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Academic literature on the topic 'Transactional Records Access Clearinghouse'
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Journal articles on the topic "Transactional Records Access Clearinghouse"
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Kirksey, J. Jacob, Carolyn Sattin-Bajaj, Michael A. Gottfried, Jennifer Freeman, and Christopher S. Ozuna. "Deportations Near the Schoolyard: Examining Immigration Enforcement and Racial/Ethnic Gaps in Educational Outcomes." AERA Open 6, no. 1 (January 2020): 233285841989907. http://dx.doi.org/10.1177/2332858419899074.
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With increased tensions and political rhetoric surrounding immigration enforcement in the United States, schools are facing greater challenges in ensuring support for their students of immigrant and Latino/a origin. This study examined the associations between deportations near school districts and racial/ethnic gaps in educational outcomes in school districts across the country. With data from the Stanford Educational Data Archive, the Civil Rights Data Collection, and the Transactional Records Access Clearinghouse, this study used longitudinal, cross-sectional analyses and found that in the years when districts had more deportations occurring within 25 miles, White-Latino/a gaps were larger in math achievement and rates of chronic absenteeism. No associations were found for gaps in English language arts achievement or rates of bullying. Implications for researchers, policymakers, and school leaders are discussed.
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Skatova, Anya, Kate Shiells, and Andy Boyd. "Attitudes towards transactional data donation and linkage in a longitudinal population study: evidence from the Avon Longitudinal Study of Parents and Children." Wellcome Open Research 4 (June 9, 2021): 192. http://dx.doi.org/10.12688/wellcomeopenres.15557.2.
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Background: Commercial transaction records, such as data collected through banking and retail loyalty cards, present a novel opportunity for longitudinal population studies to capture data on participants’ real-world behaviours and interactions. However, little is known about participant attitudes towards donating transactional records for this purpose. This study aimed to: (i) explore the attitudes of longitudinal population study participants towards sharing their transactional records for health research and data linkage; and (ii) explore the safeguards that researchers should consider implementing when looking to request transactional data from participants for data linkage studies. Methods: Participants in the Avon Longitudinal Study of Parents and Children were invited to a series of three focus groups with semi-structured discussions designed to elicit opinions. Through asking participants to attend three focus groups we aimed to facilitate more in-depth discussions around the potentially complex topic of data donation and linkage. Thematic analysis was used to sort data into overarching themes addressing the research questions. Results: Participants (n= 20) expressed a variety of attitudes towards data linkage, which were associated with safeguards to address concerns. This data was sorted into three themes: understanding, trust, and control. We discuss the importance of explaining the purpose of data linkage, consent options, who the data is linked with and sensitivities associated with different parts of transactional data. We describe options for providing further information and controls that participants consider should be available when studies request access to transactional records. Conclusions: This study provides initial evidence on the attitudes and concerns of participants of a longitudinal cohort study towards transactional record linkage. The findings suggest a number of safeguards which researchers should consider when looking to recruit participants for similar studies, such as the importance of ensuring participants have access to appropriate information, control over their data, and trust in the organisation.
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Skatova, Anya, Kate Shiells, and Andy Boyd. "Attitudes towards transactional data donation and linkage in a longitudinal population study: evidence from the Avon Longitudinal Study of Parents and Children." Wellcome Open Research 4 (December 3, 2019): 192. http://dx.doi.org/10.12688/wellcomeopenres.15557.1.
