Category Archives: Information Technology

Healthcare Quality Metrics: An Annotated Bibliography

Posted on March 13, 2014 by Menagerie Press

Healthcare Quality Metrics 1.     Health Resource and Service Administration http://www.hrsa.gov/healthit/toolbox/RuralHealthITtoolbox/PatientQuality/metrics.html Description: A quality metric allows a user to quantify the quality of a selected aspect of care.  The Health Resource and Service Administration website explains the different types of quality metrics … Continue reading →

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ICD-9 Conversion to ICD-10 Resources: An Annotated Bibliography

Posted on March 12, 2014 by Menagerie Press

ICD-9 Conversion to ICD-10 Resources 1.     Centers for Medicare and Medicaid Services http://www.cms.gov/Medicare/Coding/ICD10/index.html?redirect=/icd10 Description: ICD-9 code sets used in reporting medical diagnoses and impatient procedures are being replaced by ICD-10 code sets on October 1, 2014.  This transition is required … Continue reading →

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Big Data Analysis Tools/Resources: An Annotated Bibliography

Posted on March 10, 2014 by Menagerie Press

Big Data Analysis Tools/Resources 1.     Chris Stucchio’s blog http://www.chrisstucchio.com/blog/2013/hadoop_hatred.html This blog makes this list primarily for one article: “Don’t use Hadoop – your data isn’t that big”, which provides a guide for deciding whether your data really qualifies as big … Continue reading →

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SQL Programming Resources: An Annotated Bibliography

Posted on March 5, 2014 by Menagerie Press

SQL Programming Resources 1.     Coursera/Stanford “Introduction to Databases” https://www.coursera.org/course/db One of the biggest names in Massive Open Online Courseware (MOOC), Coursera has a huge database of university level courses. This offering from Stanford University has 9 units devoted to SQL … Continue reading →

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‘Big Data’ Public Databases: An Annotated Bibliography

Posted on March 5, 2014 by Menagerie Press

Big Public Databases 1.     Kin Lane’s Federal Dataset Tool http://federal-agency-dataset-adoption.publicprivatesector.org/index.html Many of the following listings refer to US Federal Government datasets. These are some of the biggest public datasets available. Unfortunately, much of this data is messy, published without much … Continue reading →

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Database Training Resources: An Annotated Bibliography

Posted on March 3, 2014 by Menagerie Press

Database Training Resources 1.     Coursera/Stanford “Introduction to Databases” https://www.coursera.org/course/db Introduction to Databases from Stanford University was one of the first Massive Open Online Courses (MOOCs) offered by Coursera in 2011, and has remained consistently popular. The course covers database design and … Continue reading →

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Data Visualization Resources: An Annotated Bibliography

Posted on March 2, 2014 by Menagerie Press

Data Visualization Resources 1.     The St Louis Federal Reserve http://research.stlouisfed.org/ The St Louis Federal Reserve Economic Data series is perhaps the most comprehensive repository of time-series data. It also offers an in-browser, cross-platform, data visualization tool. The time series are … Continue reading →

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Jaro-Winkler in ORACLE and textual fuzzy matching

Posted on January 20, 2014 by Menagerie Press

There is a little-known (and hence heavily under-utilized) function in Oracle 11g and up. This is the Jaro-Winkler algorithm (and the companion algorithm named Edit Distance). The Jaro-Winkler algorithm tells you what level of permutation would be necessary in order … Continue reading →

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Working in Data: ORDER CAREERS, DESC

Posted on December 24, 2013 by Menagerie Press

I’ve had the opportunity to work in health data for a while now. There are most definitely gradations and ranks in the data verse career list. In my first role as a health technologist, I learned a massive wealth of … Continue reading →

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The Yin-Yang of Understanding Data

Posted on December 7, 2013 by Menagerie Press

There are several issues with data. One is that it’s viewed with suspicion. Conversely, it is also held to sacrosanct integrity. I’d almost refer to this as the yin-yang of data understanding. When I come to findings or conclusions with … Continue reading →

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