research paper on barcode technology

Design and Implementation of Barcode Management Information System

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• Daiyun Weng 3 &
• Li Yang 3  

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Barcode technology is an automatic identification technology generated and developed in computer application and an effective means of data collection designed to achieve the automatic scanning of information. It is widely used in the logistics industry and typically used in the goods sale in supermarkets. At present, barcode management and identification system has been widely used in various types of supermarkets in the country. This article first introduces the use of bar code in domestic supermarkets and the technical characteristics and image recognition system of the maximum used EAN barcodes, proposing the corresponding barcode generation and identification methods based on image recognition technology. On this basis, the barcode generation and recognition software is developed. Feature of this study is that the recognition system can simultaneously generate and identify barcodes, so it can be more convenient and efficient for goods management and material circulation of medium, small supermarkets, specialty stores and other users. And it can be widely used in other areas, such as personnel management.

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Feng Zhang, Yaoqiu WANG: Barcode Technology and Electronic Data Exchange. Beijing: China Railway Press, 2008

Yongfa Fan, Hongzhuang He: Barcode Image Recognition System, 2006

Yingquan Yang: Design and Implementation of Library Barcode Software. Microcomputer Applications, 2005 01

Ming Wu: The use of Barcode in Large Supermarkets. China’s Retail Network, 2009

Zhijian Huang, Xiangyang Gu, Juntao Dai: Barcode Technology and Application, Beijing: Mechanical Industry Press, 2002

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Daiyun Weng & Li Yang

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, School of Computer and Information, Chongqing Normal University, Chongqing, 401331, China, People's Republic

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Weng, D., Yang, L. (2012). Design and Implementation of Barcode Management Information System. In: Zhu, R., Ma, Y. (eds) Information Engineering and Applications. Lecture Notes in Electrical Engineering, vol 154. Springer, London. https://doi.org/10.1007/978-1-4471-2386-6_158

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Implementation of barcode technology to logistics processes of a company.

1. Introduction

• non-functional RFID equipment and tags;
• usage errors related to the RFID antenna;
• errors when scanning the entire stack of plastic trays;
• incorrect identifiers in the tray (it leads to a warning sound then the operator looks at the screen and stops scanning).
• missing labels on the outside of the plastic tray;
• illegible labels on a plastic tray;
• non-functional scanning device;
• a usage error in which the operator scans the barcode incorrectly or slowly.
• Speed—because an RFID reader can read tags faster than a normal barcode scanner can scan barcodes. For example, RFID readers designed for supply chain operations can perform up to 1500 read operations per second;
• Reading distance—because it is common to read RFID tags at a distance of at least three meters between the tag and the antenna. Reading sizes and ranges are also compared with different RFID chips and the longest reading range in Article [ 14 ] is 14.6 m for a metal mounting antenna. Their passive UHF RFID tag had a range of 26 m for reading using the Higgs 4 RFID chip manufactured by Alien Tech.
• Simultaneous instead of sequential scanning—because RFID readers can identify multiple tags in a reading field;
• Direct view—because radio waves can penetrate most materials depending on the frequency used;
• Durability—as RFID tags can work in extremely demanding working conditions and can be packaged in plastic packaging or even embedded directly into finished products [ 10 , 15 , 16 ].

2. Materials and Methods

• incorrectly entered balance from the warehouse;
• ordering the wrong quantity;
• error when entering data manually;
• differences between the actual stock balance and the stock level in the SAP system.

2.1. Measuring the Duration of Individual Activities in the Process

• registration of a request for documentation;
• picking cables for production ○ picking cables on a pallet; ○ cable transport; ○ placing cables; ○ checking (OK);
• rewriting the material for ordering and sending the list for operational purchase;
• copying the list to the cable order and evaluating the order;
• issuing an order in the SAP system.

2.2. Methodology for Time Measurements

• original method = (3 min 17 s × 17) + (1 min 11 s × 3) = 59 min 23 s
• proposed method = (4 min 2 s × 17) + (1 min 11 s × 3) = 1 h 12 min 7 s
• one week 31 min and 55 s;
• one month 2 h, 7 min, and 40 s.
• scan error—incorrectly entered length;
• scanning error—writing in the wrong field;
• scan error—no input or output scan;
• scanning error—the same operation scanned 2 times;
• incorrectly ordered cable quantity;
• database error.

4. Discussion

5. conclusions.

• extending the proposed method to all available items;
• implementation of the data on the length of the cable on the spool into the barcode;
• setting up a regular inventory;
• introducing cable scanning also when receiving cables;
• regular monitoring and analysis of error rates;
• automating the database and its checking;
• introduction of the pulling principle from production.

Author Contributions

Institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Kubáňová, J.; Kubasáková, I.; Čulík, K.; Štítik, L. Implementation of Barcode Technology to Logistics Processes of a Company. Sustainability 2022 , 14 , 790. https://doi.org/10.3390/su14020790

Kubáňová J, Kubasáková I, Čulík K, Štítik L. Implementation of Barcode Technology to Logistics Processes of a Company. Sustainability . 2022; 14(2):790. https://doi.org/10.3390/su14020790

Kubáňová, Jaroslava, Iveta Kubasáková, Kristián Čulík, and Lukáš Štítik. 2022. "Implementation of Barcode Technology to Logistics Processes of a Company" Sustainability 14, no. 2: 790. https://doi.org/10.3390/su14020790

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Barcode Recognition Techniques: Review & Application

International Journal of Innovative Research in Computer Science & Technology (IJIRCS) 2021