Full textAbstract:
Background: Commercial transaction records, such as data collected through banking and retail loyalty cards, present a novel opportunity for longitudinal population studies to capture data on participants’ real-world behaviours and interactions. However, little is known about participant attitudes towards donating transactional records for this purpose. This study aimed to: (i) explore the attitudes of longitudinal population study participants towards sharing their transactional records for health research and data linkage; and (ii) explore the safeguards that researchers should consider implementing when looking to request transactional data from participants for data linkage studies. Methods: Participants in the Avon Longitudinal Study of Parents and Children were invited to a series of three focus groups with semi-structured discussions designed to elicit opinions. Through asking participants to attend three focus groups we aimed to facilitate more in-depth discussions around the potentially complex topic of data donation and linkage. Thematic analysis was used to sort data into overarching themes addressing the research questions. Results: Participants (n= 20) expressed a variety of attitudes towards data linkage, which were associated with safeguards to address concerns. This data was sorted into three themes: information, trust, and control. We discuss the importance of explaining the purpose of data linkage, consent options, who the data is linked with and sensitivities associated with different parts of transactional data. We describe options for providing further information and controls that participants consider should be available when studies request access to transactional records. Conclusions: This study provides initial evidence on the attitudes and concerns of participants of a longitudinal cohort study towards transactional record linkage. The findings suggest a number of safeguards which researchers should consider when looking to recruit participants for similar studies, such as the importance of ensuring participants have access to appropriate information, control over their data, and trust in the organisation.
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Sonkamble, Rahul Ganpatrao, Anupkumar M. Bongale, Shraddha Phansalkar, Abhishek Sharma, and Shailendra Rajput. "Secure Data Transmission of Electronic Health Records Using Blockchain Technology." Electronics 12, no. 4 (February 17, 2023): 1015. http://dx.doi.org/10.3390/electronics12041015.
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Electronic Health Records (EHR) serve as a solid documentation of health transactions and as a vital resource of information for healthcare stakeholders. EHR integrity and security issues, however, continue to be intractable. Blockchain-based EHR architectures, however, address the issues of integrity very effectively. In this work, we suggest a decentralized patient-centered healthcare data management (PCHDM) with a blockchain-based EHR framework to address issues of confidentiality, access control, and privacy of record. This patient-centric architecture keeps the patient at the center of control for secured storage of EHR data. It is effective in the storage environment with the interplanetary file system (IPFS) and blockchain technology. In order to control unauthorized users, the proposed secure password authentication-based key exchange (SPAKE) implements smart contract-based access control to EHR transactions and access policies. The experimental setup comprises four hyperledger fabric nodes with level DB database and IPFS off-chain storage. The framework was evaluated using the public hepatitis dataset, with parameters such as block creation time, transactional computational overhead with encryption key size, and uploading/downloading time with EHR size. The framework enables patient-centric access control of the EHR with the SPAKE encryption algorithm.
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Mandal, Ajaya, Prakriti Dumaru, Sagar Bhandari, Shreeti Shrestha, and Subarna Shakya. "Decentralized Electronic Health Record System." Journal of the Institute of Engineering 15, no. 1 (February 16, 2020): 77–80. http://dx.doi.org/10.3126/jie.v15i1.27716.
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With a view to overcome the shortcomings of traditional Electronic Health Record (EHR) system so as to assure the interoperability by providing open access to sensitive health data, while still preserving personal data privacy, anonymity and avoiding data misuse, Decentralized Electronic Health Record System was developed. The aforementioned issue concerning traditional EHR system can be addressed by implication of emerging technology of the era namely Block chain, together with Inter Planetary File System (IPFS) which enables data sharing in decentralized and transactional fashion, thereby maintaining delicate balance between privacy and accessibility of electronic health records. A block chain based EHR system has been built for secure, efficient and interoperable access to medical records by both patients and doctors while preserving privacy of the sensitive patient’s information. Patients can easily and comprehensively access to their medical records across providers and treatment sites using unique properties of block chain and decentralized storage. A separate portal for both the patients and doctors has been built enabling the smart contracts to handle further interaction between doctors and patients. So, in this system, it is demonstrated how principles of decentralization and block chain architectures could contribute to EHR system using Ethereum smart contracts and IPFS to orchestrate a suitable system governing the medical record access while providing patients with comprehensive record review along with consideration for audit ability and data sharing.
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Mehrad, Aida, Jordi Fernández-Castro, and Maria Pau González Gómez de Olmedo. "A systematic review of leadership styles, work engagement and organizational support." International Journal of Research in Business and Social Science (2147- 4478) 9, no. 4 (July 3, 2020): 66–77. http://dx.doi.org/10.20525/ijrbs.v9i4.735.
