Integrating Data Quality Data into Decision-Making Process: An Information Visualization Approach

2007 ◽  
pp. 366-369 ◽  
Author(s):  
Bin Zhu ◽  
G. Shankar ◽  
Yu Cai
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Information Visualization ◽  
Quality Data ◽  
Decision Making Process

Design of Marine Data Warehouse ETL System

2014 ◽  
Vol 668-669 ◽  
pp. 1374-1377 ◽  
Author(s):  
Wei Jun Wen
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Data Warehouse ◽  
Environmental Data ◽  
Data Sources ◽  
Quality Data ◽  
Critical Step ◽  
Marine Data ◽  
Data Extracting ◽  
Marine Environmental

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

A Methodology to Assure Measurement Data Quality for Key Engineering Materials

2010 ◽  
Vol 108-111 ◽  
pp. 972-978
Author(s):  
Ying Su ◽  
Jing Hua Huang ◽  
Latif Al-Hakim
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Measurement Data ◽  
Limited Attention ◽  
Decision Making Process ◽  
Precision Determination ◽  
Accuracy And Precision ◽  
Process Documentation ◽  
Engineering Materials

Purpose – Only limited attention has been paid to the issue of Measurement Data Quality (MDQ) in a metrology context. To address this critique of the literature a methodology to assure MDQ was proposed. Methodology – The study proposes a methodology which consists of four steps can be used to 1 identify the importance of a measurement (identification), 2 determine accuracy and precision (determination), 3 evaluate the criticality of the measurement to its impact on the final result (evaluation) and 4 record the facts that influenced the decision making process (documentation). Findings –When followed and properly documented, these four steps can help ensure our measurements are valid and worthwhile. Identifying the important measurements that are made, determining the level of accuracy required and then using the proper tools to make the measurements will yield valid, useful results.

scholarly journals Improving Prosthetic Selection and Predicting BMD from Biometric Measurements in Patients Receiving Total Hip Arthroplasty

Diagnostics ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 815
Author(s):  
Carlo Ricciardi ◽  
Halldór Jónsson ◽  
Deborah Jacob ◽  
Giovanni Improta ◽  
Marco Recenti ◽  
...  
Keyword(s):  
Decision Making ◽  
Total Hip Arthroplasty ◽  
Hip Arthroplasty ◽  
Quality Data ◽  
National Database ◽  
Patient Specific ◽  
Surgical Approaches ◽  
Decision Making Process ◽  
Mineral Density ◽  
Total Hip

There are two surgical approaches to performing total hip arthroplasty (THA): a cemented or uncemented type of prosthesis. The choice is usually based on the experience of the orthopaedic surgeon and on parameters such as the age and gender of the patient. Using machine learning (ML) techniques on quantitative biomechanical and bone quality data extracted from computed tomography, electromyography and gait analysis, the aim of this paper was, firstly, to help clinicians use patient-specific biomarkers from diagnostic exams in the prosthetic decision-making process. The second aim was to evaluate patient long-term outcomes by predicting the bone mineral density (BMD) of the proximal and distal parts of the femur using advanced image processing analysis techniques and ML. The ML analyses were performed on diagnostic patient data extracted from a national database of 51 THA patients using the Knime analytics platform. The classification analysis achieved 93% accuracy in choosing the type of prosthesis; the regression analysis on the BMD data showed a coefficient of determination of about 0.6. The start and stop of the electromyographic signals were identified as the best predictors. This study shows a patient-specific approach could be helpful in the decision-making process and provide clinicians with information regarding the follow up of patients.

scholarly journals Accompanying the Prostate Cancer Patient Pathway: Evaluation of Novel Clinical Decision Support Software

2021 ◽  
Author(s):  
Maurice Henkel ◽  
Tobias Horn ◽  
Francois Leboutte ◽  
Pawel Trotsenko ◽  
Sarah G. Dugas ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Data Quality ◽  
Clinical Decision Support ◽  
User Satisfaction ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Decision Making Process

Abstract Introduction Physicians spend more than half of their workday interacting with health information systems to care for their patients. Effective data management that provides physicians with comprehensive patient information from various information systems is required to ensure high quality clinical decision making.Objectives We evaluated the impact of a novel, CE-certified clinical decision support tool on physician’s effectiveness and satisfaction in the clinical decision-making process.Methods Using pre-therapeutic prostate cancer management cases, we compared physician’s expenditure of time, data quality, and user satisfaction in the decision-making process comparing the current standard with the software. Ten urologists from our department conducted the diagnostic work-up to the treatment decision for a total of 10 patients using both approaches.Results A significant reduction in the physician’s expenditure of time for the decision-making process by -59.9 % (p < 0,001) was found using the software. System usage showed a high positive effect on evaluated data quality parameters completeness (Cohen's d of 2.36), format (6.15), understandability (2.64), as well as user satisfaction (4.94).Conclusion The software demonstrated that effective data management can improve physician’s effectiveness and satisfaction in the clinical decision-making process. Further development is needed to map more complex patient pathways, such as the follow-up treatment of prostate cancer.

