose, treat, and characterize skin diseases in transgender populations. [ABSTRACT FROM AUTHOR]

Improving care for gender-diverse (GD) patients necessitates developing informatics tools and approaches to support optimal laboratory testing. This requires increased functionality and standardization of laboratory information system/electronic health record and data collection processes. Data tailored to accommodate immediate clinical care and clinical decision support (CDS) also have an impact on interoperability and downstream data needs for patients. Informatics tools can shape the clinical care experience for GD patients by careful design of laboratory-patient interactions., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background and Objective: Chronic kidney disease (CKD) is a major public health issue, and accurate prediction of the progression of kidney failure is critical for clinical decision-making and helps improve patient outcomes. As such, we aimed to develop and externally validate a machine-learned model to predict the progression of CKD using common laboratory variables, demographic characteristics, and an electronic health records database., Methods: We developed a predictive model using longitudinal clinical data from a single center for Chinese CKD patients. The cohort included 987 patients who were followed up for more than 24 months. Fifty-three laboratory features were considered for inclusion in the model. The primary outcome in our study was an estimated glomerular filtration rate ≤15 mL/min/1.73 m 2 or kidney failure. Machine learning algorithms were applied to the modeling dataset ( n = 296), and an external dataset ( n = 71) was used for model validation. We assessed model discrimination via area under the curve (AUC) values, accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score., Results: Over a median follow-up period of 3.75 years, 148 patients experienced kidney failure. The optimal model was based on stacking different classifier algorithms with six laboratory features, including 24-h urine protein, potassium, glucose, urea, prealbumin and total protein. The model had considerable predictive power, with AUC values of 0.896 and 0.771 in the validation and external datasets, respectively. This model also accurately predicted the progression of renal function in patients over different follow-up periods after their initial assessment., Conclusions: A prediction model that leverages routinely collected laboratory features in the Chinese population can accurately identify patients with CKD at high risk of progressing to kidney failure. An online version of the model can be easily and quickly applied in clinical management and treatment., Competing Interests: The authors declare that they have no competing interests., (© 2024 Du et al.)

Introduction: This study aimed to determine autoverification rules for routine glycated hemoglobin (HbA1c) analysis based on high-performance liquid chromatography (HPLC) principle. Laboratory information system (LIS) and Bio-Rad D-100 Advisor software (Bio-Rad, Hercules, USA) with graphics recognition function were carriers for the autoverification system., Materials and Methods: A total of 105,126 HbA1c results, including 98,249 HbA1c matching fast plasma glucose (FPG) results of real-world data from May 2019 to June 2020, were collected to determine autoverification rules including flags, delta checks, reporting limits, and logical rules. The validation database was composed of 48,045 HbA1c results and 41,083 matching FPG results. Autoverification passing rate and the reduction of turnaround time (TAT) were evaluated., Results: Four autoverification systems (A, B, C, D) were established by two types of delta check rules, 28 flags, one reporting limits, and two kinds of logical rules. The autoverification passing rates were 80.6%, 78.8%, 83.7%, and 81.3%, and the average time saved in TAT were 117.5 min, 116.7 min, 121.1 min, and 121.7 min, respectively., Conclusions: Autoverification system C was the optimal one. Application of distribution of FPG corresponding to HbA1c groups had better performance as logical rules. Established HbA1c autoverifcation system shortened the auditing report time and improved work efficiency., Competing Interests: Potential conflict of interest None declared., (Croatian Society of Medical Biochemistry and Laboratory Medicine.)