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Work engagement is one of the critical factors at an organization, so considering some factors such as leadership styles and organizational support is important. Lack of attention to these factors can lead to undesirable environments for workers. The purpose of this study is to conduct a systematic review based on these variables. Data for this research were gathered from databases of Web of Knowledge, psycarticles, Scopus, psycinfo, Web of Science, and Google Scholar. A total of 165 records were identified in databases. 15 records were discovered in other sources. 149 records remained after deleting duplicates. 117 of these records were examined, 52 registers excluded. 65 complete articles were chosen to be evaluated, and after 10 completed articles had been excluded, 55 studies ultimately remained for inclusion in the synthesis. Overall, leadership styles (transformational leadership and transactional leadership) and organizational support were found as two imperative organizational factors to access better outcomes at the workplace.
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Chioma Susan Nwaimo, Ayodeji Enoch Adegbola, and Mayokun Daniel Adegbola. "Predictive analytics for financial inclusion: Using machine learning to improve credit access for under banked populations." Computer Science & IT Research Journal 5, no. 6 (June 7, 2024): 1358–73. http://dx.doi.org/10.51594/csitrj.v5i6.1201.
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This paper explores the application of predictive analytics and machine learning techniques to enhance credit assessment and lending practices. By leveraging alternative data sources, such as mobile phone usage, social media activity, and transactional records, machine learning models can provide more accurate credit risk evaluations for individuals with limited traditional financial histories. The study demonstrates the efficacy of these models through empirical analysis, showcasing their potential to reduce default rates while increasing the approval rates for credit applicants. Furthermore, the paper discusses the ethical considerations and potential biases associated with the use of non-traditional data in credit scoring. The findings underscore the transformative impact of machine learning in fostering financial inclusion, offering practical insights for policymakers, financial institutions, and technology developers aiming to bridge the credit gap for under banked communities. This paper delves into the transformative potential of predictive analytics and machine learning in enhancing financial inclusion by improving credit access for under banked populations. Traditional credit scoring methods often fail to accurately assess the creditworthiness of individuals lacking conventional financial histories, thereby excluding a significant portion of the population from financial services. By incorporating alternative data sources such as mobile phone usage, social media interactions, utility payments, and transactional records, machine learning models can offer more comprehensive and precise credit risk evaluations. The research methodology involves developing and testing various machine learning algorithms, including decision trees, random forests, and neural networks, to predict creditworthiness. The models are trained and validated on datasets that include both traditional financial data and alternative data sources. The performance of these models is measured against standard metrics such as accuracy, precision, recall, and the area under the receiver operating characteristic (ROC) curve. Empirical results indicate that models utilizing alternative data significantly outperform traditional credit scoring methods, leading to higher approval rates for credit applicants while maintaining or improving risk management standards. Keywords: Financial, Inclusion, Predictive, Analytics, Machine Learning, Alternative Data.
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Padilla, Rubelyn C. "Assessment of Library Users’ Problems on Transactional Procedures: Basis for Library Management System Development." International Journal of Scientific and Management Research 05, no. 06 (2022): 10–17. http://dx.doi.org/10.37502/ijsmr.2022.5602.
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This research aimed at assessing problems encountered by library users- librarian, staff, students, and teachers- on the different library transactional procedures as basis for the development and design of a Library Management System for Cagayan State University-Piat in the Philippines. The study utilized the descriptive design in determining the degree of seriousness of the problems encountered by the respondents in using the existing library transactions, and the interventions that can be done to address the problems encountered by the respondents. Findings revealed that the problems encountered by the library users in the manual operations of the library in terms of borrowing, returning and searching library materials are “Very Serious”. On the part of the library staff, the issues on security of records, cataloguing, borrowing, returning, searching, inventory of library materials and generation of reports are considered “Serious”. Using Waterfall Model, the system was developed with the aid of software and hardware requirements. The library system developed “very efficiently” stored the library records in the database secured with password, systematically classified the materials, save time in entering information of library materials, displayed for duplication of accession numbers, monitored the borrowed and returned books, systematically displayed inventory of materials, and saved time in generating accurate library reports. It can be concluded that the proposed library system can provide better and easier access to the different transactions in the library and provide convenience to the library staff and library users in the different transactions.