6 Pages Posted: 27 Jul 2021

Nikash Pradhan

Amity University Haryana, Gurugram

Dr. Rajesh Kumar Tyagi

Amity University Haryana

Ms. Pooja Nagpal

Date Written: MAY 20, 2021

Because of the importance of maintaining track of all products in one location, barcodes have become important elements of sales and product services. Many methods have been developed to make the task of reading barcodes more user-friendly. This project aims to use image processing as a technique for recognizing the barcode using the camera. Using this technique, the machines will be able to read the barcode using the camera and can decode the information on the barcode using the software capable of image processing [1]. The platform will be created for the MATLAB software package and will function with a webcam or digital camera as an interface. On the Graphical User Interface, the device can analyse the image and display the barcode type, data, and image size (GUI) [1]. The machine is designed to identify different types of barcodes and display the data if the barcode image is obtained. The machine is also intended to provide a more convenient and cost-effective way of viewing data from barcodes than electronic barcode scanners. An individual who wants to inspect data identified by barcode numbers without having to go to a location that provides barcode scanner services can use this computer at any time and from any location [1]. As a result, the project has gone smoothly and without a hitch. It is advised that the computer have a slider so that the user can change the brightness of the image captured by the webcam for future device enhancement.

Keywords: Barcode, Graphical User Interface, MATLAB, Recognize, Product

Suggested Citation: Suggested Citation

Nikash Pradhan (Contact Author)

Amity university haryana, gurugram ( email ).

Panchgaon, Manesar, Gurugram, Haryana Gurugram, Haryana 122413 India

Amity University Haryana ( email )

Manesar Manesar, 122413 India

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Barcode medication administration technology use in hospital practice: a mixed-methods observational study of policy deviations

1 Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway

Liv Mathiesen

Katja taxis.

2 Pharmacotherapy and Pharmaceutical Care, University of Groningen, Groningen, The Netherlands

Anne Gerd Granås

Associated data.

bmjqs-2021-013223supp001.pdf

bmjqs-2021-013223supp002.pdf

bmjqs-2021-013223supp003.pdf

bmjqs-2021-013223supp004.pdf

No data are available. Additional deidentified data from the observational tool or field notes are not available as participants did not agree to share this information with a broad audience.

Introduction

Barcode medication administration (BCMA) can, if poorly implemented, cause disrupted workflow, increased workload and cause medication errors. Further exploration is needed of the causes of BCMA policy deviations.

To gain an insight into nurses’ use of barcode technology during medication dispensing and administration; to record the number and type of BCMA policy deviations, and to investigate their causes.

We conducted a prospective, mixed-methods study. Medication administration rounds on two hospital wards were observed using a digital tool and field notes. The SEIPS (Systems Engineering Initiative for Patient Safety) model was used to analyse the data.

We observed 44 nurses administering 884 medications to 213 patients. We identified BCMA policy deviations for more than half of the observations; these related to the level of tasks, organisation, technology, environment and nurses. Task-related policy deviations occurred with 140 patients (66%) during dispensing and 152 patients (71%) during administration. Organisational deviations included failure to scan 29% of medications and 20% of patient’s wristbands. Policy deviations also arose due to technological factors (eg, low laptop battery, system freezing), as well as environmental factors (eg, medication room location, patient drawer size). Most deviations were caused by policies that interfere with proper and safe BCMA use and suboptimal technology design.

Our findings indicate that adaptations of the work system are needed, particularly in relation to policies and technology, to optimise the use of BCMA by nurses during medication dispensing and administration. These adaptations should lead to enhanced patient safety, as the absolute goal with BCMA implementation.

Barcode medication administration (BCMA) technology is a health information technology credited for preventing medication errors and promoting patient safety when used accurately. 1 BCMA technology automates the process of verification by scanning the barcode on the medication and the patient identification wristband, thus assisting the nurses in confirming the ‘five rights’ of medication administration: right patient, right medication, right dose, right route and right time. 2 In an effort to prevent consequences of medication administration errors to patients, 3 hospitals have strongly encouraged BCMA implementation. 4–7 The BCMA has shown to reduce medication administration errors significantly and to reduce harm from serious medication errors. 8 Previous studies have also reported an increase in patient identity verification rate after implementing BCMA. 9 10

While BCMA has existed for over two decades, hospitals have struggled to adapt and implement it within their existing infrastructure, 5 11–15 and several studies demonstrate that the implementation process for BCMA is important for its overall success. 12 13 Studies have shown increased workload or disrupted workflow with the use of BCMA, resulting in workarounds, 7 12 14 16 17 such as carrying prescanned medications on carts. 18 These workarounds, also described as policy deviations, can lead to new errors created by the use of the technology. 7 12 18

Although previous studies have identified workarounds and policy deviations with BCMA, 7 12 18 there has been limited research to disclose why deviations occur and the impact of the surrounding context to their occurrence. One systematic review that evaluated the impact of BCMA technology to patient safety concluded that human factors and technical issues are standing in way of achieving intended scanning rates and patient safety benefits. 1 Another systematic review came to a similar conclusion and highlighted the importance of analysing whether deviations that are outside the five types of medication errors can have important implications to patient safety. 19 The purpose of this study, therefore, was to investigate nurses’ interaction with the technology and identify policy deviations as potential unsafe practices using a human factors approach. 20 More specifically, the study aimed to (1) gain an in-depth understanding of how nurses actually use the BCMA during medication rounds, (2) to record the number and types of BCMA policy deviations during medication dispensing and administration, and (3) to investigate probable causes of policy deviations in relation to the socio-technical factors of the working environment.

We used a concurrent triangulated, mixed-methods design comprising structured observation (quantitative data) and field notes and nurses’ comments (qualitative data) of BCMA use at two medical wards at a 700-bed hospital in Norway. Structured observation, involving a digital observational tool, was used to quantify policy deviations. Field notes and nurses’ comments contextualised the quantitative data, provided explanations and sometimes cued the causes to policy deviations.

