Current Data Collection Research Articles

Usage of IoT Devices as Progressive Technology in the Era of Digitization: Case Study

This article deals with implementing an IoT approach based on a case study with an emphasis on current data collection concepts and expanding automated workplaces’ functionality. As part of this, the article describes the issues and advantages of IO-Link technology as part of the introduction of the emerging digitization all around us. Part of the presented solution is the direct configuration and diagnostic functions of IO-Link sensors and IO-Link master, which are applied to the FMS 500 modular laboratory system. The proposed case study proves the complexity and compatibility of individual modules, and its goal is to demonstrate the feasibility of practical requirements, research, and teaching in Industry 4.0 standards. Additionally, test experiments have shown the suitability of deploying such concepts in global diagnostics and predictive maintenance environments.

Antimicrobial Resistance Surveillance Methods in Bangladesh: Present and Way Forward.

The Institute of Epidemiology, Disease Control and Research (IEDCR) conducts active, case-based national antimicrobial resistance (AMR) surveillance in Bangladesh. The Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project accessed aggregated retrospective data from non-IEDCR study sites and 9 IEDCR sites to understand the pattern and extent of AMR and to use analyzed data to guide ongoing and future national AMR surveillance in both public and private laboratories. Record-keeping practices, data completeness, quality control, and antimicrobial susceptibility test practices were investigated in all laboratories participating in case-based IEDCR surveillance and laboratory-based CAPTURA sites. All 9 IEDCR laboratories recorded detailed case-based data (n = 16 816) in electronic format for a priority subset of processed laboratory samples. In contrast, most CAPTURA sites (n = 18/33 [54.5%]) used handwritten registers to store data. The CAPTURA sites were characterized by fewer recorded variables (such as patient demographics, clinical history, and laboratory findings) with 1 020 197 individual data, less integration of patient records with the laboratory information system, and nonuniform practice of data recording; however, data were collected from all available clinical samples. The analyses conducted on AMR data collected by IEDCR and CAPTURA in Bangladesh provide current data collection status and highlight opportunities to improve ongoing data collection to strengthen current AMR surveillance system initiatives. We recommend a tailored approach to conduct AMR surveillance in high-burden, resource-limited settings.

Forensic anthropologists and estimates of skeletal completeness: The impacts of training and experience

Forensic anthropologists engage with numerous and diverse stakeholders in their casework. Regarding the recovery of human remains, these stakeholders may be interested in quantifying or qualifying the amount of remains recovered. How forensic anthropologists respond to such questions, whether verbally or in written reporting, has the potential to impact the trajectory of a case. However, communications about skeletal completeness are rarely discussed within the field. Current data-collection procedures recommend the use of inventories. This approach may be less feasible for complicated assemblages involving commingling or high degrees of fragmentation. Numerous methods exist to quantify the amount of skeletal remains present in complex or larger assemblages, but it remains unclear to what extent forensic anthropologists utilize these methods and whether factors like degree of expertise influence analysts’ ability to report skeletal completeness consistently and precisely.A study was designed to examine differences between public and professional perceptions of skeletal completeness, presenting images of incomplete bones and skeletal remains. Survey participants were asked to assess the completeness of the remains in each image. Few patterns were observed regarding photographs of skeletal assemblages, but distinct differences were observed among individual bones between respondents with different degrees of expertise. These responses reflect potentially unexamined assumptions underlying assessments of incomplete bones and skeletal assemblages. This highlights the necessity of standardizing how we report estimates of completeness within the forensic anthropology community and how we discuss these results with external stakeholders. Completeness estimates must be either removed from reports and bench notes or annotated and cited clearly, as is standard with other aspects of forensic anthropological analysis. Several methods are summarized, with recommendations for integrating them into casework.

