A Data Management Approach to Quality Assurance Using Colorectal Carcinoma Reports From Two Institutions as a Model

2007 ◽  
Vol 2007 ◽  
pp. 11-12
Author(s):  
S.S. Raab
Keyword(s):  
Quality Assurance ◽  
Colorectal Carcinoma ◽  
Data Management ◽  
Management Approach

Designing Information Product (IP) Maps On the Process of Data Processing and Academic Information

2017 ◽  
Vol 4 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Diana Effendi
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Management ◽  
Information Quality ◽  
Quality Data ◽  
Management Approach ◽  
Quality Of Data ◽  
Information Product ◽  
Academic Activities

Information Product Approach (IP Approach) is an information management approach. It can be used to manage product information and data quality analysis. IP-Map can be used by organizations to facilitate the management of knowledge in collecting, storing, maintaining, and using the data in an organized. The  process of data management of academic activities in X University has not yet used the IP approach. X University has not given attention to the management of information quality of its. During this time X University just concern to system applications used to support the automation of data management in the process of academic activities. IP-Map that made in this paper can be used as a basis for analyzing the quality of data and information. By the IP-MAP, X University is expected to know which parts of the process that need improvement in the quality of data and information management.   Index term: IP Approach, IP-Map, information quality, data quality. REFERENCES[1] H. Zhu, S. Madnick, Y. Lee, and R. Wang, “Data and Information Quality Research: Its Evolution and Future,” Working Paper, MIT, USA, 2012.[2] Lee, Yang W; at al, Journey To Data Quality, MIT Press: Cambridge, 2006.[3] L. Al-Hakim, Information Quality Management: Theory and Applications. Idea Group Inc (IGI), 2007.[4] “Access : A semiotic information quality framework: development and comparative analysis : Journal ofInformation Technology.” [Online]. Available: http://www.palgravejournals.com/jit/journal/v20/n2/full/2000038a.html. [Accessed: 18-Sep-2015].[5] Effendi, Diana, Pengukuran Dan Perbaikan Kualitas Data Dan Informasi Di Perguruan Tinggi MenggunakanCALDEA Dan EVAMECAL (Studi Kasus X University), Proceeding Seminar Nasional RESASTEK, 2012, pp.TIG.1-TI-G.6.

The advantages of an Ontology-Based Data Management approach: openness, interoperability and data quality

2016 ◽  
Vol 108 (1) ◽  
pp. 441-455 ◽  
Author(s):  
Cinzia Daraio ◽  
Maurizio Lenzerini ◽  
Claudio Leporelli ◽  
Paolo Naggar ◽  
Andrea Bonaccorsi ◽  
...  
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Management Approach

Automation of Wind Pressure Computation Using a Data Management Approach

1993 ◽  
Author(s):  
Yamini Gourishankar ◽  
Frank Weisgerber
Keyword(s):  
Data Management ◽  
Data Retrieval ◽  
Design Guidelines ◽  
Database Management System ◽  
Information Modeling ◽  
Wind Pressure ◽  
Management Approach ◽  
Analysis And Design ◽  
Design Requirements ◽  
Wind Pressures

Abstract It is observed that calculating the wind pressures on structures involves more data retrieval from the ASCE standard than any subjective reasoning on the designer’s part. Once the initial design requirements are established, the procedure involved in the computation is straightforward. This paper discusses an approach to automate the process associated with wind pressure computation on one story and multi-story buildings using a data management strategy (implemented using the ORACLE database management system). In the prototype system developed herein, the designer supplies the design requirements in the form of the structure’s exposure type, its dimensions and the nature of occupancy of the structure. Using these requirements, the program retrieves the necessary standards data from an independently maintained database, and computes the wind pressures. The final output contains the wind pressures on the main wind force resisting system, and on the components and claddings, for wind blowing parallel and perpendicular to the ridge. The knowledge encoded in the system was gained from ASCE codes, design guidelines and as a result of interviews with various experts and practitioners. Several information modeling methodologies such as the entity relationship model, IDEF 1X, etc. were employed in the system analysis and design phase of this project. The prototype is implemented on an IBM PC using the ORACLE DBMS and the ‘C’ programming language. Appendix A illustrates a sample run.