Objective: Assess the effectiveness of providing Logical Observation Identifiers Names and Codes (LOINC®)-to-In Vitro Diagnostic (LIVD) coding specification, required by the United States Department of Health and Human Services for SARS-CoV-2 reporting, in medical center laboratories and utilize findings to inform future United States Food and Drug Administration policy on the use of real-world evidence in regulatory decisions.Materials and Methods: We compared gaps and similarities between diagnostic test manufacturers' recommended LOINC® codes and the LOINC® codes used in medical center laboratories for the same tests.Results: Five medical centers and three test manufacturers extracted data from laboratory information systems (LIS) for prioritized tests of interest. The data submission ranged from 74 to 532 LOINC® codes per site. Three test manufacturers submitted 15 LIVD catalogs representing 26 distinct devices, 6956 tests, and 686 LOINC® codes. We identified mismatches in how medical centers use LOINC® to encode laboratory tests compared to how test manufacturers encode the same laboratory tests. Of 331 tests available in the LIVD files, 136 (41%) were represented by a mismatched LOINC® code by the medical centers (chi-square 45.0, 4 df, P < .0001).Discussion: The five medical centers and three test manufacturers vary in how they organize, categorize, and store LIS catalog information. This variation impacts data quality and interoperability.Conclusion: The results of the study indicate that providing the LIVD mappings was not sufficient to support laboratory data interoperability. National implementation of LIVD and further efforts to promote laboratory interoperability will require a more comprehensive effort and continuing evaluation and quality control. [ABSTRACT FROM AUTHOR]

ContextLow-grade appendiceal mucinous neoplasm (LAMN) and appendiceal adenocarcinoma are known to cause the majority of pseudomyxoma peritonei (PMP, i.e. mucinous ascites); however, recognition and proper classification of these neoplasms can be difficult despite established diagnostic criteria.ObjectiveTo determine the pathological diagnostic concordance for appendix neoplasia and related lesions during patient referral to an academic medical center specialized in treating patients with PMP.DesignThe anatomic pathology laboratory information system was searched to identify cases over a two-year period containing appendix specimens with mucinous neoplasia evaluated by an outside pathology group and by in-house slide review at a single large academic medical center during patient referral.Results161 cases containing appendix specimens were identified over this period. Forty-six of 161 cases (28.6%) contained appendiceal primary neoplasia or lesions. Of these, the originating pathologist diagnosed 23 cases (50%) as adenocarcinoma and 23 cases (50%) as LAMN; however, the reference pathologist diagnosed 29 cases (63.0%) as LAMN, 13 cases (28.3%) as adenocarcinoma, and 4 cases (8.7%) as ruptured simple mucocele. Importantly, for cases in which the originating pathologist rendered a diagnosis of adenocarcinoma, the reference pathologist rendered a diagnosis of adenocarcinoma (56.5%, 13 of 23), LAMN (39.1%, 9 of 23), or simple mucocele (4.3%, 1 of 23). The overall diagnostic concordance rate for these major classifications was 71.7% (33 of 46) with an unweighted observed kappa value of 0.48 (95% CI, 0.27-0.69), consistent with moderate interobserver agreement. All of the observed discordance (28.3%) for major classifications could be attributed to over-interpretation. In addition, the majority of LAMN cases (65.5%) had potential diagnostic deficiencies including over-interpretation as adenocarcinoma and lacking or discordant risk stratification (i.e. documentation of extra-appendiceal neoplastic epithelium).ConclusionsAppendiceal mucinous lesions remain a difficult area for appropriate pathological classification with substantial discordance due to over-interpretation in this study. The findings highlight the critical need for recognition and application of diagnostic criteria regarding these tumors. Recently published consensus guidelines and a checklist provided herein may help facilitate improvement of diagnostic concordance and thereby reduce over-interpretation and potential overtreatment. Further studies are needed to determine the extent of this phenomenon and its potential clinical impact.

For maintaining collaboration and coordination among emergency department (ED) caregivers, it is essential to effectively share patient-centered information. Indirect activities on patients, such as searching for laboratory results and sharing information with scattered colleagues, waste resources to the detriment of patients and staff. Therefore, we conducted a pilot study to evaluate the initial efficacy of a mobile app to facilitate rapid mobile access to central laboratory results and remote interprofessional communication. A total of 10 ED residents and registered nurses were randomized regarding the use of the app versus conventional methods during semi-simulated scenarios in a pediatric ED (PED). The primary outcome was the elapsed time in minutes in each group from the availability of laboratory results to their consideration by participants. The secondary outcome was the elapsed time to find a colleague upon request. Time to consider laboratory results was significantly reduced from 23 min (IQR 10.5–49.0) to 1 min (IQR 0–5.0) with the use of the app compared to conventional methods (92.2% reduction in mean times, p = 0.0079). Time to find a colleague was reduced from 24 min to 1 min (i.e., 93.0% reduction). Dedicated mobile apps have the potential to improve information sharing and remote communication in emergency care. [ABSTRACT FROM AUTHOR]