Improving Accuracy of Sensor Data by Frequent Pattern Mining Algorithm Using Edge Computing

Sensor data plays a crucial role in various applications, including industrial automation, environmental monitoring, and healthcare. However, the accuracy of sensor data can be adversely affected by factors such as noise, latency, and data transmission issues in existing systems. This study focuses on identifying the disadvantages associated with current sensor data collection and analysis methods and explores the use of frequent pattern mining to enhance data accuracy. The research presents a comprehensive overview of Edge computing in conjunction with sensor systems and the Internet of Things, highlighting the complexities in processing sensor data using conventional methods and the advantages of employing frequent pattern mining. The study concludes that the utilization of frequent pattern mining in edge sensor data processing offers optimized response time, resource utilization, and better scalability. It is also capable of handling the massive amount of data generated from sensors and mobile devices in the Internet of Things.

PSIX-24 Social Trust in a Small Dairy Farmer Organization in Southeast Brazil

Abstract The objective of this study was to analyze the social trust in a group of dairy farmers in the State of São Paulo, Brazil. The related Association of Dairy Producers (ADP) is like most small rural organizations present in Brazil that emerged to meet the public policies. Current assessment had three stages: a) identifying producers; b) applying the surveys; and c) data analyses. The producer association was unable to provide some basic information about its members (such as phone number), which signals a lack of trust. To identify the ADP members, it was necessary to visit the milking parlor expansion tanks to find such contact. Another situation reinforced the first impression regarding the lack of social trust: an ADP member did not authorize the access to to the research conduct the surveys for the members that used the expansion tank installed on his land. The surveys were then conducted at four out of five locations where expansion tanks were installed. Among the ADP members surveyed, 68.75% answered the survey. Approximately 82% of respondents indicated caution when dealing people in general (inside or outside the ADP). Although there was an indication of lack of social trust, 54.4% of producers trusted entirely the ADP; 22.7% partially trusted; 13.6% were indifferent; 4.5% had low trust, and 4.5% did not trust. When voluntary participation in decision in the association activities was questioned, 68.2% of the surveyed members answered “actively participate”, 31.8% “participate without actions,” and none of the surveyed members admitted no participation. Approximately 82% of the surveyed members had a positive perception of the association, while 18% believed it was not properly managed and inferred no longer assist with it in the future. A greater participation in the association activities may have not being observed due to the fact that current association was transitioning into a cooperative business model at the time of current data collection. For 18.25% of the members, the two main causes of the distrust in the recently created agricultural cooperative was related to: a) the requirement to obligatory become a member; and b) the delay in the construction completion of the dairy processing plant. The results suggest that producers show signs of general social distrust, indicated by concerns regarding the advantages, disadvantages, or even the risks associated with becoming members of the agricultural cooperative. Nonetheless, the vast majority of producer members trusted in the association. Further assessment is warranted to investigate if the source of general social mistrust observed erupted from internal (local community) or external (city, state, and federal public policies) venues of the society.

A Synthetic Integrated Wireless Aerodynamic Evaluation System for Train–Bridge System

The development of high-speed railway networks and the increased running speeds of high-speed trains (HSTs) have made the aerodynamic interference between HSTs and their surrounding environments increasingly important. Compared with a traditional wind tunnel test, systematically understanding the aerodynamic characteristics of HSTs involves relatively more stringent requirements, highlighting the need to develop experimental methods and technologies with enhanced dynamic performance. Central South University (CSU) developed a wireless data acquisition system, named as the in-model sensory and wireless data acquisition — remote control and processing system (ISWDA-RCPS), which can operate onboard a novel moving train and infrastructure rig. The system was developed to meet current wind tunnel data collection needs, and it avoids the physical cables used in conventional devices, which are extremely susceptible to induced noise. The system accepts inputs from various sensors and transfers the data wirelessly to an access point outside a wind tunnel’s test section. To analyze the feasibility of the ISWDA-RCPS concerning its sensing capabilities and wireless communications, we conduct experiments in multiple operating conditions. Finally, pressure measurements are acquired from a moving Fuxing HST model at different points and used to analyze the aerodynamic behavior of the model.

Occupation and Industry Data Quality Among Select Notifiable Conditions in Washington State.