Quality Management Approach in Qualifications Framework Implementation in Industrial Engineering

2015 ◽  
Vol 760 ◽  
pp. 721-726 ◽  
Author(s):  
Rodica Rohan ◽  
Nicolae Ionescu
Keyword(s):  
Higher Education ◽  
Quality Assurance ◽  
Quality Management ◽  
Conceptual Design ◽  
Industrial Engineering ◽  
Management Approach ◽  
Detailed Design ◽  
National Qualifications Framework ◽  
Implementation Stages

Currently in Romania it has been implemented the European Qualifications Framework (EQF) and its sustainability has become an impending need. In this paper, the authors propose an integrating structure, which involves a relatively large number of organizations for the sustainability of the National Qualifications Framework (CNC), while also providing quality assurance in higher education. Using quality management principles and their implementation stages as generic conceptual solutions, there have been established the specific conceptual solutions for the conceptual design of a system which the authors have called the System of Implementation and Sustainability of the National Qualifications Framework in Higher Education (SIS - CNCIS). It was then prepared the detailed design of the SIS-CNCIS for the particular case of implementation in Industrial Engineering.

scholarly journals Patient-generated health data management and quality challenges in remote patient monitoring

JAMIA Open ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 471-478 ◽  
Author(s):  
Robab Abdolkhani ◽  
Kathleen Gray ◽  
Ann Borda ◽  
Ruth DeSouza
Keyword(s):  
Quality Assurance ◽  
Data Management ◽  
Remote Monitoring ◽  
Patient Monitoring ◽  
Health Data ◽  
Clinical Settings ◽  
Remote Patient Monitoring ◽  
Monitoring Programs ◽  
Remote Patient ◽  
Promising Source

Abstract Background Patient-Generated Health Data (PGHD) in remote monitoring programs is a promising source of precise, personalized data, encouraged by expanding growth in the health technologies market. However, PGHD utilization in clinical settings is low. One of the critical challenges that impedes confident clinical use of PGHD is that these data are not managed according to any recognized approach for data quality assurance. Objective This article aims to identify the PGHD management and quality challenges that such an approach must address, as these are expressed by key PGHD stakeholder groups. Materials and Methods In-depth interviews were conducted with 20 experts who have experience in the use of PGHD in remote patient monitoring, including: healthcare providers, health information professionals within clinical settings, and commercial providers of remote monitoring solutions. Participants were asked to describe PGHD management processes in the remote monitoring programs in which they are involved, and to express their perspectives on PGHD quality challenges during the data management stages. Results The remote monitoring programs in the study did not follow clear PGHD management or quality assurance approach. Participants were not fully aware of all the considerations of PGHD quality. Digital health literacy, wearable accuracy, difficulty in data interpretation, and lack of PGHD integration with electronic medical record systems were among the key challenges identified that impact PGHD quality. Conclusion Co-development of PGHD quality guidelines with relevant stakeholders, including patients, is needed to ensure that quality remote monitoring data from wearables is available for use in more precise and personalized patient care.

Quality assurance review center: Role in multi-institutional breast cancer trials.

2011 ◽  
Vol 29 (27_suppl) ◽  
pp. 205-205
Author(s):  
J. Moni ◽  
H. T. Le-Petross ◽  
J. C. Boughey ◽  
F. Laurie ◽  
R. Hanusik ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Quality Assurance ◽  
Data Acquisition ◽  
Data Management ◽  
Remote Access ◽  
Data Management System ◽  
Data Systems ◽  
Neoadjuvant Endocrine Therapy ◽  
Trial Management ◽  
Cancer Trials

205 Background: Central review is an important trial management and validation tool. Multisite trials require data systems to accommodate diverse image acquisition and review. Breast cancer is challenging as its imaging objects are not always easily shared across departments. Quality Assurance Review Center (QARC) has a diverse portfolio of facile data acquisition and powerful informatics support that meets these needs. We report on the role of QARC in three of the current breast cancer trials from the American College of Surgeons Oncology Group. Methods: QARC data management system includes secure network infrastructure and a validated relational operating database (MAX). QARC has data acquisition/imaging re-distribution expertise for real time response reviews, response measuring tools and corresponding data archive for secondary reviews. MAX includes query ability; records link to digital information. QARC underwent systematic information systems validation process for 21 CFR Part 11. DICOM/non-DICOM files are stored in the QARC PACS. On-site/remote reviewers use MAX to retrieve, view, annotate and save images. Data extracted is securely sent to partner statistical centers. Results: In Z1031, a neoadjuvant endocrine therapy trial, all of the mammographic exams are archived at QARC. For Z1071, a sentinel lymph node trial, pre- and post-treatment ultrasound (US) images of 321 patients were remotely reviewed. For Z1072, the cryoablation US, pre and post-cryoablation MRI for 40 of 47 cases were remotely archived, retrieved and transferred to investigator workstation for post-processing and review. The other 7 patients did not have evaluable imaging studies. In all three trials, the costs of shipping hardcopies of exams and travel to QARC for central review functions were eliminated. Conclusions: QARC data management systems provide diverse informatics supports for multi-institutional trials, ranging from archives of images, provide remote access and download of data, and central review. The vibrant informatics supports meet the growing needs of clinical trials. Future directions include radiation field review for breast cancer trials and the incorporation of pathology microarray analysis as DICOM objects.

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