People are increasingly accessing their own laboratory (lab) results online. However, Canadians may be expected to use different systems to access their results, depending upon where they are tested (e.g., community lab vs. hospital), and these results may be displayed differently. This study examined the extent to which participants without medical expertise (N = 25) made errors identifying lab results (i.e., missing or misidentifying abnormal results) in a mock report. Six participants overlooked each of the flagged values, 20 participants missed an abnormal result that was not flagged, and 2 participants mis-identified a normal value as out of range. We describe potential causes of these errors and the implications for the design of consumer-facing lab results. [ABSTRACT FROM AUTHOR]

Hospital laboratory results are a significant data source in Clinical Data Ware-houses (CDW). To ensure comparability across healthcare organizations and for use in research studies, the results need to be interoperable. The LOINC (Logical Observation Identifiers, Names, and Codes) terminology provides a unique identifier for local codes for lab tests, enabling interoperability. However, in real-world, events occur over time and can disrupt the distribution of lab result values. For example, new equipment may be added to the analysis pipeline, a machine may be replaced, formulas may evolve due to new scientific knowledge, and legacy terminologies may be adopted. This article proposes a pipeline for creating an automated dashboard to monitor these events and data quality. We used automatic change point detection methods such as PELT for event detection in lab results. For a given LOINC code, we create a dashboard that summarizes the number of local codes mapped, and the number of patients (by sex, age, and hospital service) associated with the code. Finally, the dashboard enables the visualization of time events that disrupt the signal distribution. The biologists were able to explain to us the changes for several biological assays.

Background: Direct access of patients to their web-based patient portal, including laboratory test results, has become increasingly common. Numeric laboratory results can be challenging to interpret for patients, which may lead to anxiety, confusion, and unnecessary doctor consultations. Laboratory results can be presented in different formats, but there is limited evidence regarding how these presentation formats impact patients' processing of the information., Objective: This study aims to synthesize the evidence on effective formats for presenting numeric laboratory test results with a focus on outcomes related to patients' information processing, including affective perception, perceived magnitude, cognitive perception, perception of communication, decision, action, and memory., Methods: The search was conducted in 3 databases (PubMed, Web of Science, and Embase) from inception until May 31, 2023. We included quantitative, qualitative, and mixed methods articles describing or comparing formats for presenting diagnostic laboratory test results to patients. Two reviewers independently extracted and synthesized the characteristics of the articles and presentation formats used. The quality of the included articles was assessed by 2 independent reviewers using the Mixed Methods Appraisal Tool., Results: A total of 18 studies were included, which were heterogeneous in terms of study design and primary outcomes used. The quality of the articles ranged from poor to excellent. Most studies (n=16, 89%) used mock test results. The most frequently used presentation formats were numerical values with reference ranges (n=12), horizontal line bars with colored blocks (n=12), or a combination of horizontal line bars with numerical values (n=8). All studies examined perception as an outcome, while action and memory were studied in 1 and 3 articles, respectively. In general, participants' satisfaction and usability were the highest when test results were presented using horizontal line bars with colored blocks. Adding reference ranges or personalized information (eg, goal ranges) further increased participants' perception. Additionally, horizontal line bars significantly decreased participants' tendency to search for information or to contact their physician, compared with numerical values with reference ranges., Conclusions: In this review, we synthesized available evidence on effective presentation formats for laboratory test results. The use of horizontal line bars with reference ranges or personalized goal ranges increased participants' cognitive perception and perception of communication while decreasing participants' tendency to contact their physicians. Action and memory were less frequently studied, so no conclusion could be drawn about a single preferred format regarding these outcomes. Therefore, the use of horizontal line bars with reference ranges or personalized goal ranges is recommended to enhance patients' information processing of laboratory test results. Further research should focus on real-life settings and diverse presentation formats in combination with outcomes related to patients' information processing., (©Frederieke A M van der Mee, Fleur Schaper, Jesse Jansen, Judith A P Bons, Steven J R Meex, Jochen W L Cals. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.08.2024.)