Occupation and industry are basic data elements that, when collected during public health investigations, can be key to understanding patterns of disease transmission and developing effective prevention measures. To assess the completeness and quality of occupation and industry data among select notifiable conditions in Washington and discuss potential improvements to current data collection efforts. We evaluated occupation and industry data, collected by local health departments during routine case investigations, for 11 notifiable conditions, selected for inclusion based on an established or plausible link to occupational exposure. Confirmed cases of select notifiable conditions among Washington residents aged 16 to 64 years, for years 2019-2021. We calculated the percentage of cases among working-age adults reported as employed, the percentage with occupation and industry data collected, and the percentage assigned standard occupation and industry codes. We identified the most common responses for occupation and industry and challenges of assigning codes to those responses. Among the 11 conditions evaluated, one-third of cases aged 16 to 64 years were reported as employed. Among the cases reported as employed, 91.5% reported occupation data and 30.5% reported industry data. "Self-employed" was among the top responses for occupation, a response that does not describe a specific job and could not be assigned an occupation code. In the absence of additional information, 4 of the most common responses for industry could not be coded: "health care," "technology," "tech," and "food." Routine collection of informative occupation and industry data among working-age adults is largely absent from case investigations in Washington. Methods of data collection that improve quality while minimizing the burden of collection should be pursued. Suggestions for improving data quality are discussed.

A Latent-Factor-Model-Based Approach for Traffic Data Imputation with Road Network Information

With the rapid development of the economy, car ownership has grown rapidly, which causes many traffic problems. In recent years, intelligent transportation systems have been used to solve various traffic problems. To achieve effective and efficient traffic management, intelligent transportation systems need a large amount of complete traffic data. However, the current traffic data collection methods result in different forms of missing data. In the last twenty years, although many approaches have been proposed to impute missing data based on different mechanisms, these all have their limitations, which leads to low imputation accuracy, especially when the collected traffic data have a large amount of missing values. To this end, this paper proposes a latent-factor-model-based approach to impute the missing traffic data. In the proposed approach, the spatial information of the road network is first combined with the spatiotemporal matrix of the original traffic data. Then, the latent-factor-model-based algorithm is employed to impute the missing data in the combined matrix of the traffic data. Based on the real traffic data from METR-LA, we found that the imputation accuracy of the proposed approach was better than that of most of the current traffic-data-imputation approaches, especially when the original traffic data are limited.

Evaluasi Kelayakan Finansial Usaha Kerupuk Rambak Di Kecamatan Rambah Hilir Kabupaten Rokan Hulu

Evaluation of business feasibility is needed to get an idea of ​​whether it is feasible or not, in running a rambak cracker business, almost all business actors do not apply bookkeeping in their business finances, so they do not know how much the expenses and income are in their business. This research was conducted with the aim of knowing the production techniques, income, and financial feasibility of the rambak crackers processing business. This research was carried out from August 2022 to February 2022. The sampling technique was a saturated sample in the form of a rambak cracker processing business in Hilir District. The current data collection method used was direct interviews and observations at the place of business. The results showed that the rambak cracker production techniques included tool preparation, seasoning refining, mixing, molding, boiling, cutting, drying to packaging, the rambak cracker processing business was declared feasible with a Net Present Value of 126.301.605 which is positive (NPV> 0) Internal The Rate OF Return (IRR) is 56,00% where the IRR value is greater than the applicable discount rate, which is 8.30%, Net B/C is 2,9503 where (Net B/C> 1), Payback Period (PP) is 1 Year 5 Months 27 Days, and Break Even Point (BEP) 3 Year 8 Months 9 Days. All results analyzed with investment criteria stated that the rambak cracker business in Rambah Hilir District was feasible to run.

