Data Entry Task Research Articles

A digital twin for operations management in manufacturing engineering-to-order environments

Engineering-to-order (ETO) companies satisfy a very demanding market, where each client specifies the type of product they require and actively participate in the design, selection of materials, and other activities. This converts the production processes of ETO companies into one-of-a-kind processes (OKP) type, where production planning and control (PPC) activities are extremely complex. The cause of this complexity is the little or no standardization between the different production cycles that must be executed, as each cycle is of the OKP type. In addition, Intra-logistics operations represent a key factor in ETO PPC, since each piece of work-in-process or sub-assembly can be extremely large, heavy or complicated of handling. Then, ETO systems involve heterogenous production and intra-logistics processes, where the associated information is fragmented and diverse. This hampers a streamline information processing and operations management. To overcome all these issues, a Digital Twin (DT) approach is proposed. The DT designed and developed here allows to integrate engineering and planning departments to be effectively integrated with the shop-floor and operations management in a smooth and effective manner. To solve interoperability and information access without overloading data-entry tasks novel information structures are designed, along with the logical processes that support them. These logical processes enable DT to generate autonomously intra-logistics operations orders from the engineering plans, fostering the system integration and agility. This DT is tested on a manufacturing ETO case study and shows its efficiency.

Handwritten Optical Character Recognition to Digital Text Conversion

Handwritten Optical Character Recognition (OCR) is a crucial technology for converting handwritten text into digital format. This process involves detecting and interpreting handwritten characters from images or scanned documents. In this project, we focus on OCR for three languages: Kannada, Telugu, and Hindi. The system utilizes machine learning algorithms, specifically trained neural networks, to recognize and transcribe handwritten characters accurately. The OCR system preprocesses the input images, applies character segmentation, and then classifies each segment into the corresponding character class. Post- processing techniques may be applied to improve accuracy and handle noise. The converted digital text can then be further processed, analyzed, or stored as needed. This technology has various applications in digitizing historical documents, automating data entry tasks, and enabling accessibility for visually impaired individuals

RECENT ADVANCES AND APPLICATIONS OF DEEP LEARNING (DL) IN THE ACCOUNTING PROFESSION

In recent years, the accounting profession has undergone a transformative revolution with the help of rapid advancement in Deep Learning (DL) technologies. Deep Learning, a subset of Artificial Intelligence (AI) has emerged as a powerful tool in the world of finance and accounting, offering unprecedented opportunities for automating tasks, improving accuracy and uncovering valuable insights. This groundbreaking technology has found a multitude of applications in accounting, ranging from automating repetitive data entry tasks to enhancing fraud detection, financial forecasting and risk management. Deep Learning driven by Artificial Intelligence Neural Networks (AI-NN), Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN) and more is reshaping the landscape of financial analysis, auditing, prevention of frauds, risk management and much more. Through these advancements, we gain not only efficiency but also a new perspective on the role of accountants in an increasingly data-driven and digitally interconnected world.

Application of OCR-based assistance solutions in engine maintenance

The aviation industry is one of the leading transportation sectors with a rising number of passengers worldwide. However, this rise in demand leads to increased maintenance requirements for the engines. Jet engines are comprised of many components each denoted with a part and serial number. The data entry task for mechanics can be cumbersome and human errors can lead to incorrectly documented numbers and even result in severe safety issues. To assist mechanics in the task of recognizing and transcribing serial numbers, optical character recognition methods are being considered, with no satisfactory solution being found yet. This paper addresses this issue by comparing possible optical character recognition methods and identifying ways to improve the error rate based on a real use case.