Theoretical framework

We used the SEIPS model (Systems Engineering Initiative for Patient Safety) 16 20 to provide the theoretical underpinning for this study. This model explores interactions between humans, the technology they use and the environment in which they work, and has been successfully applied in the field of medication administration technologies, 16 as well as across healthcare. 20 In our study, we applied the SEIPS model to categorise the integrated qualitative and quantitative data according to the five elements of the SEIPS model 20 : (1) tasks, (2) organisational factors, (3) technology, (4) physical environment, and (5) individuals.

The study hospital was the first to introduce eMAR (electronic Medication Administration Record) and BCMA technology in Norway. The technology was implemented over a 3-year period, from 2017 to 2019. The studied eMAR and BCMA were a part of Metavision, iMDsoft. In addition to the digitalised medication records, the system comprised barcode scanners, patient identification (ID) wristbands, single-dose medication units, and scanning during dispensing and administration. The hospital used a decentralised ward-based dispensing system. The description of the delivery, dispensing and administration process with respective policy descriptions is illustrated in figure 1 . Data were collected on two wards: a cardiac medical ward and a geriatric intensive care ward. Other ward characteristics and dates of observation are summarised in online supplemental appendix 1 .

Description of the dispensing and administration process. BCMA, barcode medication administration; COW, computer on wheels.

Supplementary data

Definitions.

We defined a policy deviation as the act of dispensing or administering a medicine that was not in accordance with the hospital policy. Task-related deviations were failures with tasks involving use of barcode scanning during dispensing and administration. Organisational policy deviations included violations of hospital medication management policies, for example dispensing the wrong dose of the medication in the patient drawer placed in the computer on wheels (COW). Technology-related factors included problems with the technological equipment (hardware and software) associated with the BCMA. Environmental factors were elements of the physical environment that affected the BCMA. Nurse-related factors were related to the practice or comments of individuals.

Data collection

One registered pharmacist and one fifth-year pharmacy student observed medication administration rounds between October 2019 and January 2020. The observers contacted the assigned nurse on the respective ward prior to the medication round, explained the purpose of the study and obtained written consent. Upon entering the patient room, the nurse informed the patient briefly about the presence of the observer and the purpose of the study. To minimise observation bias, 21 the observers remained silent during observation. No patient-identifiable data were recorded. The observer alerted the nurse if they became aware of a medication error with the potential to cause patient harm.

We used a digital observational tool (described later) to record quantitative data and checked for consistency by the research team. Data were collected using handheld tablets and directly sent to a secured server for storage. After completing the structured observations of the medication rounds, the observers documented additional qualitative field notes of the medication safety environment and any comments made by the nurse.

Data collection stopped when saturation was achieved, and the research team members evaluated that additional data would not lead to new information. 22 The observers periodically met with the research team to review observation data for this determination.

Development and piloting of the data collection tool

A digital observational tool, using secure web-based data survey software, 23 was developed to collect data during medication administration. The tool was piloted for 7 days, by two observers, who observed the administration of medications to 30 patients on two medical wards. While the pilot data were not included in the main study, they were discussed by our inter-professional research team, and each question in the observational tool was evaluated for relevance to the research question and consistency with current evidence. We developed separate data collection tools for oral and parenteral medications because the differences in their administration processes ( online supplemental appendices 2 and 3 ). The 28 questions in the oral and parenteral observational tool (14 questions in each) were aligned with the workflow described in the hospital policies and quantified data on the following:

• The total number of medications; scannable and scanned medications; number of scanned patient ID wristbands.
• Policy deviations with dispensing, labelling, storage or scanning.
• Technological problems with equipment or software.
• The storage of inpatients’ own medications.
• A free-text option in the tool was available to register the observers’ comments.

Quantitative data from both observational tools were merged; any string data were converted to numeric values. Scanning rates and frequency of policy deviations were analysed using descriptive statistics with IBM SPSS V.25. Qualitative data were analysed with inductive thematic analysis 24 through an iterative process. Two researchers coded the data assigning utterances to themes which were developed as they emerged from the data. The researchers discussed the manner in which the data fitted in the themes to reach joint consensus. Following the separate analysis of quantitative and qualitative data, we integrated the two data sets using a triangulated approach. 25 26 Key findings from both data sets were identified and complimentary findings were compared to enhance validity and provide a deeper understanding of policy deviations and their causes. The integrated findings were then categorised according to the five elements of the SEIPS model. 20

A total of 44 nurses were observed while preparing and administering medications; 29 during the morning and 15 during the evening medication rounds. We observed the administration of 884 medications (mean per patient, 4.2; range, 0 to 14) to 213 patients ( table 1 ). In total, 133 patients (62%) received oral medications only, 59 patients (28%) received both oral and parenteral, while 21 patients (10%) received only parenteral medications.

Characteristics of the observed barcode medication administration

Task-related policy deviations

Data source: observational tool.

We registered how nurses used BCMA during dispensing and administration. Task-related policy deviations affected 140 patients (66%) during medication dispensing and 152 patients (71%) during medication administration, illustrated in figure 2 . During administration, we identified three variations in nurses’ BCMA use which resulted in deviations: nurses did not use BCMA; nurses partially used BCMA; nurses used BCMA correctly, but deviations still occurred.

Task-related policy deviations with barcode medication administration. BCMA, barcode medication administration; COW, computer on wheels.

Organisational policy deviations

Data source: observational tool, field notes and nurses’ comments.

Organisational deviations were deviations from the medication management policies. In terms of medication administration deviations, these arose with not scanning 29% medications and 20% patient ID wristband ( table 1 ).

