A reminder in case you have not registered yet for HASUG's upcoming meeting
Charles S Patridge - PDPC, Ltd.
172 Monce Road - Burlington, CT 06013 USA
Email: Charles_S...@prodigy.net
Web: http://www.sconsig.com
--- On Tue, 7/31/12, Charles Patridge <charles_s...@prodigy.net> wrote:
From: Charles Patridge <charles_s...@prodigy.net>
Subject: August 16th, 2012 - HASUG Meeting, Orange, CT - 10:00 AM to 1:00 PM
To: "Members HASUG" <ha...@googlegroups.com>
Cc: "HASUG-L Steering Committee" <hartford-area-...@googlegroups.com>
Date: Tuesday, July 31, 2012, 8:51 AM
HASUG MEETING ANNOUNCEMENT AND DIRECTIONS
Our next meeting is Thursday, Aug 16th, 2012 at
Case Memorial Library (Orange Library)
176 Tyler City Road,
Orange, CT 06477 from 10:00am to 1pm
Our Topics and Speakers will be:
Planting Your Rows:
Using SAS Formats to Make the Generation of Zero-Filled Rows in Tables Less Thorny, by Kathy Fraeman
Often tables or summary reports need to be produced with SAS where all possible values of one or more variables need to be included as rows in a table. However, the actual data to be summarized in a table might include variables that don’t have all of the variables’ possible values, even though the table needs a corresponding zero-filled row for that variable value. These zero-filled table rows for non-existent variable values will be missing from the table unless additional programming is done. One programming method to make sure all rows are included would be to hard code all possible values of a variable, although this method could be tedious if a large number of variables and/or values are involved. A more dynamic method of determining all possible values of a variable is to attach a SAS format to each table variable, where the format contains all of the variable’s possible values. SAS can dynamically determine the name of a format
attached to a variable using SYSFUNC with SCL or a dictionary table using PROC SQL. SAS can then generate a data set of all possible values for the variable by using the CNTLOUT = option of PROC FORMAT. The output data set generated from PROC FORMAT can be dynamically used to ensure that all possible values of a variable, even values that don’t actually exist in the data, will be included as rows in a table
Kathy Fraeman, SM, is the Director of Data Analytics for UBC's Epidemiology and Database Analytics (EDA) group. Ms. Fraeman is an accomplished and knowledgeable SAS Programmer/analyst with over 25 years of experience in analytic SAS programming and data management for biomedical research studies, including pharmaceutical clinical trials, epidemiologic studies, survey research, cost-of-drug-treatment studies, and drug safety and marketing studies. She is highly experienced in analyzing large and complex relational health care databases, including insurance claims files. Ms. Fraeman has co-authored several publications in the fields of epidemiology and health care issues. Before joining UBC, Ms. Fraeman was a self-employed independent SAS contractor who worked on over a dozen projects with UBC. She received her Bachelor of Science in Biology from the Massachusetts Institute of Technology and her Master's of Science in Environmental Health Sciences
from the Harvard University School of Public Health.
Leveraging Text Mining in Insurance: Claims Analytics Using Text Mining, by Chuck Patridge
Claims is a key business area for any carrier, with significant impact on bottom-line results. Much rides on the expertise and follow-through of the adjusters, who not only have to negotiate a fair and equitable settlement, but also make a number of other assessments such as subrogation, suspicion, and the need for an independent medical exam. Missed opportunities in making the right assessments can significantly impact business results.
Text mining can be used to uncover insights from adjuster notes and aid the systematic detection and referral of claims to such specialists.
Chuck Patridge is a IIA Data Manager since June 2008. Chuck graduated from Central Connecticut State University in 1972 with a BS in mathematics and education. He has passed Actuarial exams 1-2, and has 40 graduate hours in statistics. His expertise is using the SAS software since 1979 in a variety of business environments such as HR, Technical Support, Claims, Actuarial, Reinsurance, Goverment, Education, Transportation, Relocation Services , Marketing, Financial, Pharmaceutical and Insurance (Life, Health and P&C) with most career experience in the Property Casualty Insurance arena He has presented a number of papers to various SAS user groups including SAS Global Forum and publishing a white paper on “Fuzzy Match/Merge“ in conjunction with SAS Institute Chuck also started the first local SAS User Group – Hartford Area SAS User Group ( www.hasug.org) – HASUG in 1983 as well as created and maintains another SAS user
website, www.sconsig.com (SAS Consultant Special Interest Group) since 1994.
Directions to Orange Library can be found on the HASUG website at www.hasug.org . Also, please register for this meeting by going to hasug website and register. Feel free to invite your colleagues to also register and attend the meeting as well.
Looking forward to seeing you there,
HASUG Steering Committee
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