Simplifying molecular testing through electronic order entry

Abstract Our solid-tumor molecular laboratory receives more than 3,000 orders each year, with about two-thirds coming from internal providers. Before this project, molecular tests were ordered using one of two different paper forms, which the care team then faxed or e-mailed to the Genetics Preanalytical Service (GPS). These requests led to frequent modifications and cancellations due to the complexity of molecular testing. A small fraction of requisitions were lost due to transmission errors. We undertook a project to design, develop, and implement computerized physician order entry (CPOE) in Epic (Epic Systems Corp., Verona, WI) and Sunquest (Clinisys, Tucson, AZ). We conducted extensive interviews with the directors of the molecular lab, laboratory medicine IT, GPS, anatomic pathology staff, laboratory scientists, laboratory genetic counselors, oncologists, clinicians, and nurse coordinators. The order itself and other technical changes underwent iterative review and testing by a subset of interviewees. Five oncologists participated in formal beta-testing. The user interviews allowed us to produce a detailed process diagram that drew attention to specific areas of repetition or risk. We proposed a new workflow that would eliminate repetition, provide redundant order-tracking, and automate some lab processes. Once approved, we built the electronic order in Epic and modified existing laboratory programs and interfaces as needed. The process of placing an order, which previously typically involved both nurses and doctors over several calendar days, was now being completed in fewer than 5 minutes by a single practitioner. Requisition status events were no longer created manually in Sunquest by GPS. Certain data-entry tasks were eliminated through the incorporation of label printers. Within one month of launch, more than 50% of somatic molecular orders arrived via CPOE, increasing to 90% within six months. At a rate of 125 CPOE orders per month, time savings range from 20 hours per month for GPS staff, 50 hours per month for nursing, and 20 hours per month for physicians. The success of this project demonstrates the feasibility of replacing a paper-based process for a complex test menu with CPOE. Due to the intricacies of molecular testing, such a change will undoubtedly involve multiple divisions. We attribute the success of this project to early involvement by key stakeholder groups, including developers; an extended testing phase to ensure reliability at roll-out; creation of straightforward reference documents; and rapid response to user questions, especially during the first weeks post-launch.

Effect of electronic health records on doctor-patient relationship in Arabian gulf countries: a systematic review.

The electronic health record (EHR) has been widely implemented internationally as a tool to improve health and healthcare delivery. However, EHR implementation has been comparatively slow amongst hospitals in the Arabian Gulf countries. This gradual uptake may be linked to prevailing opinions amongst medical practitioners. Until now, no systematic review has been conducted to identify the impact of EHRs on doctor-patient relationships and attitudes in the Arabian Gulf countries. To understand the impact of EHR use on patient-doctor relationships and communication in the Arabian Gulf countries. A systematic review of English language publications was performed using PRISMA chart guidelines between 1990 and 2023. Electronic database search (Ovid MEDLINE, Global Health, HMIC, EMRIM, and PsycINFO) and reference searching restricted to the six Arabian Gulf countries only. MeSH terms and keywords related to electronic health records, doctor-patient communication, and relationship were used. Newcastle-Ottawa Scale (NOS) quality assessment was performed. 18 studies fulfilled the criteria to be included in the systematic review. They were published between 1992 and 2023. Overall, a positive impact of EHR uptake was reported within the Gulf countries studied. This included improvement in the quality and performance of physicians, as well as improved accuracy in monitoring patient health. On the other hand, a notable negative impact was a general perception of physician attention shifted away from the patients themselves and towards data entry tasks (e.g., details of the patients and their education at the time of the consultation). The implementation of EHR systems is beneficial for effective care delivery by doctors in Gulf countries despite some patients' perception of decreased attention. The use of EHR assists doctors with recording patient details, including medication and treatment procedures, as well as their outcomes. Based on this study, the authors conclude that widespread EHR implementation is highly recommended, yet specific training should be provided, and the subsequent effect on adoption rates by all users must be evaluated (particularly physicians). The COVID-19 Pandemic showed the great value of EHR in accessing information and consulting patients remotely.

Adherence to standard operating procedures for improving data quality: An empirical analysis in the postal service industry

Complete and accurate data is an important enabler of effective supply chain decision making. Despite the increasing efforts to fully automate data collection processes using advanced sensors and scanners, human operators are still in charge of data entry tasks in most industries. Unfortunately, operators do not often comply with the standard operating procedures (SOPs) and do not always exhibit the consistency and commitment required to collect high-quality data. In fact, data collection is often perceived as a non-value-adding activity that increases workloads and lowers productivity. We aim to empirically study the extent to which compliance with SOPs for data collection is affected by some of the key factors. Using a large dataset obtained from a leading postal service provider in Australia, we find that an operator’s workload, fatigue, and related work experience directly impact the compliance levels. We also find that a company’s compliance reinforcement intervention to improve compliance behavior can moderate these impacts.