We identified 10 types of policy deviations during the dispensing process. The most frequent were medication not dispensed (n=80 patients), barcode label missing (n=70 patients) and wrong dose dispensed (n=30 patients). Dispensing deviations and their connection to potential medication errors are listed in table 2 . All data in table 2 are presented as deviations, although three of these deviations also classify as actual medication errors including wrong medication dispensed, wrong dose dispensed, and medication not dispensed and not administered which is a medication omission. These deviations in the COW were often revealed after the nurse had entered the patient room and resulted in a prolonged and frequently interrupted administration, which led to medication omission for 25 patients. For 11 patients, scanning in the eMAR prevented administration of the wrongly dispensed medication. The observer intervened on one occasion when a nurse dispensed a wrong (look-alike) medication from the medication room and intended to give to the patient.

Organisational policy deviations with barcode medication administration and their connection to potential medication errors

*The number of deviations refers to one deviation of the same type per patient even if more deviations of same type exist with one patient, for example, if one patient had wrong dose dispensed for two medications, this was counted as one deviation.

†Deviations which also classify as actual medication errors.

COW, computer on wheels; eMAR, electronic Medication Administration Record.

We also observed deviations from the storage of patients’ own medication (home-brought). According to policy, patients’ own medication should be stored in the COW or the medication room. We registered a 96% deviation rate from this policy ( table 2 ). Patients’ own medications were not integrated in the BCMA and were not barcoded or scanned.

Technology-related factors

Data source: observational tool and field notes.

Technology-related factors were registered with the observational tool and deviations were found in 38 observations (18%). These included low laptop battery in 28 observations (13%), system freezing in seven observations (3%), malfunctioning barcode scanner in two observations and the barcode scanner was unavailable for administration in one observation ( online supplemental appendix 4 ). Software problems included slow response and the need for multiple clicking after scanning each medication. Nurses used the laptop mousepad to navigate the eMAR, and this extensive clicking was perceived by the nurses as frustrating. The size of the COW was deemed to slow the administration process and lead to deviations.

Environmental factors

Medication rooms were located some distance from the nursing stations and patient rooms. The nurses ran back and forth to the medication room multiple times during an administration round to rectify deviations in the COW. Other disruptive environmental factors affecting the BCMA workflow were the fact that the patient drawers were too small and could not contain all the patient medications. We also observed that the work surface of the COWs and at the nursing stations were often untidy and contained single-dose units from past administrations or falsely dispensed medications.

Nurse-related factors

Several nurses admitted that they did not use the barcode scanning equipment on a daily basis. If the ward was particularly busy, nurses tended to discard BCMA because they perceived it slowed down the medication administration. However, nurses who used BCMA regularly valued the automated medication verification because it confirmed that the right patient would receive the right medication.

Probable causes of BCMA policy deviations

The probable causes of BCMA deviations and their data sources are listed in table 3 . Under task-related deviations, the failure to scan medications during administration occured because scanning was discarded during dispensing; a non-streamlined workflow during administration was caused by a mismatch with the tasks required during administration. Causes for organisational deviations were associated with unclear or poorly described policies, health professionals unaware of policies or the policy was incompatible with workflow. Even when the policy was clear and excluding, deviations occurred; for example, the policy stated that only the prescribed dose should be dispensed, however occasionally whole tablet blisters were dispensed in the COW.

Probable causes to barcode medication administration policy deviations according to the SEIPS categories

BCMA, barcode medication administration; COW, computer on wheels; eMAR, electronic Medication Administration Record.

Probable causes for deviations associated with technology were poor or unclear charging routines, the scanner was not mobile but attached to the laptop, and software usability issues. In addition, the design of the COW, including its large/bulky size, sometimes prevented nurses from scanning the patient ID wristband at the bedside. Furthermore, the undersized patient drawer led to dispensing omission because there was insufficient capacity to store all the medicines. Nurse-related deviations were caused by the slow BCMA process, which led to refraining from scanning or to skip the technology use. These factors all conflicted with patient safety during medication dispensing and administration.

We observed policy deviations which affected 6 of 10 patients during dispensing and 7 of 10 patients during medication administration. The causes to policy deviations were related to a complex dispensing process, slow or cumbersome BCMA procedure, suboptimal technology design and non-specific policy description. Working with suboptimal solutions in a busy environment, it was hard for the nurses not to deviate from policies, which explains why deviations were normalised in practice.

Despite these imperfections, our findings suggest that when the scanning of medications and ID wristbands was used, it offered benefits to patient safety by preventing the administration of wrong dispensed medication for 5% of the patients.

The lack of standardised delivery of dispensed doses lead to several variations in how the medications were dispensed in the COW. Patterson et al 27 found that BCMA made it easier to anticipate others’ actions and detect erroneous actions. In our study, however, it was difficult for other nurses to take for granted that the medications dispensed by a fellow nurse were correct. To compensate for the uncertainty, the nurses had to manually reconfirm doses before administering to patients. This practice undermines the purpose of BCMA.

The scanning rates in our study, that is, 71% for medications, 91% for scannable doses and 80% for patient ID wristbands, are considerably lower than the 95% standard goal for scanning medications and patients. 28 In a recent observational study of BCMA at a UK hospital, Barakat and Franklin registered scanning rates for medications of 83%, scannable doses of 95% and patient verification of 100%. 29 Although Barakat and Franklin had a smaller sample size, their study was undertaken with a similar ward-stock dispensing process and BCMA technology design to our study, which makes the rates broadly comparable.

A recent national study of medication errors in Norwegian hospitals, where BCMA was not used, found that 70% of all medication errors occurred during the medication administration stage. 3 We suggest that many of these errors, such as wrong dose, wrong patient and wrong medication during administration, could have been avoided if BCMA had been implemented. However, even if the technology is used accurately, hospitals may still fail to achieve the full benefits of BCMA to patient safety and unintended consequences may arise from technology implementation, 18 both demonstrated in our findings. In the current study, the technology was used as intended in only half of medication administrations. These deviations often originated in the dispensing process, such as not dispensed medications, wrong medication dispensed and wrong dose dispensed, and consequentially resulted in new deviations even when the BCMA was used correctly during medication administration.