Objective: Digital pathology is an opportunity to revise the routine and old artisanal workflow, moving to standard operating procedures, quality control and reproducibility. Here the results of a survey promoted by the Coordinamento della Medicina di Laboratorio (CRC Med Lab) of the Lombardy region in Italy are reported to shed light on the current situation of digital adoption in the country., Methods: The survey composed of 58 questions was sent to 60 pathology laboratories. The results were collected and most significant answers were reported and discussed., Results: Answers were received from 57 (95%) laboratories, a minority organized in spoke-hub networks (16%) with a centralized processing phase (11%). Hybrid manual/computer-assisted traceability was prevalent (36%), with QR/barcode labeling starting within the pathology lab (23%). Different laboratory information systems (LIS) were employed, mostly with alert functions and/or multimedial file attachments (56% and 46%, respectively). The majority opted for a semi-automated tracking management (44, 77%) and 18 centers (32%) were partly digitizing the routine (¾ scanning < 25% of slides). Whole slide images were retained for 3.7 years in average; in-house blocks/slides archiving was still preferred (30, 53%), with 1838 (±1551) and 1798 (±1950) days (5 years) internal permanence for blocks and slides that are stored in out-source (mean turnaround time for return on-demand 3.7±2.1, range 1-10 days)., Conclusions: The advantages of digital pathology must be balanced against the challenges faced in the structural revision of the pathology workflow. This regional scouting can represent the foundation to build an efficient and connected digital pathology system in the territory., (Copyright © 2024 Società Italiana di Anatomia Patologica e Citopatologia Diagnostica, Divisione Italiana della International Academy of Pathology.)

Introduction: Tuberculosis remains a public health problem despite all the efforts made to eradicate it. To strengthen the surveillance system for this condition, it is necessary to have a good data management system. Indeed, the use of electronic information systems in data management can improve the quality of data. The objective of this project was to set up a laboratory-specific electronic information system for Mycobacteria and Atypical Tuberculosis. Methods: The design of this laboratory information system required a general understanding of the workflow and the implementation processes in order to generate a realistic model. For the implementation of the system, Java technology was used to develop a web application compatible with the intranet of the company. The impact and the acceptability of the use of the system on the running of the laboratory were evaluated using Likert scale. Results: The system in place has been in operation for about 12 months, in conjunction with the paper registers. Since then, 4811 requests for examinations concerning 6083 samples have been registered. The results of analysis of 3892 patients were printed from the Laboratory information system. In order to produce tuberculosis drug resistance reports and laboratory performance reports, dashboards have been developed. Conclusion: The system has been adopted by the staff because of the time and efficiency gained in managing laboratory data. However, obtaining an optimized tool will only be done in a cycle of sustained improvement.

Introduction: An appropriate management of anaemia laboratory tests is crucial for a correct diagnosis and treatment. A non-sequential “shotgun” approach (where every anaemia related test is ordered) causes workload and cost increases and could be potentially harmful. We have implemented a Decision Support System through our laboratory information system (LIMS) based on reflexive algorithms and automatic generation of interpretative reports specifically in diagnosis of anaemia for primary care patients. Materials and methods: When a request contained an “Anaemia Suspicion Study” profile, more than twenty automatic reflexive rules were activated in our LIMS based upon laboratory results. These rules normally involved the addition of reflexive tests. A final report was automatically generated for each interpretation which was always reviewed for their validity by two staff pathologists. We measured the impact of this system in the ordering of most common anaemia related tests and if a proper treatment was established based on the interpretive report. Results: From all the studies performed, only 12% were positive being “iron deficiency” and “anaemia of chronic disease” the most frequent causes, 62% and 17%, respectively. Proper treatment was established in 88% of these anaemic patients. Total iron, transferrin, ferritin, folate and vitamin B12 demand decreased substantially after implementation representing a cost reduction of 40% only for these five tests. Conclusions: Our system has easily improved patient outcomes, advising on individual clinical cases. We have also noticeably reduced the number of over-requested tests and laboratory costs. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) remains a significant global health challenge. Indeed, according to the World Health Organization (WHO), TB is classified as the second most common cause of death worldwide due to a single infectious agent in 2022, following COVID-19. To effectively manage tuberculosis patients, it is necessary to ensure accurate diagnosis, prompt treatment initiation, and vigilant monitoring of patients' progress. In 2017, the TB Ge network was implemented and launched in two primary hospitals within the Liguria Region in Italy, with the main purpose to manage tuberculosis infections. This system, organized as a web-based tool, simplifies the manual input of patient's data and therapies, while automating the integration of test results from hospitals' Laboratory Information Systems (LIS), without requiring human intervention. The goal of this paper is to highlight the outcomes achieved through the implementation of the TB Ge network in a period seriously affected by the COVID-19 pandemia and outline future directions. More specifically, the aim is to extend its adoption to all hospitals in the Liguria Region, thus improving the management of tuberculosis infections across healthcare facilities.