Trends, relationship, and model of selected service sector workers in Malaysia: Physiological responses of mental workload and mental fatigue during performing real-time tasks

Service sector is a job that is considered exposed to high mental demand. There is lack of technique to measure issues related to the mental workload and mental fatigue levels among workers. Moreover, no studies have yet developed a model to predict mental fatigue especially for service sector workers. It is necessary to investigate mental workload and mental fatigue in real time working activities. The main purpose of this study was to identify the trends and relationship between mental workload and mental fatigue level among service sector workers. Ten participants with a mean age of 35.00±8.62 (SD) years took part in the study. Two experiments in Without Rest (WoR) and With Rest (WR) segments involving data entry and arithmetic tasks were conducted. Physiological measures using Electroencephalogram (EEG), Electrooculogram (EOG) and heart rate (HR) were assessed while participants were performing the tasks. The result shows that EEG alpha signal was significantly higher at the end of WR compared to WoR segment (p<0.05). Comparison between WoR and WR segments for each task show that HR of WR tasks were significantly lower in all tasks (p<0.05). This study developed seven mental workload and mental fatigue conceptual models with strong variables correlations (r>0.05) to evaluate the variability of both parts of two types of activities, namely, data entry and arithmetic tasks. The findings highlighted that validated parameters and methods for mental fatigue and mental workload measures are brain signals and heart rate monitoring, and task performance measure. Significant findings of the study could be as a reference for organizations to plan and manage resources by optimizing mental workload condition and minimizing mental fatigue occurrence

E-liquid purchase as a function of workplace restriction in the experimental tobacco marketplace.

E-cigarette use is prohibited in most smoke-free environments. The effect of this policy on tobacco consumption could be examined using the Experimental Tobacco Marketplace (ETM). The ETM allows observation of policy on smokers' purchasing behavior under conditions that simulate "real-world" circumstances. A within-subject design was used to evaluate the effect of workplace policy (Vaping Allowed vs. Not Allowed) and nicotine concentration (24 mg/mL vs. 0 mg/mL) on tobacco product consumption. Participants (n = 31) completed one sampling and two ETM/workplace sessions per week for 2 weeks. During the sampling session, participants were given an e-cigarette with a 2-day supply of a commercially available e-liquid of their preferred flavor. Before purchasing, participants were informed whether e-cigarette use was permitted. During the four ETM sessions, participants purchased for the following 24 hr, including the 4-hr work shift that started immediately after buying products in the ETM. The workplace session consisted of data entry tasks in a mock office environment. Participants could use any purchased tobacco products during two 15-min breaks. Condition order was counterbalanced. The results show that permitting E-cigarette use in the workplace increased e-liquid purchase on average, but nicotine concentration had no effect on e-liquid demand. Cigarette demand was unaltered across conditions. The present study suggests that allowing e-cigarette use in the workplace would increase demand for e-liquid regardless of nicotine strength. However, it would not change conventional cigarette demand. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Utilization of 2D Barcode Technology to Create Surgical Pathology Reports

Abstract Introduction/Objective After professional transcription service is eliminated, pathologists inevitably undertake the task of diagnostic data entry into pathology repot by adapting a variety of methods such as speech recognition, manual typing, and pre-texted command. Errors and inefficiency in reporting remain common problems, especially for information with unusual syntax such as genotype or nucleotide sequences. To overcome these shortcomings, we introduce here a novel application of a well-established technology as a complementary method, namely 2- dimensional (2D) barcode symbology. Methods/Case Report Commonly used diagnostic wordings of pathology reports including specimen type, surgical procedure, diagnosis, and test results are collated and organized by organ (specimen type) and by their frequency of usage/occurrence. Next, 2D data matrix barcodes are created for these diagnostic wordings using a on-line tool (www.free-barcode-generator.net/datamatrix/). The 2D barcodes along with their text are displayed on the computer screen (or printed out as a booklet). A 2D barcode scanner (Symbol LS2208, Motorola) was used to retrieve the text information from the barcodes and transfer into the pathology report. To assess the efficacy of this barcode method, we evaluated the time of data entry into reports for 117 routine cases using an on-line stopwatch and compared with those by other data entry methods. Results (if a Case Study enter NA) Unlike manual typing or speech recognition, the barcode method did not introduce typographic or phonosemantic errors since the method simply transferred pre-texted and proof-read text content to report. It was also faster than manual typing or speech recognition, and its speed was comparable to that of the pre-text method integrated in LIS but did not require human memorization of innumerable text commands to retrieve desired diagnosis wordings. Conclusion Our preliminary results demonstrated that the diagnostic data entry time was reduced from 28.5% by other methods to 22.1% by the barcode method although due to the small sample size, statistical analysis was not conclusive.