Development of a semi-open chamber system for the gas exchange measurement of whole-canopy under steady and unsteady states in cucumber seedlings

BackgroundLarge-scale data on the photosynthetic characteristics of whole crop canopy is crucial for improving yield. However, current data collection methods remain challenging, and the time constraints associated with photosynthetic data collection further complicate matters. Developing a practical yet easy-to-use tool for collecting whole-canopy data is essential to address these challenges. Furthermore, it is necessary to obtain instantaneous measurements of photosynthetic rate over a wide range of CO2 concentrations under an unsteady state to enable faster data collection and obtain reliable biochemical limits of carbon assimilation. This study developed a semi-open chamber system with steady and unsteady state measurement techniques to collect biochemical photosynthetic data from an entire cucumber canopy, emphasizing the correction procedures for CO2 concentration of unsteady state measurements applicable regardless of chamber scale.ResultsAfter constructing a semi-open chamber system, we described how to correct measurement errors according to chamber volume. In order to assess the accuracy of the newly developed system, an analysis was conducted to determine the overall measurement error resulting from variations in the reference, sample CO2 concentration, and leakage flow rate. The total measurement error was accurate to no more than 10%. Furthermore, the difference between the photosynthetic rate of the single leaf and that of the whole-canopy was not significant in Rubisco activity-limited carboxylation range. In addition, the Farquhar–von Caemmerer–Berry (FvCB) model parameters and the photosynthetic rate estimation values were compared to evaluate the steady- and unsteady state measurement methods between the cucumber seedlings' single-leaf and whole-canopy. The average root mean square error of the FvCB model in the steady (standard A-Ci response) and unsteady states (800 to 400 ramp) of the chambers was 1.4 and 2.3, respectively. Results show that the developed system is suitable for measuring the gas exchange rate of the cucumber canopy.ConclusionsWe demonstrate the correction method for measurement errors to enable the gas exchange rate of the whole-canopy even in an unsteady state. The correction method of the measurement system of the gas exchange rate for the whole- canopy can be applied regardless of the volume of the chamber, and it can be applied simply to other chamber systems. In addition, an unsteady state measurement method for fast data collection was also applicable. However, it was deemed necessary to identify a more optimal measurement range by conducting measurements across a broader range of values.

Designing Inclusive Qualitative Research with Carers of People Living with Dementia: Methodological Insights.

The support provided by carers of people living with dementia results in savings for the UK economy; however, providing this care has a significant impact on carers. Supports are needed to ensure that carers can continue to provide care, and carers should be involved in the generation of the evidence necessary to develop such support. However, this relies on their ability to meaningfully engage with research, yet current data collection methods create obstacles to engagement. In this paper, we aim to provide a critical examination of approaches to qualitative data collection with carers and produce recommendations for the design of inclusive research. First, different approaches to qualitative data collection are discussed and appraised. Following this, a case study of inclusive research is presented, illustrating how carers can be facilitated to engage in research. Finally, recommendations for inclusive research are offered, including the collection of data without the cared-for person present, building additional care into a study design, providing 'incidental funds,' offering sustenance and remuneration, and undertaking research in a neutral space. These recommendations are designed to facilitate the involvement of carers in research and promote the use of more varied or multifaceted methods to develop the current evidence base.

Implementasi Metode Learning Vector Quantization (LVQ) Untuk Klasifikasi Keluarga Beresiko Stunting

Stunting is a condition where a child's height is too short compared to children of the same age. This condition affects the health of toddlers in the short and long term, such as suboptimal body posture in adulthood, decreased reproductive health, and decreased learning capacity, resulting in suboptimal performance in school. One of the causes of stunting is a lack of nutrition, basic health facilities, and poor parenting practices. However, the current data collection and classification of families at risk of stunting still use Microsoft Excel, which is ineffective in processing large data. Therefore, the LVQ method, which is an improvement of the Vector Quantization method, is used to accelerate the classification process. In this study, 5 parameters were tested, and the optimal result was achieved by using 7 input neurons, Chebychev distance as the distance measure, a learning rate of 0.1, 7 epochs, and 30% of training data. With these parameters, an accuracy of 99.38% was obtained. Based on these results, the LVQ method can help improve accuracy in classifying families at risk of stunting

Centering patient perspectives to achieve injury-related health equity in trauma care systems: Improving trauma registry data