UnlabelledWorkflow Information Storage Toolkit (WIST) is a set of application programming interfaces and web applications that allow for the rapid development of customized laboratory information management systems (LIMS). WIST provides common LIMS input components, and allows them to be arranged and configured using a flexible language that specifies each component's visual and semantic characteristics. WIST includes a complete set of web applications for adding, editing and viewing data, as well as a powerful setup tool that can build new LIMS modules by analyzing existing database schema.Availability and implementationWIST is implemented in Perl and may be obtained from http://vimss.sf.net under the BSD license.

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Introduction: Rapid laboratory glucose testing assists prompt on-site treatment for abnormal glycaemic episodes. New generation Point-of-Care Testing (POCT) for whole blood glucose analysis have high sensitivity and short processing time, which is competent for on-site rapid glucose testing. Aim: To assess the accuracy and Turn Around Time (TAT) of the POCT (Rightest GM700 Pro) compared with the Central Laboratory Testing (CLT) at a National Level, Urban Hospital. Materials and Methods: A retrospective study of 1,812 patients was conducted for glucose testing at the Laboratory Department of Cathay General Hospital from November 2016 to November 2017. Consistency between GM700 Pro and Beckman Coulter AU680, used as CLT, was analysed. TAT was measured from phlebotomy to result availability in Laboratory information system (LIS). Two widely accepted standards for blood glucose meters ISO 15197:2013 (for self-monitoring) and USFDA Prescription Point-of-Care Use (for hospital use) were adopted to evaluate the accuracy. Pearson’s correlation and Passing-Bablok regression were used for the analysis. BlandAltman analysis was used to determine the agreement between POCT and CLT glucose results. Results: Linear regression analysis of GM700 Pro showed significant agreement (y=0.97×-0.89, r2 =0.99) with CLT. Results of TAT indicated that POCT generated glucose report for clinical decision-making was 7 times faster than CLT (p

Background: The Ministry of Health in Côte d'Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President's Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation., Objective: This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment., Methods: This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS., Results: There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels., Conclusions: These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d'Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems., (©Yao He, Yves-Rolland Kouabenan, Paul Henri Assoa, Nancy Puttkammer, Bradley H Wagenaar, Hong Xiao, Stephen Gloyd, Noah G Hoffman, Pascal Komena, N'zi Pierre Fourier Kamelan, Casey Iiams-Hauser, Adama Sanogo Pongathie, Alain Kouakou, Jan Flowers, Nadine Abiola, Natacha Kohemun, Jean-Bernard Amani, Christiane Adje-Toure, Lucy A Perrone. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.03.2024.)

Objectives: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Its diagnosis poses significant challenges especially at early stages and in atypical cases. The aim of this study was to develop a machine learning model based on common laboratory tests that can aid SLE diagnosis., Methods: A standard protocol was developed to collect data of SLE and control immune diseases. A 10-fold cross-validation was performed in the modeling dataset (n=862), and an external dataset (n=198) was used for model validation. Machine learning algorithms were applied to construct a diagnostic model. Performance was evaluated based on area under the curve (AUC) values, F1-score, negative predictive value, positive predictive value, accuracy, sensitivity, and specificity., Results: The optimal model was based on a random forest algorithm with 10 clinical features. Thrombin time, prothrombin activity, and uric acid contributed most to the diagnostic model. The SLE diagnostic model showed sufficient predictive accuracy, with AUC values of 0.8286 in the validation dataset., Conclusions: Our diagnostic model based on 10 common laboratory tests identified the patients with SLE with high accuracy. An online version of the model can potentially be applied in clinical settings for the differential diagnosis of SLE.

