Nov. 2013 Data Quality Science News

The focus of this month’s newsletter is on software tools for evaluating data quality and modifying or correcting data to address deficiencies in quality. Researchers and analysts often seek to implement program code that can be used to…

Email Newsletter: November 2013
Sent by: Lisa Lix
Department of Community Health Sciences, University of Manitoba

LL_banner_

November 2013


The focus of this month’s newsletter is on software tools for evaluating data quality and modifying or correcting data to address deficiencies in quality. Researchers and analysts often seek to implement program code that can be used to routinely and systematically produce measures of data completeness, correctness, and timeliness. Access to data quality macros or subroutines means that reports can be consistently generated with just a few keystrokes. Routine data quality evaluations are important for ensuring that data quality does not erode over time, and they can be the basis for ongoing dialogues between data providers and data users.  Specialized software tools to measure and address specific data quality issues, such as missing data, are equally important to include in the analysts’ toolkit.  
 
At the 2013 SAS®Global Forum in San Francisco, there were a number of presentations on software tools for data quality, two of which were made by analysts working with Canada’s administrative health data. I have provided links to these technical papers in the Links of Interest. As well, I recently came across an interesting website that highlights a recent SAS® book entitled “Data Quality for Analytics” that you may find useful. 
 
Lisa Lix
 

Recent Publications

  1. Data Quality for Analytics:  http://www.sascommunity.org/wiki/Gerhard%27s_Blog
Links of Interest
  1. Data Fitness: A SAS® Macro-based Application for Data Quality of Large Health Administrative Data: http://support.sas.com/resources/papers/proceedings13/075-2013.pdf
  2. A Flexible Method to Apply Multiple Imputation Using SAS/IML® Studio: http://support.sas.com/resources/papers/proceedings13/283-2013.pdf
  3. In-Database Data Quality – Performance for Big Data: http://support.sas.com/resources/papers/proceedings13/079-2013.pdf

Networking and Training

Delivering High Quality Hospital Data: Towards Clinically Meaningful Information

e-Health 2014 Conference

Copyright © | November 2013 | Lisa Lix, All rights reserved.

Lisa Lix
Department of Community Health Sciences, University of Manitoba
Email: Lisa.Lix@med.umanitoba.ca

university of manitoba logo
 
Data Quality Science eNews is a monthly e-bulletin for people interested in research about the quality of secondary data.

It is published by Lisa Lix of the University of Manitoba, Canada, and she invites you to share your research, events, announcements, and resources by sending your submissions here

Public Health Agency of Canada (Data Cubes)

The Chronic Disease Surveillance Division at the Public Health Agency of Canada has recently launched the following data cube on its public website: Arthritis in Canada Update
Using a nationally representative sample of 25,978 Canadians aged 15 years and older from the 2010-11 Canadian Community Health Survey, this data cube provides the latest statistics on the impact of arthritis on Canadians.

Do biologics cut mortality in rheumatoid arthritis?

This content is restricted to CANRAD Network members. If you are an existing member, please login.
thumb_do-biologics-cut-mortality-in-rheumatoid-arthritis
Biologics use by rheumatoid arthritis patients was associated with a 25% reduction in the risk of premature death, compared to patients without exposure to biologics, based on data from a population-based study of more than 4,000 patients. Dr. Diane Lacaille of the Arthritis Research Center of Canada discusses the results at the American College of Rheumatology’s annual meeting.