BackgroundLimitations in current data collection systems for patients who experience traumatic injury limit researchers’ ability to identify and address disparities in injury and outcomes. We sought to develop and test a patient-centered data-collection system for equity-related data indicators that was acceptable to racially and ethnically diverse patients being treated for traumatic injuries. MethodsHealth equity indicators included in this study were race and ethnicity, language, education, employment, housing, and injury address. We conducted interviews with 245 racially and ethnically diverse trauma patients who were treated at a level-1 trauma center in the US in 2019–2020. We first interviewed 136 patients to develop a culturally resonant process and options for the health equity indicators to be added to a revised data collection system for the electronic medical record. English and Spanish interviews were audio-recorded and transcribed verbatim; qualitative analysis was used to assess patient preferences. We then pilot tested the revised data collection system with an additional 109 trauma patients to assess acceptability. Acceptability was defined as having more than 95% of participants self-identify with one of the proposed options for race/ethnicity, language, education, employment, and housing. Injury address (to identify geographic disparities) was pre-defined as acceptable if at least 85% of participants could identify exact address, cross streets, a landmark or business, or zip code of injury. ResultsA revised data collection system, including culturally resonant indicators and a process to be used by patient registrars to collect health equity data, was pilot tested, refined, and considered acceptable. Culturally resonant question phrasing/answer options for race/ethnicity, language, education, employment, housing status, and injury address were identified as acceptable. ConclusionsWe identified a patient-centered data collection system for health equity measures with racially and ethnically diverse patients who have experienced traumatic injury. This system has the potential to increase data quality and accuracy, which is critical to quality improvement efforts and for researchers seeking to identify groups most impacted by racism and other structural barriers to equitable health outcomes and effective intervention points.

Participation in a multidisciplinary institutional committee, “RQUEST,” to enhance quality improvement education, project design, and implementation for hematology/oncology fellows.

e18733 Background: Participation in quality improvement (QI) projects allows medical trainees to develop an essential skillset to systematically analyze practice and implement changes with the goal of practice improvement. The ACGME designates QI education and participation as a core competency for all fellows. Training programs and institutions can vary significantly in QI educational format, participation, and direct support for project design and implementation. Here we present a description of the Resident Quality, Experience, and Safety Team (RQUEST) committee, which is being utilized by Hematology and Oncology fellows for QI project design and implementation at our institution. Methods: The first RQUEST committee was convened in August of 2021. RQUEST holds formal monthly meetings from August to June of each academic year. At the initial meetings, committee members are introduced to quality, safety, and patient experience structures and receive introductory training in QI tools and techniques. RQUEST members are then split into smaller project groups and work to select a QI project, perform current state analysis and baseline data collection, design and implement improvement interventions, and re-measure to determine the impact of the chosen interventions. The year concludes with each team presenting their project at a joint session to a larger audience of program directors, quality officers, service line directors, department chairs, graduate medical education staff, and hospital leadership RQUEST participation provides fellows with direct access to a multidisciplinary team and resources throughout project design and implementation. The timeline of monthly meetings provides both accountability and productive feedback. This facilitates the identification of system-specific opportunities for improvement and the most practical points of contact within the hospital, clinic, or EMR to design and apply quality interventions promptly and effectively. Results: We sent a voluntary survey to RQUEST participants, and 40% of participants responded to the survey. 100% of those who responded said participating in RQUEST has been beneficial in developing and implementing a QI project, and 100% said they would recommend participating in RQUEST to other medical trainees. The most common benefits listed were: · Structured approach/guidance · Institutional support and resources · A collaborative environment with a team of members from various departments, including IT. Conclusions: Fellow participation in a multidisciplinary QI committee at our institution has improved fellow QI education, participation, and project implementation. This engagement model has proven valuable to fellows and faculty in enhancing QI competency and clinical practice.