A comparative evaluation of the wearable augmented reality-based data presentation interface and traditional methods for data entry tasks

Data entry is a ubiquitous task performed in today's offices. Persistent data entry is linked with high workload and fatigue due to poor ergonomic workplace design and poor posture. This study aims to alleviate data entry operators' workload and improve data entry performance by applying wearable augmented reality (AR) technology to data entry tasks. An AR-based interface was developed and used to present data to the participants, who entered the data in web-based data entry forms. A total of eighteen participants performed data entry tasks to evaluate the AR interface with traditional methods – extra desktop monitor and paper-based data presentation methods. Each method's performance was judged on the task completion time, typing error rate, workload, and usability. The usability and overall perceived workload while using an AR interface for data entry were similar to the traditional way of using paper, despite the additional burden due to the weight of the AR headset. AR interface did not perform better than the extra desktop monitor interface for usability and overall perceived workload. The results from this study can be utilized to design AR devices that are suited for data entry tasks.

Effects of Head-locked Augmented Reality on User’s Performance and Perceived Workload

An augmented reality (AR) environment includes a set of digital elements with which the users interact while performing certain tasks. Recent AR head-mounted displays allow users to select how these elements are presented. However, few studies have been conducted to examine the effect of presenting augmented content on user performance and workload. This study aims to evaluate two methods of presenting augmented content — world-locked and head-locked modes in a data entry task. A total of eighteen participants performed the data entry task in this study. The effectiveness of each mode is evaluated in terms of task performance, muscle activity, perceived workload, and usability. The results show that the task completion time is shorter, and the typing speed is significantly faster in the head-locked mode while the world-locked mode achieved higher scores in terms of preference. The findings of this study can be applied to AR user interfaces to improve content presentation and enhance the user experience.

Abstract P241: Why Do We Expect Clinicians to Perform the Work of Computers? Developing an Automated Stroke Registry

Background: Stroke registries are established with the primary goal of improving health care quality and performance improvement through increased adherence to evidenced based guideline recommendations. As a Joint Commission certified organization, the Comprehensive Stroke Center uses the American Heart Association’s Get With The Guidelines® (GWTG) stroke patient management tool to collect performance improvement data on patients admitted with a principle diagnosis of stroke. Data abstraction is laborious and time consuming which requires manual entry by multiple clinicians. Therefore, we developed an automated internal stroke database to improve efficiency and augment accuracy. Methods: We collaborated with software engineers and EPIC report writers to create an innovative stroke database with the capability to extract data from an Electronic Health Record (EHR) for upload to GWTG. The clinicians identified data elements for automation in the EHR. Based on final ICD-10 coding the report writer retrieved end-user data, which were organized into tables and sent to the software engineer. These variables were processed to match GWTG specifications and then presented to clinicians in the user interface for validation. Next, a CSV file was generated and uploaded to GWTG, where the remaining data was entered. Results: The case completion time was reduced from 45 minutes to one hour to an average of 25 minutes (median 23 minutes), thus achieving our primary goal. Due to the variance in the number of required data elements based on diagnosis and patient specific variables, we aggregated the data elements, automated versus required, and calculated an automation rate of 54%. Approximately half of the 414 fields required in GWTG have the potential for automation, and we continue to strive toward this goal. Due to the complexity of GWTG questions and the way data is captured in the EHR, some data elements require manual entry. Conclusions: An automated stroke registry has the potential to enhance efficiency and limit the opportunity for human error. By minimizing the clinicians’ data entry tasks to those of higher-level data abstraction, there is more time for performance improvement.