scholarly journals Improving data quality and information utilization at Metema Primary Hospital, Amhara national regional state, Northwest Ethiopia 2018: Capstone project

2021 ◽  
Vol 27 (3) ◽  
pp. 146045822110431
Author(s):  
Tajebew Z Gonete ◽  
Lake Yazachew ◽  
Berhanu F Endehabtu
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Quality Data ◽  
Health Management Information System ◽  
Evidence Based ◽  
Supportive Supervision ◽  
Data Recording ◽  
Post Intervention ◽  
Information Utilization ◽  
Significant Difference

Quality data for evidence-based decision making become a growing concern globally. Available information needs to be disseminated on time and used for decision making. Therefore, an effective Health Management Information System is essential to make evidence-based decision. This study aimed to measure the change in data quality and information utilization before and after intervention. Facility-based pre-post interventional study design was conducted at Metema hospital from September/2016 to December30/2018. A total of 384 individual medical-records, HMIS registration-books and reports were reviewed. Training, supportive supervision and feedback were intervention packages. About 309 (80.5%) of charts were from outpatient department. Data recording completeness increased from 69.0% to 96.0%, data consistency increased from 84.0% to 99.5% and report timeliness enhanced from 66.0% to 100%. There was a statistically significant difference for data recording completeness between pre and post-intervention results with mean difference of −0.246 (−0.412, −0.081). Also, after the intervention, gap-filling feedback and supportive supervision were given to all departments. In addition, four quality improvement projects were developed at post-intervention phase. The level of data quality and use was improved after the intervention. So, designing and implementing intervention strategies based on the root causes will help to improve data quality and use.

ISO 9001 International Standard, a Tool to Enhance Data Quality in Durable Socio-Technical Systems

2015 ◽  
Vol 809-810 ◽  
pp. 1528-1534
Author(s):  
Alexandre Sava ◽  
Kondo Adjallah ◽  
Valentin Zichil
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Quality Management System ◽  
Technical System ◽  
Iso 9001 ◽  
Decision Making Process ◽  
Quality Of Data ◽  
International Standard ◽  
Technical Systems

The quality of data is recognized to be a key issue for the assets management in enterprises as data is the foundation of any decision making process. Recent research work has established that the quality of data is highly dependent on the knowledge one has on the socio-technical system being considered. Three modes of knowledge have been identified: knowing what, knowing how and knowing why. In this paper we focus on how to manage these modes of knowledge in durable socio-technical systems to enhance the data quality face to technological progress and employees turnover. We believe that an organization based on ISO 9001 international standard can provide a valuable framework to provide the data quality needed to an efficient decision making process. This framework has been applied to design the data quality management system within a high education socio-technical system. The most important benefits that have been noticed are: 1) a shared vision on the external clients of the system with a positive impact on the definition of the strategy and the objectives of the system and 2) a deep understanding of the data client-supplier relationship inside the socio-technical system. A direct consequence of these achievements was the increasing knowledge on “know-what” data to collect, “know-why” to collect that data and “know-how” to collect it.

scholarly journals Exploring the Potential of Online Webcam-based Eye Tracking in Decision-Making Research and Influence Factors on Data Quality

2021 ◽  
Author(s):  
Tim Schneegans ◽  
Matthew D. Bachman ◽  
Scott A. Huettel ◽  
Hauke Heekeren
Keyword(s):  
Decision Making ◽  
Eye Tracking ◽  
Data Quality ◽  
Open Source ◽  
Influence Factors ◽  
Frame Rate ◽  
Quality Data ◽  
Tracking Data ◽  
Chin Rest ◽  
Negative Effect

Recent developments of open-source online eye-tracking algorithms suggests that they may be ready for use in online studies, thereby overcoming the limitations of in-lab eye-tracking studies. However, to date there have been limited tests of the efficacy of online eye-tracking for decision-making and cognitive psychology. In this online study, we explore the potential and the limitations of online eye-tracking tools for decision-making research using the webcam-based open-source library Webgazer (Papoutsaki et al., 2016). Our study had two aims. For our first aim we assessed different variables that might affect the quality of eye-tracking data. In our experiment (N = 210) we measured a within-subjects variable of adding a provisional chin rest and a between-subjects variable of corrected vs uncorrected vision. Contrary to our hypotheses, we found that the chin rest had a negative effect on data quality. In accordance with out hypotheses, we found lower quality data in participants who wore glasses. Other influence factors are discussed, such as the frame rate. For our second aim (N = 44) we attempted to replicate a decision-making paradigm where eye-tracking data was acquired using offline means (Amasino et al., 2019). We found some relations between choice behavior and eye-tracking measures, such as the last fixation and the distribution of gaze points at the moment right before the choice. However, several effects could not be reproduced, such as the overall distribution of gaze points or dynamic search strategies. Therefore, our hypotheses only find partial evidence. This study gives practical insights for the feasibility of online eye-tacking for decision making research as well as researchers from other disciplines.

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