Molecular microbiology assays have a higher cost of testing compared to traditional methods and need to be utilized appropriately. Results from these assays may also require interpretation and appropriate follow-up. Electronic tools available in the electronic health record and laboratory information system can be deployed both preanalytically and postanalytically to influence ordering behaviors and positively impact diagnostic stewardship. Next generation technologies, such as machine learning and artificial intelligence, have the potential to expand upon the capabilities currently available and warrant additional study and development but also require regulation around their use in health care., Competing Interests: Disclosure M.W. Starolis discloses that she is a full-time employee and stockholder of Quest Diagnostics. M.W. Starolis is an elected council member of the Pan American Society of Clinical Virology (PASCV), and chair of the PASCV Clinical Practice Committee. M.W. Starolis has served as an unpaid advisor to Roche and Bio-Rad. R.M. Liesman is a member of the PASCV Clinical Practice Committee. M.A. Zaydman has received speaking honoraria from Siemens and Sebia and speaking honoraria with travel support from the Association for Diagnostic and Laboratory Medicine (ADLM) and the Association of Pathology Informatics. M.A. Zaydman serves as a committee member on the ADLM Data Analytics Steering Committee. M.A. Zaydman received research support from bioMérieux. M.A. Zaydman holds provisional patents, US 20210311046 A1 and US2022/071184., (Copyright © 2023 Elsevier Inc. All rights reserved.)

As Rwanda approaches the UNAIDS Fast Track goals which recommend that 95% of HIV-infected individuals know their status, of whom 95% should receive treatment and 95% of those on treatment achieve viral suppression, the country currently relies on an inefficient paper, and disjointed electronic, systems for case-based surveillance (CBS). Rwanda has established an ecosystem of interoperable systems based on open standards to support HIV CBS. Data were successfully exchanged between an EMR, a client registry, laboratory information system and DHIS-2 Tracker, and subsequently, a complete analytic dataset was ingested into MS-Power Business Intelligence (MS-PowerBI) for analytics and visualization of the CBS data. Existing challenges included inadequate workforce capacity to support mapping of data elements to HL7 FHIR resources. Interoperability optimization to support CBS is work in progress and rigorous evaluations on the effect on health information exchange on monitoring patient outcomes are needed.

The final, post-analytical, phase of laboratory testing is increasingly recognized as a fundamental step in maximizing quality and effectiveness of laboratory information. There is a need to close the loop of the total testing cycle by improving upon the laboratory report, and its notification to users. The harmonization of the post-analytical phase is somewhat complicated, mainly because it calls for communication that involves parties speaking different languages, including laboratorians, physicians, information technology specialists, and patients. Recently, increasing interest has been expressed in integrated diagnostics, defined as convergence of imaging, pathology, and laboratory tests with advanced information technology (IT). In particular, a common laboratory, radiology and pathology diagnostic reporting system that integrates text, sentinel images and molecular diagnostic data to an integrated, coherent interpretation enhances management decisions and improves quality of care., (© 2024 the author(s), published by De Gruyter, Berlin/Boston.)

Rationale, aims, and objectives: Laboratory information sub‐systems play an important role in diagnosis and treatment of patients. This study aimed to determine functional requirements of users and assess the existence of these requirements in the laboratory information system. Method: This descriptive cross‐sectional study was conducted in 2016 in two phases. The first phase was done through three stages. First, based on an unsystematic review of related literature, an outline of functional laboratory information system requirements was identified. In the second stage, these requirements were identified in group meetings in the form of a semi‐structured questionnaire and given to experts. Then, modified Delphi technique was used to reach agreement on each item. Then, based on experts' comments, the final version of the questionnaire was presented including 61 closed‐ended items using Likert scale and an open‐ended item. It was surveyed by 50 experts using Delphi technique. Responses were scored, and the requirements whose mean final score was 3 and above were finally confirmed. In the second phase, based on the confirmed requirements, a checklist comprising 68 requirements was prepared and adopted hospital information systems were evaluated through researcher observation. Data were analysed using descriptive statistics. Results: The final list of functional laboratory information system requirements was prepared with 68 items. The results of the evaluation revealed that confirmed requirements existed in 58.8% of hospital information systems. Conclusion: Laboratory information system requirements were designed with 68 items. Evaluation results showed that the systems were moderate in terms of compliance with the requirements. [ABSTRACT FROM AUTHOR]