Effect of Size of Smart Technologies under the Influence of Noise on the Performance of Gender during Data Entry Task

Effect of Size of Smart Technologies under the Influence of Noise on the Performance of Gender during Data Entry Task

ON THE PATH TO ARTIFICIAL INTELLIGENCE: THE EFFECTS OF A ROBOTICS SOLUTION IN A FINANCIAL SERVICES FIRM

As ever-increasing advances in automation and artificial intelligence solutions create more opportunities for businesses to streamline their operations, the key challenges for managers are to identify the appropriate use cases for automation solutions in their organisations and to integrate the solution effectively to meet the objectives of both the firm and its employees. This case study examines the impact of implementing a machine-learning robotic process automation (RPA) solution that is aimed at reducing manual data entry tasks for employees in a financial services firm. The study employed an action research approach to follow a single team in the firm before and after the RPA implementation — a period of six months. The findings showed that RPA improved productivity in the team and created more positive work experiences for employees, as they had more time to dedicate to creative, cognitive, and customer service tasks. The study also found that the roles of employees were being redefined during the integration process, with employees reporting a high potential for broader transformation in the business as a result of the RPA implementation.

Can Augmented Reality Assist Data Entry Task? A Preliminary Study

Can Augmented Reality Assist Data Entry Task? A Preliminary Study

Increased Productivity and Efficiency Among Cancer Center Clinical Trials Workforce during the COVID-19 Pandemic

Increased Productivity and Efficiency Among Cancer Center Clinical Trials Workforce during the COVID-19 Pandemic

P‐28: Investigating the Usability of Touchscreen Interfaces in a Turbulent Flight Deck – For Panning and Numeric Data Entry Tasks

This paper studies the use of touchscreen displays on the flight deck, focusing on the usability of touch interfaces to complete panning and numeric entry tasks. Results from this study show that the usability of a drag gesture to meet a pan function, surpasses the performance of a simple tapping interface under all turbulent conditions tested. Also, that this drag interface is more useable in an inter‐seat flight deck position, than a central one. It was also found that touchscreen interfaces can surpass the performance of the traditional mechanical dial interface for numeric data entry tasks, under all turbulent conditions tested.

Vulnerabilities for Drug Diversion in the Handling, Data Entry, and Verification Tasks of 2 Inpatient Hospital Pharmacies: Clinical Observations and Healthcare Failure Mode and Effect Analysis.

Inpatient hospital pharmacies have a central role in managing controlled substances (CS) throughout the hospital medication use process (MUP). Our objectives were to identify vulnerabilities for diversion in the MUPs of 2 inpatient pharmacies, explore differences between the sites, and characterize the types of vulnerabilities identified. We conducted clinical observations in 2 pharmacies to map their MUPs and performed a healthcare failure mode and effect analysis to proactively identify (1) the critical failure modes (CFMs) that make them vulnerable to diversion and (2) the controls that prevent, mitigate, or enhance the detectability of CFMs. We conducted 99 hours of observations between May-June and September-October 2018. We observed 36 pharmacy technicians, 4 pharmacists, and 1 clerk as they conducted tasks involving 4 processes common to both sites: procuring CS, receiving CS deliveries to the pharmacy, unit-dose packaging CS oral solids, and distributing CS to hospital units. The tasks and subtasks we mapped in the process flow diagrams led to the identification of 220 failure modes. Of these, 34 were deemed CFMs and were categorized as related to handling CS, data entry, or verification tasks. Three of the CFMs were unique to one site, given that the other site had a control for the CFM. Multiple vulnerabilities for diversion exist in inpatient pharmacy processes. Our results provide some much needed detail about how specific vulnerabilities in MUP tasks and subtasks lead to an increased risk of diversion.

Gaze window: A new gaze interface showing relevant content close to the gaze point

AbstractIn this paper, we propose a novel concept of the gaze window, which follows the user's gaze to show relevant information close to their gaze point on a screen space. We explore the use of a gaze window, especially for two use cases: (1) a single‐user data entry task by displaying data‐source image close to the gaze point where the data are typed in and (2) a teleconferencing setup showing a remote partner close to the gaze point. To investigate the performance of gaze window in these cases, we conducted two experiments. For the single‐user task, we compared the gaze window with a baseline non‐gaze‐window condition and found that the gaze window significantly reduced the user's gaze movement and mental effort and increased usability. In the teleconferencing task, we compared displaying partner close to gaze point in the gaze window to displaying partner at the corner of screen, when two remote users watch a shared and synchronized content together. We found that displaying the partner's face nearby the user's gaze helped the user look at the partner more frequently, and for a longer time, significantly increasing co‐presence and emotional interdependence. As a result of this research, we also presented design guidelines for gaze‐window systems.