The availability of functioning hardware is essential for the BCMA to have a preventive effect on errors. We identified a reoccurring problem with laptops not being charged and borrowing of scanners across wards, but these were not the main cause of technology-related deviations. The most important cause was the design of the technology like the bulky COW and the fact that scanners were not wireless. Those design issues limited the staffs’ efficiency during medication administration. This may explain why 20% of patient ID wristbands were not scanned during observation. Others have also described the size of the medication cart getting in way of efficient use of BCMA. 4 18 One observational study concluded that nurses uniformly believed that manually confirming patient identity took less time than wheeling the large medication cart in the patient room. 27

The distant medication rooms indirectly affected patient safety because retrieving of missing medications in the COW took a long time and led to medication omissions. Other environmental factors were in direct conflict with patient safety. Dispensing omissions were unavoidable because medications larger in size (eg, eyedrops, inhalers or syringes) could not fit in the small pocket of the COW patient drawers. Such environmental characteristics have affected medication safety in other studies as well. 30

Our nurses also expressed that BCMA prolonged the time they spent on medication administration. Compared with others that used automated dispensing cabinets, 18 or pharmacy-operated dispensing, 12 it is important to stress that nurses in our study had more tasks to attend to during the dispensing process (eg, packaging, labelling, dispensing in the correct compartment of the patient drawer). This is likely to explain the high proportion of dispensing deviations in the current study.

This study demonstrates variations among nurses in their BCMA use: from not using the BCMA in entire administrations, to partial use, to those who were fully compliant. Much of the variability can be explained by doses lacking barcodes and that the policies allowed for too many variations in the workflow. In the study of Barakat and Franklin, the BCMA led to less variability in how nurses undertake medication administration. 29 Some of this difference may be explained by safety culture differences, for example, if the BCMA technology is not used by all nurses, such as found in our study, it could result in being a burden to the workflow rather than a safety initiative. Lyons et al 31 have also described a similar performance variability among nurses within the use of other medication administration technologies, and addressed that this adaptive behaviour could be a source of resilience, compensating for the weaknesses of the system, but raised concerns that it could also lead to unsatisfactory outcomes.

Implications

Having the advantage of studying the use of BCMA within the actual setting, this study may provide implications to technology implementation and strategies for improvement.

• Prior to implementation, hospitals should risk-assess policies and make institution-specific decisions on how to properly integrate the technology into their workflow.
• The scanning rates could be improved if a greater number of medications are scannable. One way to address this is for the pharmaceutical industry to barcode medications on the primary packaging. 32 This could reduce the workload for the nurses and the hospital pharmacy and increase the standardisation of the dispensing process across wards.
• Ward-based medication dispensing, which is associated with significantly more medication errors than a unit-based system, 33 should be evaluated for efficiency and safety.
• Redesigning technology to fit the nurses’ workflow, that is, replacing the cumbersome COW with a lightweight cart and mobile eMAR device, could create better experiences for nurses and compensate for the downsides of the currently implemented system.
• Greater attention to the usability and functionality of BCMA is required: override logs and scanning stats were not available within the BCMA system observed in this study, which limits the monitoring of the technology use significantly.
• Besides data monitoring, ongoing assessments of the actual use of the BCMA technology are mandatory as changes in policy and technology will lead to new deviations. 16 This could be accomplished through periodical observation of medication rounds, 13 34 which give an insight in the technology use with all the contextual factors in place, but also to involve end-users in making suggestions on improvement.
• Shared learning of BCMA practices between hospitals with similar systems is an important resource to improve knowledge, implementation, and staff motivation.

Strengths and limitations

The mixed-method approach provided insight into the nurses’ BCMA use and understanding of the context in which deviations occur. The added value of using both the qualitative and quantitative data was that it identified frequency of deviations and their probable causes. Our observational tool allowed the detection of ‘normal’ deviations in practice (eg, dispensing wrong dose of medications) that often remain undetected because they are not identified using standard methods such as incident reports and chart reviews. 35 Previous studies have demonstrated that BCMA can reduce medication error rates. 4 5 7 8 In our study, the identified policy deviations indicate that workarounds occur due to system flaws that produce latent conditions which could ultimately lead to serious medication errors. However, focusing on policy deviations rather than medication errors is also a limitation because there is no direct measure of the impact of BCMA to patient safety.

Other limitations are acknowledged. First, there could be differences among observers, either in their data collection or in their interpretation and knowledge of local policy. Observers were carefully trained in observational techniques 36–38 and familiarised with local medication management policies to minimise such effect. Second, the presence of an observer might have influenced the nurses to consciously or unconsciously modify their behaviour. 39 Nurses were aware of being observed while administering medications, and the expected change in behaviour would have been in the direction of better compliance with BCMA use. Some nurses indicated that they were using the technology because they were being observed. However, the findings associated with the medication dispensing were not affected by the observation because this activity took place prior to the observation period that is, usually undertaken by nurses from the previous shift.

We studied an eMAR paired with BCMA technology in a hospital with a traditional ward-based medication dispensing operated by nurses. It is likely that our data will not be generalisable to organisations that use a pharmacy-operated or automated medication dispensing. On the other hand, hospitals that use a ward-based dispensing system can value from our findings, as there is limited research on the BCMA technology use in a ward-based medication dispensing.

