Galaxy's Data Quality Program

2011 ◽  
pp. 1-25
Author(s):  
Eric Infield ◽  
Laura Sebastian-Coleman
Keyword(s):  
Health Care ◽  
Data Quality ◽  
Data Warehouse ◽  
Information Quality ◽  
Lessons Learned ◽  
Statistical Process ◽  
Health Care Data ◽  
Quality Program

This paper is a case study of the data quality program implemented for Galaxy, a large health care data warehouse owned by UnitedHealth Group and operated by Ingenix. The paper presents an overview of the program’s goals and components. It focuses on the program’s metrics and includes examples of the practical application of statistical process control (SPC) for measuring and reporting on data quality. These measurements pertain directly to the quality of the data and have implications for the wider question of information quality. The paper provides examples of specific measures, the benefits gained in applying them in a data warehouse setting, and lessons learned in the process of implementing and evolving the program.

The Effects of Survey Enhancements on the Quality of Reporting in the Medical Expenditure Panel Survey, 2008–2015

2019 ◽  
Vol 8 (3) ◽  
pp. 589-616 ◽  
Author(s):  
Samuel H Zuvekas ◽  
Adam I Biener ◽  
Wendy D Hicks
Keyword(s):  
Health Care ◽  
Data Quality ◽  
Large Scale ◽  
Medical Expenditure Panel Survey ◽  
Lessons Learned ◽  
Health Care Use ◽  
Medical Expenditure ◽  
Panel Survey ◽  
Quality Of Reporting

Abstract It is well established that survey respondents imperfectly recall health care use in surveys. However, careful attention to both survey design and fielding procedures can enhance recall. We examine the effects of a comprehensive, multi-pronged approach to changing field procedures in the Medical Expenditure Panel Survey (MEPS) to improve quality of health care use reporting. Conducted annually since 1996, the MEPS is the leading large-scale nationally representative health survey with detailed individual and household information on health care use and expenditures. These survey enhancements were undertaken in 2013–2014 because of concerns over a drop in the quality of reporting in 2010 that persisted into 2011–2012. The approach combined focused retraining of field supervisors and interviewers, developing quality metrics and reports for ongoing monitoring of interviewers, and revising advanced letters and materials sent to respondents. We seek to determine the extent to which changes in field procedures and trainings improved interviewer and respondent behaviors associated with better reporting, and more importantly, improved reporting accuracy. We use longitudinal MEPS data from 2008 through 2015, combining household reported use with sociodemographic and health status characteristics, and paradata on the characteristics of the interviews and interviewers. We exploit the longitudinal data and timings of major trainings and changes in field procedures in regression models, separating out the effects of the trainings and other fielding changes to the extent possible. We find that the 2013–2014 data quality improvement activities substantially improved reporting quality. Positive interviewer behaviors increased substantially to above pre-2010 levels, and utilization reporting has recovered to above pre-2010 levels, returning MEPS to trend. Importantly, these substantial gains occurred in 2013, prior to extensive in-person training for most of the field force. We examine the lessons learned from this data quality initiative both for the MEPS program and for other large household surveys.

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.

Medical Informatics and the Quality of Health: New Approaches to Support Patient Care

2003 ◽  
Vol 42 (02) ◽  
pp. 185-189 ◽  
Author(s):  
R. Haux ◽  
C. Kulikowski ◽  
A. Bohne ◽  
R. Brandner ◽  
B. Brigl ◽  
...  
Keyword(s):  
Health Care ◽  
Medical Informatics ◽  
Health Care Providers ◽  
Medical Knowledge ◽  
Lessons Learned ◽  
Care Providers ◽  
Access To Health Services ◽  
Leading Role ◽  
Future Challenges