Purpose. Patient portals of electronic health record systems currently present patients with tables of laboratory test results, but visual displays can increase patient understanding and sensitivity to result variations. We sought to assess physician preferences and concerns about visual display designs as potential motivators or barriers to their implementation. Methods. In an online survey, 327 primary care physicians (>50% patient care time) recruited through the online e-community/survey research firm SERMO compared hemoglobin A1c (HbA1c) test results presented in table format to various visual displays (number line formats) previously tested in public samples. Half of participants also compared additional visual formats displaying target goal ranges. Outcome measures included preferred display format and whether any displays were unacceptable, would change physician workload, or would induce liability concerns. Results. Most (85%–89%) respondents preferred visual displays over tables for result communications both to patients tested for diagnosis purposes and to diagnosed patients, with a design with color-coded categories most preferred. However, for each format (including tables), 11% to 23% rated them as unacceptable. Most respondents also preferred adding goal range information (in addition to standard ranges) for diagnosed patients. While most physicians anticipated no workload changes, 19% to 32% anticipated increased physician workload while 9% to 28% anticipated decreased workload. Between 32% and 40% had at least some liability concerns. Conclusions. Most primary care physicians prefer visual displays of HbA1c test results over table formats when communicating results to patients. However, workload and liability concerns from a minority of physicians represent a barrier for adoption of such designs in clinical settings. [ABSTRACT FROM AUTHOR]

Background Hypernatraemia is a surrogate marker of morbidity and mortality, particularly in the older person.(1) Met Eireann defines a heatwave as 5 consecutive days >25°C. HSE guidelines outline preventative strategies for community-dwelling adults and inpatients during heatwaves.(2) Our objective was to compare the prevalence of hypernatraemia (Na>145mmol/l), in biochemical samples during the heatwave of 2018 to the same period in 2017 Methods A retrospective cross-sectional study using patient demographics, biochemical data from Laboratory Information System and meteorological data from Met Éireann was performed. A ten-day period from 24thJune to 3rdJuly was assessed in 2017 and 2018. Patients aged >65 with at least one biochemical sample were included. Only the first sample from each patient was included. Predictor variables of age, gender and source of sample were measured. Results Maximum air temperatures were higher in 2018 than 2017 (mean 27 v 16.8°C, p<0.0001). Hypernatraemia had 3.6% prevalence (66/1840 samples) during the heatwave of 2018 in comparison to 1.4% prevalence (23/1593 samples) in 2017. This corresponds to a prevalence ratio of 2.5 in heatwave 2018 compared with 2017. In 2018 hypernatraemic samples: 56%(n=37) were male, mean age was 75 with 71(n=47) General Practitioner(GP) samples,12%(n=8) inpatients and 17%(n=11) from outpatient department(OPD). In 2017 hypernatraemic samples: 30%(n=7) were male, mean age was 75 and 74%(n=17) were GP samples,17%(n=4) were inpatients, 9%(n=2) from OPD. The sources of total samples (regardless of Na level) were 63% GP, 7% inpatients and 30% outpatients. Conclusion Hypernatraemia was 2.5 times more prevalent during the heatwave in 2018 than the previous year in patients aged over 65. Hypernatraemia is more prevalent in GP and inpatients taking into account the usual distribution of samples by source. Current guidelines are either not being adhered to or ineffective, a matter which merits further evaluation. [ABSTRACT FROM AUTHOR]

Hemoglobin A1c (HbA1c) is a long-term measure for glucose concentration in plasma. Since its introduction as a diabetes monitoring tool, and its more recent application as a diagnostic tool, the number of measurements of HbA1c have risen dramatically. However, HbA1c change is slow, so repeating measurements should not be done too often. We use a large, unfiltered dataset from 52,017 patients to determine the possible rate of change in HbA1c concentration. In our laboratory, the critical difference between HbA1c measurements is 8.5%. Our data show that a 1-unit HbA1c rise takes 4 weeks to occur, hence, at a HbA1c concentration around 50 mmol/mol Hgb, a critically increased HbA1c concentration cannot be determined until after 16 weeks. Conversely a critically lower HbA1c can manifest itself after 2 weeks, but after 7 weeks the dropping tendency stops. The amount of measurements that can be cancelled because they were taken sooner than 16 weeks is 23 percent. [ABSTRACT FROM AUTHOR]