This study provides an in-depth understanding of how the BCMA is used in the clinical environment. We identified policy deviations for over half of the observations, such as not scanning the patients or the medications, omission of dispensing, or wrong dose dispensed. We also identified variations in how nurses used BCMA. Deviations were caused with unclear policies, policies that interfere with appropriate BCMA use, including the labor-intensive dispensing process, as well as problems with technology design. Our findings suggest that several factors in the work system need reassessment and adaptation to nurses’ workflow. Deviations are expected with technology implementation in any complex system. As such, analysing policy deviations in practice is an important method of identifying and addressing system weaknesses in order to achieve the full benefits of BCMA in terms of patient safety.

Acknowledgments

The authors thank the nursing staff for their participation in the study. We also would like to acknowledge the contributions provided by the staff from the Southern and Eastern Norway Pharmaceutical Trust and the Department of Information and Communication Technology at the hospital.

Contributors: AM and AGG conceived of the presented idea. KT, LM and AGG were involved in planning and supervising the work. AM took lead in the data collection, analysis and in writing the manuscript. All authors have read and approved the final version of the manuscript.

Funding: This study was internally funded.

Competing interests: None declared.

Provenance and peer review: Not commissioned; externally peer reviewed.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

Ethics statements, patient consent for publication.

Not required.

Ethics approval

The study was approved by the institutional data protection board.

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How AI tools help students—and their professors—in academic research

New systems can help surface relevant research papers and quickly understand what they have to say.

[Photo: Nikish Hiraman/peopleimages.com/Adobe Stock]

BY  Steven Melendez 7 minute read

For students and professional scholars alike, starting a new research project typically means digging through academic literature to understand what others have already written.

That can take a considerable amount of time, with researchers tracking down and combing through journal articles to begin their research and contextualize their own findings. But a growing collection of AI-powered tools aims to make that process easier. These new tools can help researchers more quickly find relevant papers, pull out relevant information from them, or both.

“It can be a really helpful way to get started with research, especially for students who aren’t familiar with the research process,” says Breanne Kirsch, director of the library at Illinois College. “As long as they’re taught how to use it in an ethical way, and that they can then expand beyond what it does.”

A tool called Elicit can help researchers conduct what are called systematic reviews , which involve going through copious amounts of published research to find an answer to a question, like how a particular drug affects a medical condition. “It’s all very, very manual,” says James Brady, head of engineering at Elicit. “It takes teams of people many months, and you know, costs hundreds of thousands or millions of dollars to do these things.” 

Elicit can make that process much faster, and also help researchers by quickly finding and summarizing published papers related to a particular question. It can also generate tables describing a whole set of relevant papers, with columns for data points like algorithms and statistical techniques used, variables examined, and the number of participants in experiments. 

The company recommends researchers still look at the original papers, and Brady emphasizes that the tool doesn’t replace the human judgment and analysis necessary to scientific research. “It’s not like you take the final step of Elicit and hit the publish button and then it ends up in Nature or something,” he says, but it can still greatly speed the process of sifting through and understanding prior work.

Understanding how AI can help academic research is part of a larger industry question of how and when the technology can replace or supplement traditional web search tools. And since the 1990s , computer scientists have realized that the academic publishing landscape—where scholars cite each other’s papers and publish in journals with a particular reputation in a particular field—isn’t that different from the internet ecosystem . That means techniques for finding relevant materials, minimizing AI errors and hallucinations, and presenting useful and verifiable results to the user may transfer from academia to the broader web.

ABOUT THE AUTHOR

Steven Melendez is an independent journalist living in New Orleans.   More

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Report on BARCODE TECHNOLOGY

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… (ICSPS), 2010 2nd …

Md Kafiul Islam

International Journal of Science Technology & Engineering

IJSTE - International Journal of Science Technology and Engineering

Mobile cameras are being used now-a-days to scan barcodes to retrieve the product details. But the drawback is mobile cameras are made by a charge coupled device which is does not have the ability to handle out of focus and blur images. In this project, out of focus and blur images are restored using a dynamic template matching algorithm using directed graphical model. The directed graphical model is used to determine the relationship between state variable from blurred waveform at specific blur level and observation sequence. A varying program based inference algorithm is used to recover the optimal state sequence and hence the system works in real-time.

Proceedings / IEEE Workshop on Applications of Computer Vision. IEEE Workshop on Applications of Computer Vision

Ender Tekin

Most camera-based systems for finding and reading barcodes are designed to be used by sighted users (e.g. the Red Laser iPhone app), and assume the user carefully centers the barcode in the image before the barcode is read. Blind individuals could benefit greatly from such systems to identify packaged goods (such as canned goods in a supermarket), but unfortunately in their current form these systems are completely inaccessible because of their reliance on visual feedback from the user.To remedy this problem, we propose a computer vision algorithm that processes several frames of video per second to detect barcodes from a distance of several inches; the algorithm issues directional information with audio feedback (e.g. "left," "right") and thereby guides a blind user holding a webcam or other portable camera to locate and home in on a barcode. Once the barcode is detected at sufficiently close range, a barcode reading algorithm previously developed by the authors...

Journal of Computer Science IJCSIS , Rizwan Mukati

Barcodes and RFIDs, the two most frequently used " Automatic Identification and Data Capture (AIDC) " techniques based on " Assigned " properties, are being used nearly for the last five decades, in the supply-chain, distribution and manufacturing processes. In this paper, an in-depth look, their pros and cons and their suitability in the given processes, have been presented.

Proceedings / Canadian Conference on Computer and Robot Vision. Canadian Conference on Computer and Robot Vision

The 1D barcode is a ubiquitous labeling technology, with symbologies such as UPC used to label approximately 99% of all packaged goods in the US. It would be very convenient for consumers to be able to read these barcodes using portable cameras (e.g. mobile phones), but the limited quality and resolution of images taken by these cameras often make it difficult to read the barcodes accurately. We propose a Bayesian framework for reading 1D barcodes that models the shape and appearance of barcodes, allowing for geometric distortions and image noise, and exploiting the redundant information contained in the parity digit. An important feature of our framework is that it doesn't require that every barcode edge be detected in the image. Experiments on a publicly available dataset of barcode images explore the range of images that are readable, and comparisons with two commercial readers demonstrate the superior performance of our algorithm.