Software Methodology for Data Control and Collection for Autonomous Monitoring Systems with a Large Amount of Generated Information on the Example of Software for a Hydrological Radiolocation System

Introduction . The current data monitoring and collection systems produce a growing amount of generated information. Such factors, as the increasing sampling rate of ADCs and the increasing speed of systems for primary processing, receiving, and transmitting information, etc., make the systems operate almost at the bandwidth limit of data transmission interfaces. In some applications, such a flow is redundant and can be optimized through the use of various algorithms for the primary processing of information. However, in some applications, reducing the data flow is impossible, since the received information is processed with a delay. Therefore, the development of a software methodology for controlling and collecting data in the system of automatic monitoring of the sea surface by a hydrological radiolocation system seems a relevant research task. Aim . To synthesize a methodology and to develop software for controlling the information system of radar monitoring of the sea surface. Materials and methods . System approach, software architectural and algorithmic design, software quality management methods, system analysis, Qt framework, C++ programming language. Results . A working methodology for designing software for controlling information and measurement technologies with a large amount of generated data was obtained. The effectiveness of the methodology and software quality were confirmed by control tests. A 3-month autonomous testing of the stability and reliability of the system was carried out. Detection of data loss in the system comprised less than 0.002 %, thus not exceeding the specified critical level of 0.5 %. Conclusion . The developed methodology can be used in designing software for controlling information and measuring systems generating a large amount of data. The approaches used to build a multithread software architecture with asynchronous data flow control has shown their high efficiency.

Examining injury trends in parcel delivery drivers in the United States: Challenges and opportunities.

Growth of e-commerce has caused a vast increase in parcel delivery, which raises concern for safety of drivers and other road users as more deliveries take place. This project analyzes injury/illness and fatality trends among workers with delivery-related NAICS codes using three major sources of occupational hazard data in the United States: the Survey of Occupational Illnesses and Injuries, the Census of Fatal Occupational Injuries, and the Industrial Tracking Application. Descriptive statistics were employed to illustrate trends over time as well as to highlight opportunities for improved data collection and dissemination. The number of injuries to drivers has risen sharply over the past decade. Some of this increase appears due to growth of this industry, but increasing overall rates suggest the industry is becoming more hazardous. While nonfatal injuries were typically caused by continuous workplace exposures (e.g., repetitive strain, contact with object/equipment), fatalities were almost exclusively caused by transportation incidents. Additionally, crucial aspects of these trends are difficult or impossible to analyze given the current data landscape. Observed trends reinforce earlier calls for additional scrutiny of working conditions that threaten drivers. Injuries caused by transportation incidents are likely more severe than others and highlight the danger the transportation system poses to drivers and others. Current data collection and dissemination processes offer room to improve in terms of understanding how to prevent future injuries.

A systems science approach to identifying data gaps in national data sources on adolescent suicidal ideation and suicide attempt in the United States

BackgroundSuicide is currently the second leading cause of death among adolescents ages 10–14, and third leading cause of death among adolescents ages 15–19 in the United States (U.S). Although we have numerous U.S. based surveillance systems and survey data sources, the coverage offered by these data with regard to the complexity of youth suicide had yet to be examined. The recent release of a comprehensive systems map for adolescent suicide provides an opportunity to contrast the content of surveillance systems and surveys with the mechanisms listed in the map.ObjectiveTo inform existing data collection efforts and advance future research on the risk and protective factors relevant to adolescent suicide.MethodsWe examined data from U.S. based surveillance systems and nationally-representative surveys that included (1) observations for an adolescent population and (2) questions or indicators in the data that identified suicidal ideation or suicide attempt. Using thematic analysis, we evaluated the codebooks and data dictionaries for each source to match questions or indicators to suicide-related risk and protective factors identified through a recently published suicide systems map. We used descriptive analysis to summarize where data were available or missing and categorized data gaps by social-ecological level.ResultsApproximately 1-of-5 of the suicide-related risk and protective factors identified in the systems map had no supporting data, in any of the considered data sources. All sources cover less than half the factors, except the Adolescent Brain Cognitive Development Study (ABCD), which covers nearly 70% of factors.ConclusionsExamining gaps in suicide research can help focus future data collection efforts in suicide prevention. Our analysis precisely identified where data is missing and also revealed that missing data affects some aspects of suicide research (e.g., distal factors at the community and societal level) more than others (e.g., proximal factors about individual characteristics). In sum, our analysis highlights limitations in current suicide-related data availability and provides new opportunities to identify and expand current data collection efforts.