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Welekar, Rashmi, Farhadeeba Shaikh, Abhijit Chitre, Kirti Wanjale, Shabana Pathan, and Anil Kumar. "An advanced cloud based framework for privacy and security in medical data using cryptographic method." Journal of Discrete Mathematical Sciences and Cryptography 26, no. 5 (2023): 1585–96. http://dx.doi.org/10.47974/jdmsc-1826.
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The exchange of medical information has been drastically altered by patient-centered developments such as personal health records (PHR). By giving patients a place to handle their own PHR on a unified transactional platform, personal health record (PHR) services increase the efficiency with which medical information may be kept, accessed, and transferred. With the ultimate objective of providing patients with total surveillance under data, our findings is focused on creating a state-of-the-art infrastructure for the safe transfer of personal health data via cloud computing. Patients have the option of encrypting their PHR files, which provides an additional layer of security and allows them to set access control limits such as who has access to their files and to what degree. When data is encrypted in the cloud, only approved users may access it. Using cloud-based platforms to share health records raises concerns over confidentiality and privacy, which are addressed by the proposed method. Patients may still benefit from data interchange for the goal of better healthcare thanks to the framework’s provision of an encrypted PHR file option. This framework may accommodate attribute-based encryption (ABE) and other kinds of granular security. These measures ensure that people may continue to have access to, and make changes to, their own medical data, even when they are stored on the cloud. This article presents research that attempts to meet the demands of patients while also providing a safe method of transferring individual health information through cloud computing.
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Mora, E., M. Gemmani, J. Zayas-Castro, and D. A. Martinez. "Uncovering Hospitalists’ Information Needs from Outside Healthcare Facilities in the Context of Health Information Exchange Using Association Rule Learning." Applied Clinical Informatics 06, no. 04 (2015): 684–97. http://dx.doi.org/10.4338/aci-2015-06-ra-0068.
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SummaryBackground: Important barriers to health information exchange (HIE) adoption are clinical work-flow disruptions and troubles with the system interface. Prior research suggests that HIE interfaces providing faster access to useful information may stimulate use and reduce barriers for adoption; however, little is known about informational needs of hospitalists.Objective: To study the association between patient health problems and the type of information requested from outside healthcare providers by hospitalists of a tertiary care hospital.Methods: We searched operational data associated with fax-based exchange of patient information (previous HIE implementation) between hospitalists of an internal medicine department in a large urban tertiary care hospital in Florida, and any other affiliated and unaffiliated healthcare provider. All hospitalizations from October 2011 to March 2014 were included in the search. Strong association rules between health problems and types of information requested during each hospitalization were discovered using Apriori algorithm, which were then validated by a team of hospitalists of the same department.Results: Only 13.7% (2 089 out of 15 230) of the hospitalizations generated at least one request of patient information to other providers. The transactional data showed 20 strong association rules between specific health problems and types of information exist. Among the 20 rules, for example, abdominal pain, chest pain, and anaemia patients are highly likely to have medical records and outside imaging results requested. Other health conditions, prone to have records requested, were lower urinary tract infection and back pain patients.Conclusions: The presented list of strong co-occurrence of health problems and types of information requested by hospitalists from outside healthcare providers not only informs the implementation and design of HIE, but also helps to target future research on the impact of having access to outside information for specific patient cohorts. Our data-driven approach helps to reduce the typical biases of qualitative research.
Books on the topic "Transactional Records Access Clearinghouse"
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Clearinghouse, Transactional Records Access. Transactional Records Access Clearinghouse: TRAC. Syracuse, N.Y: Transactional Records Access Clearinghouse, Syracuse University, 1996.
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