Yuri Matveev , Kukharev Georgy , Georgy Kukharev

In this paper we propose a simple method for generating standard type linear barcodes from facial images. The method uses the difference in gradients of image brightness. It involves averaging the gradients into a limited number of intervals, quantization of the results into the range of decimal numbers from 0 to 9, and table conversion into the final barcode. The proposed solution is computationally low-cost and does not require the use of any specialized image processing software, which makes it possible to generate facial barcodes in mobile systems. Results of tests conducted on the Face94 database and a database of composite faces at different ages show that the proposed method is a new solution for use in real-world practice. It ensures the stability of the generated barcodes against changes of scale, pose and mirroring of facial images, as well as changes of facial expressions and shadows on faces from local lighting.

IJSRD - International Journal for Scientific Research and Development

In this Review paper discusses about the last few years, Two-Dimensional (2D) codes to get the importance in the industrial sector, and the greater storage capacity information gradually replace many applications of One Dimensional Barcode. Quick response (QR) codes are one of the most popular types of 2D codes. QR Code widely used in many commercial applications due to their highspeed decoding.

International Journal of Latest Technology in Engineering, Management & Applied Science -IJLTEMAS (www.ijltemas.in)

This paper presents designing a Color Barcode for Mobile Applications, 2D barcodes have gained popularity as one of the key pervasive technologies for mobile applications on smart phones. They can be used as shortcuts to URL links, a means to store contact information for easy transfer admission tickets or boarding passes and tokens for retrieving digital information, such as public transportation timetables or fresh produce production information, either directly from the barcode itself or through a networked database server. Most mobile applications use black-and-white 2D barcodes that carry only a limited amount of encoded data. A color barcode framework for mobile phone applications by exploiting the spectral diversity aborted by the cyan (C), magenta (M), and yellow (Y) print colorant channels commonly used for color printing and the complementary red (R),green (G), and blue (B) channels, respectively, used for capturing color images. Specifically, we exploit this spectral diversity to realize a threefold increase in the data rate by encoding independent data in the C, M, and Y print colorant channels and decoding the data from the complementary R, G and B channels captured via a mobile phone camera. To mitigate the effect of cross-channel interference among the printcolorant and capture color channels, we develop an algorithm for interference cancellation. To estimate the model parameters required for crosschannel interference cancellation, we propose two alternative methodologies: a pilot block approach that uses suitable selections of colors for the synchronization blocks and an expectation maximization approach that estimates the parameters from regions encoding the data.

Student attendance play significant role in order to justify academic outcome of a student and college as overall. Unfortunately, there is no automated attendance record keeping application available in colleges. There is a need for a tool to systematically keep the students attendance record due to increasing number of college students The project that we are going to make is to help the teachers in our college to avoid maintaining the registry book. This project uses a barcode scanner. B.B.S.A.S uses Barcode scanner to take the attendance of students entering the lab. Each student's ID card will have a barcode at the back side of it. This barcode contains unique data of the student such as roll number, branch and year. Etc. Student will scan their barcode at the end so that the student can't cheat. The display screen will show the attendance of the particular student after scanning his/her barcode. Teachers and administrator will only have access to the system with their respective login ID's and passwords.

International Journals for Researchers [ER Publication, WOAR Journals, IJEAS and IJEART]

 Abstract— Radio frequency identification (RFID) is a rapidly emerging technology which allows productivity and convenience. Radio Frequency Identification (RFID) is a new generation of Auto Identification and Data collection technology which helps to automate business processes and allows identification of large number of tagged objects like books, using radio waves. This paper proposes RFID Based University Library Management System that would allow fast transaction flow and will make it easy to handle the issue and return of books from the library without much intervention of manual book keeping which benefits by adding properties of traceability and security. The proposed system is based on RFID readers and passive RFID tags that are able to electronically store information that can be read with the help of the RFID reader. This system would be able to issue and return books via RFID tags and also calculates the corresponding fine associated with the time period of the absence of the book from the library database.

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MIT engineers’ new theory could improve the design and operation of wind farms

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The blades of propellers and wind turbines are designed based on aerodynamics principles that were first described mathematically more than a century ago. But engineers have long realized that these formulas don’t work in every situation. To compensate, they have added ad hoc “correction factors” based on empirical observations.

Now, for the first time, engineers at MIT have developed a comprehensive, physics-based model that accurately represents the airflow around rotors even under extreme conditions, such as when the blades are operating at high forces and speeds, or are angled in certain directions. The model could improve the way rotors themselves are designed, but also the way wind farms are laid out and operated. The new findings are described today in the journal Nature Communications , in an open-access paper by MIT postdoc Jaime Liew, doctoral student Kirby Heck, and Michael Howland, the Esther and Harold E. Edgerton Assistant Professor of Civil and Environmental Engineering.

“We’ve developed a new theory for the aerodynamics of rotors,” Howland says. This theory can be used to determine the forces, flow velocities, and power of a rotor, whether that rotor is extracting energy from the airflow, as in a wind turbine, or applying energy to the flow, as in a ship or airplane propeller. “The theory works in both directions,” he says.

Because the new understanding is a fundamental mathematical model, some of its implications could potentially be applied right away. For example, operators of wind farms must constantly adjust a variety of parameters, including the orientation of each turbine as well as its rotation speed and the angle of its blades, in order to maximize power output while maintaining safety margins. The new model can provide a simple, speedy way of optimizing those factors in real time.