Legal issues pertaining to the collection of sociodemographic data in emergency departments.

Legal issues pertaining to the collection of sociodemographic data in emergency departments.

What Does School Attendance Mean in Japanese Compulsory Education Schools? Analysing the National Annual Report

School absenteeism in Japan has become a serious psychosocial issue over the past few decades. According to the national survey conducted annually by the Ministry of Education, Culture, Sports, Science and Technology − Japan (MEXT), the number of students with school attendance problems (futoko) in compulsory education schools has been the highest since the government introduced the current data collection format in 1991. All Japanese compulsory education schools collect data on attendance and absence each day. The obtained data in each school are collected by MEXT via local education boards, which are eventually reported as annual national data. However, in recent years, data classification and interpretation of school attendance and absenteeism have become more complicated, which may constitute a limiting factor for appropriate measures for school absenteeism in Japan. The current study showed the situation of school absenteeism in Japanese compulsory education schools using the annual data reported by MEXT, and it examined matters of data classification and interpretation. The author proposed that two main categories of attendance/absence be used, namely: (a) class attendance in mainstream schools, and (b) class nonattendance in mainstream schools.

ESHRE PGT Consortium data collection XXI: PGT analyses in 2018.

What are the trends and developments in preimplantation genetic testing (PGT) in 2018 as compared to previous years? The main trends observed in this 21st dataset on PGT are that the implementation of trophectoderm biopsy with comprehensive whole-genome testing is most often applied for PGT-A and concurrent PGT-M/SR/A, while for PGT-M and PGT-SR, single-cell testing with PCR and FISH still prevail. Since it was established in 1997, the ESHRE PGT Consortium has been collecting and analysing data from mainly European PGT centres. To date, 20 datasets and an overview of the first 10 years of data collections have been published. The data for PGT analyses performed between 1 January 2018 and 31 December 2018 with a 2-year follow-up after analysis were provided by participating centres on a voluntary basis. Data were collected using an online platform, which is based on genetic analysis and has been in use since 2016. Data on biopsy method, diagnostic technology, and clinical outcome were submitted by 44 centres. Records with analyses for more than one PGT for monogenic disorders (PGT-M) and/or PGT for chromosomal structural rearrangements (PGT-SR), or with inconsistent data regarding the PGT modality, were excluded. All transfers performed within 2 years after the analysis were included, enabling the calculation of cumulative pregnancy rates. Data analysis, calculations, and preparation of figures and tables were carried out by expert co-authors. The current data collection from 2018 covers a total of 1388 analyses for PGT-M, 462 analyses for PGT-SR, 3003 analyses for PGT for aneuploidies (PGT-A), and 338 analyses for concurrent PGT-M/SR with PGT-A.The application of blastocyst biopsy is gradually rising for PGT-M (from 19% in 2016-2017 to 33% in 2018), is status quo for PGT-SR (from 30% in 2016-2017 to 33% in 2018) and has become the most used biopsy stage for PGT-A (from 87% in 2016-2017 to 98% in 2018) and for concurrent PGT-M/SR with PGT-A (96%). The use of comprehensive, whole-genome amplification (WGA)-based diagnostic technology showed a small decrease for PGT-M (from 15% in 2016-2017 to 12% in 2018) and for PGT-SR (from 50% in 2016-2017 to 44% in 2018). Comprehensive testing was, however, the main technology for PGT-A (from 93% in 2016-2017 to 98% in 2018). WGA-based testing was also widely used for concurrent PGT-M/SR with PGT-A, as a standalone technique (74%) or in combination with PCR or FISH (24%). Trophectoderm biopsy and comprehensive testing strategies are linked with higher diagnostic efficiencies and improved clinical outcomes per embryo transfer. The findings apply to the data submitted by 44 participating centres and do not represent worldwide trends in PGT. Details on the health of babies born were not provided in this manuscript. The Consortium datasets provide a valuable resource for following trends in PGT practice. The study has no external funding, and all costs are covered by ESHRE. There are no competing interests declared. N/A.