Summary Objectives: The Yearbook of Medical Informatics is published annually by the International Medical Informatics Association (IMIA) and contains a selection of excellent papers on medical informatics research which have been recently published (www.yearbook.uni-hd.de). The 2003 Yearbook of Medical Informatics took as its theme the role of medical informatics for the quality of health care. In this paper, we will discuss challenges for health care, and the lessons learned from editing IMIA Yearbook 2003. Results and Conclusions: Modern information processing methodology and information and communication technology have strongly influenced our societies and health care. As a consequence of this, medical informatics as a discipline has taken a leading role in the further development of health care. This involves developing information systems that enhance opportunities for global access to health services and medical knowledge. Informatics methodology and technology will facilitate high quality of care in aging societies, and will decrease the possibilities of health care errors. It will also enable the dissemination of the latest medical and health information on the web to consumers and health care providers alike. The selected papers of the IMIA Yearbook 2003 present clear examples and future challenges, and they highlight how various sub-disciplines of medical informatics can contribute to this.

scholarly journals Using the Google™ Search Engine for Health Information: Is There a Problem? Case Study: Supplements for Cancer

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Hannah C Cai ◽  
Leanne E King ◽  
Johanna T Dwyer
Keyword(s):  
Health Information ◽  
Search Engine ◽  
Information Quality ◽  
Nutrition Information ◽  
High Quality ◽  
Search Results ◽  
Health And Nutrition ◽  
Quality Rating

ABSTRACT We assessed the quality of online health and nutrition information using a Google™ search on “supplements for cancer”. Search results were scored using the Health Information Quality Index (HIQI), a quality-rating tool consisting of 12 objective criteria related to website domain, lack of commercial aspects, and authoritative nature of the health and nutrition information provided. Possible scores ranged from 0 (lowest) to 12 (“perfect” or highest quality). After eliminating irrelevant results, the remaining 160 search results had median and mean scores of 8. One-quarter of the results were of high quality (score of 10–12). There was no correlation between high-quality scores and early appearance in the sequence of search results, where results are presumably more visible. Also, 496 advertisements, over twice the number of search results, appeared. We conclude that the Google™ search engine may have shortcomings when used to obtain information on dietary supplements and cancer.

scholarly journals Getting the Numbers Right on China's Actual Overseas Investment: The Case of the Netherlands

2017 ◽  
Vol 46 (1) ◽  
pp. 187-209 ◽  
Author(s):  
Piter De Jong ◽  
Mark J. Greeven ◽  
Haico Ebbers
Keyword(s):  
The Netherlands ◽  
Data Quality ◽  
Chinese Firms ◽  
Chamber Of Commerce ◽  
Overseas Investment ◽  
Data Source

This study assesses the quality of Chinese outbound FDI data. In our case study of the Netherlands, we checked the data quality of the often-used Orbis/Amadeus database and its data source, the Dutch Chamber of Commerce (Kamer van Koophandel, KVK), which has one of the oldest and, arguably, one of the better databases within Europe. We analysed Chinese investments in the Netherlands and show that six adjustments are necessary to clean up the data. We also show that not making these adjustments can significantly impact the outcome of research. The cleaned-up data show that sampled Chinese firms are young, small, and private.

IT Architecture and Information Quality in Data Warehouse and Business Intelligence Environments

2014 ◽  
pp. 112-127
Author(s):  
Samuel Otero Schmidt ◽  
Edmir Parada Vasques Prado
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Information Quality ◽  
Relevant Literature ◽  
Research Model ◽  
Structured Interviews ◽  
It Architecture ◽  
Financial Company ◽  
The Relationship

Organizations are currently investing more in information technology to store and process a vast amount of information. Generally, this information does not comply with any standard, which hinders the decision-making process. The cause of the difficulties can be attributed to Information Quality (IQ), which has technical characteristics related to the architecture used in Data Warehouse (DW) and Business Intelligence (BI) environments. On the basis of the relevant literature in IQ, DW, and BI, a research model was created to identify the relations between components of DW/BI architecture and IQ dimensions. This research model was applied in a real case study (Big Financial Company in Brazil). This case study involved semi-structured interviews with managers and analysts. This chapter attempts to provide a better understanding of the relations between IT architecture and IQ in DW and BI environments. The authors hope to motivate the discussion around the development of IQ-oriented architectures for BI and the relationship between these concepts.

Sign in / Sign up

Export Citation Format

Share Document