“This is what we’re so excited about, is that it has immediate and direct potential for impact across the value chain of wind power,” Howland says.

Modeling the momentum

Known as momentum theory, the previous model of how rotors interact with their fluid environment — air, water, or otherwise — was initially developed late in the 19th century. With this theory, engineers can start with a given rotor design and configuration, and determine the maximum amount of power that can be derived from that rotor — or, conversely, if it’s a propeller, how much power is needed to generate a given amount of propulsive force.

Momentum theory equations “are the first thing you would read about in a wind energy textbook, and are the first thing that I talk about in my classes when I teach about wind power,” Howland says. From that theory, physicist Albert Betz calculated in 1920 the maximum amount of energy that could theoretically be extracted from wind. Known as the Betz limit, this amount is 59.3 percent of the kinetic energy of the incoming wind.

But just a few years later, others found that the momentum theory broke down “in a pretty dramatic way” at higher forces that correspond to faster blade rotation speeds or different blade angles, Howland says. It fails to predict not only the amount, but even the direction of changes in thrust force at higher rotation speeds or different blade angles: Whereas the theory said the force should start going down above a certain rotation speed or blade angle, experiments show the opposite — that the force continues to increase. “So, it’s not just quantitatively wrong, it’s qualitatively wrong,” Howland says.

The theory also breaks down when there is any misalignment between the rotor and the airflow, which Howland says is “ubiquitous” on wind farms, where turbines are constantly adjusting to changes in wind directions. In fact, in an  earlier paper in 2022, Howland and his team found that deliberately misaligning some turbines slightly relative to the incoming airflow within a wind farm significantly improves the overall power output of the wind farm by reducing wake disturbances to the downstream turbines.

In the past, when designing the profile of rotor blades, the layout of wind turbines in a farm, or the day-to-day operation of wind turbines, engineers have relied on ad hoc adjustments added to the original mathematical formulas, based on some wind tunnel tests and experience with operating wind farms, but with no theoretical underpinnings.

Instead, to arrive at the new model, the team analyzed the interaction of airflow and turbines using detailed computational modeling of the aerodynamics. They found that, for example, the original model had assumed that a drop in air pressure immediately behind the rotor would rapidly return to normal ambient pressure just a short way downstream. But it turns out, Howland says, that as the thrust force keeps increasing, “that assumption is increasingly inaccurate.”

And the inaccuracy occurs very close to the point of the Betz limit that theoretically predicts the maximum performance of a turbine — and therefore is just the desired operating regime for the turbines. “So, we have Betz’s prediction of where we should operate turbines, and within 10 percent of that operational set point that we think maximizes power, the theory completely deteriorates and doesn’t work,” Howland says.

Through their modeling, the researchers also found a way to compensate for the original formula’s reliance on a one-dimensional modeling that assumed the rotor was always precisely aligned with the airflow. To do so, they used fundamental equations that were developed to predict the lift of three-dimensional wings for aerospace applications.

The researchers derived their new model, which they call a unified momentum model, based on theoretical analysis, and then validated it using computational fluid dynamics modeling. In followup work not yet published, they are doing further validation using wind tunnel and field tests.

Fundamental understanding

One interesting outcome of the new formula is that it changes the calculation of the Betz limit, showing that it’s possible to extract a bit more power than the original formula predicted. Although it’s not a significant change — on the order of a few percent — “it’s interesting that now we have a new theory, and the Betz limit that’s been the rule of thumb for a hundred years is actually modified because of the new theory,” Howland says. “And that’s immediately useful.” The new model shows how to maximize power from turbines that are misaligned with the airflow, which the Betz limit cannot account for.

The aspects related to controlling both individual turbines and arrays of turbines can be implemented without requiring any modifications to existing hardware in place within wind farms. In fact, this has already happened, based on earlier work from Howland and his collaborators two years ago that dealt with the wake interactions between turbines in a wind farm, and was based on the existing, empirically based formulas.

“This breakthrough is a natural extension of our previous work on optimizing utility-scale wind farms,” he says, because in doing that analysis, they saw the shortcomings of the existing methods for analyzing the forces at work and predicting power produced by wind turbines. “Existing modeling using empiricism just wasn’t getting the job done,” he says.

In a wind farm, individual turbines will sap some of the energy available to neighboring turbines, because of wake effects. Accurate wake modeling is important both for designing the layout of turbines in a wind farm, and also for the operation of that farm, determining moment to moment how to set the angles and speeds of each turbine in the array.

Until now, Howland says, even the operators of wind farms, the manufacturers, and the designers of the turbine blades had no way to predict how much the power output of a turbine would be affected by a given change such as its angle to the wind without using empirical corrections. “That’s because there was no theory for it. So, that’s what we worked on here. Our theory can directly tell you, without any empirical corrections, for the first time, how you should actually operate a wind turbine to maximize its power,” he says.

Because the fluid flow regimes are similar, the model also applies to propellers, whether for aircraft or ships, and also for hydrokinetic turbines such as tidal or river turbines. Although they didn’t focus on that aspect in this research, “it’s in the theoretical modeling naturally,” he says.

The new theory exists in the form of a set of mathematical formulas that a user could incorporate in their own software, or as an open-source software package that can be freely downloaded from GitHub . “It’s an engineering model developed for fast-running tools for rapid prototyping and control and optimization,” Howland says. “The goal of our modeling is to position the field of wind energy research to move more aggressively in the development of the wind capacity and reliability necessary to respond to climate change.”

The work was supported by the National Science Foundation and Siemens Gamesa Renewable Energy.

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• Unified momentum model software
• Howland Lab
• Department of Civil and Environmental Engineering

Related Topics

• Civil and environmental engineering
• Renewable energy
• Climate change

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