Neonatal screening and ongoing follow-up of children with sickle cell disease are essential to reduce the mortality caused by this disease. To ensure care continuity, it is essential to include in the patient's record the history and details of biological tests. Thus, it is necessary to provide a Laboratory Information System for electronic management of biological test prescription and results, and the laboratory system must integrate well with Health Information Systems. In this paper, we propose a Laboratory Information System for the management of biological tests for the neonatal screening and healthcare of sickle cell disease in Senegal. [ABSTRACT FROM AUTHOR]

People are increasingly able to access their laboratory results via patient portals. The potential benefits provided by such access, such as reductions in patient burden and improvements in patient satisfaction, disease management, and medical decision making, also come with potentially valid concerns about such results causing confusion or anxiety among patients. However, it is possible to clearly convey the meaning of results and, when needed, indicate required action by designing systems to present laboratory results adapted to the people who will use them. Systems should support people in converting the potentially meaningless data of results into meaningful information and actionable knowledge. We offer 10 recommendations toward this goal: (1) whenever possible, provide a clear takeaway message for each result. (2) Signal whether differences are meaningful or not. (3) When feasible, provide thresholds for concern and action. (4) Individualize the frame of reference by allowing custom reference ranges. (5) Ensure the system is accessible. (6) Provide conversion tools along with results. (7) Design in collaboration with users. (8) Design for both new and experienced users. (9) Make it easy for people use the data as they wish. (10) Collaborate with experts from relevant fields. Using these 10 methods and strategies renders access to laboratory results into meaningful and actionable communication. In this way, laboratories and medical systems can support patients and families in understanding and using their laboratory results to manage their health. [ABSTRACT FROM AUTHOR]

Many point-of-care laboratory tests are manually entered into the electronic health record by ambulatory clinic staff, but the rate of manual transcription error for this testing is poorly characterized. Using a dataset arising from a duplicated workflow that created a set of paired interfaced and manually entered point-of-care glucose measurements, we found that 260 of 6930 (3.7%) manual entries were discrepant from their interfaced result. Thirty-seven of the 260 (14.2%) errors were discrepant by more than 20% and included potentially dangerous mistranscriptions. An additional 37 (14.2%) errors were due to inclusion of non-numeric characters. Staff-entered result flags deviated from the result flag generated in the laboratory information system in 5121 of 6930 (73.9%) pairs. These data demonstrate that clinically significant discrepancies for clinic-entered point of care results occurred at a rate of approximately 5 per 1000 results and they underline the importance of interfacing instruments when feasible. [ABSTRACT FROM AUTHOR]

Background: A common challenge in the development of laboratory clinical decision support (CDS) and laboratory utilization management (UM) initiatives stems from the fact that many laboratory tests have multiple potential indications, limiting the ability to develop context-specific alerts. As a potential solution, we designed a CDS alert that asks the ordering clinician to provide the indication for testing, using D-dimer as an exemplar. Using data collected over a nearly 3-year period, we sought to determine whether the indication capture was a useful feature within the CDS alert and whether it provided actionable intelligence to guide the development of an UM strategy. Methods: We extracted results and ordering data for D-dimer testing performed in our laboratory over a 35-month period. We analyzed order patterns by clinical indication, hospital service, and length of hospitalization. Results: Our final data set included 13,971 result-order combinations and indeed provided actionable intelligence regarding test utilization patterns. For example, pulmonary embolism was the most common emergency department indication (86%), while disseminated intravascular coagulation was the most common inpatient indication (56%). D-dimer positivity rates increased with the duration of hospitalization and our data suggested limited utility for ordering this test in the setting of suspected venous thromboembolic disease in admitted patients. In addition, we found that D-dimer was ordered for unexpected indications including the assessment of stroke, dissection, and extracorporeal membrane oxygenation. Conclusions: Indication capture within a CDS alert and correlation with result data can provide insight into order patterns which can be used to develop future CDS strategies to guide appropriate test use by clinical indication. [ABSTRACT FROM AUTHOR]