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insurance claims

198 papers and 7 presentations; 189 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 Assessing Quality of Real-World Data Sources S. Robert Collins source 4
PHUSE APAC 2026 An Open-Source R Implementation of a Validated Claims-Based Algorithm to Identify Pregnancy Episodes Dhirishiya P,
Onkar Kshirsagar		 source
presentation source		 7
PHUSE APAC 2026 Annualized Relapse Rate and Clinical Profiles in South Korean Multiple Sclerosis Patients: A Sample Cohort Study Using Korean National Health Insurance Data Seongjun Byun,
Jisuk Jo		 source
presentation source		 8
PHUSE APAC 2026 Building a Trustworthy RWD Analytics Platform Key Considerations and Strategies William Yuanhao Kuan,
Ashwini Reddy		 source
presentation source		 7
PHUSE APAC 2026 Integrating Real-World Evidence (RWE) and Digital Health Technologies (DHTs) with AI for Enhanced Patient Outcomes (RE) Varun Sethuraman source
presentation source		 10
PHUSE EU 2025 Close Encounters with Real-World Data Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt		 source
presentation source		 21
PHUSE EU 2025 FHIR for RWD Submissions: Why a US Regulation Signals a Global Shift And What You Need To Do Now Sanyogeeta Andhale,
Nachiket Thakkar		 source
presentation source		 11
PHUSE EU 2025 Unlocking Healthcare Insights: Graph-Based Modelling and Analysis of Synthetic Patient Data George Panagiotakis,
Nikolaos Kountouris		 source
presentation source		 18
MWSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
WUSS 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
PharmaSUG 2025 Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source Jayanth Iyengar source 32
PharmaSUG 2025 Scoring Real-World Data Reliability for Clinical Investigations James Joseph source 15
PharmaSUG 2025 You don-t have to handle the truth! Three Things to Know about Synthetic Data Catherine Briggs,
S. Robert Collins,
Sundaresh Sankaran		 source 7
PHUSE US 2025 Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP Ingeborg Holt,
Sarah Ferko,
Jeffrey M. Abolafia		 source
presentation source		 15
PHUSE US 2025 Measure Total Steroid Dose Using Real-World Data Yi-Chien Lee source
poster source		 2
PHUSE EU 2024 Considerations for the Submission of RWD using CDISC with Insights from HL7 FHIR and OMOP Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt		 source
presentation source		 13
PHUSE EU 2024 Introducing Graph Structure in Real-World Data Analyses Georgios Panagiotakis,
Maria Puri		 source
poster source		 10
PHUSE EU 2024 Unlocking the Potential of Unstructured Data in Real-World Evidence: Leveraging Text for Enhanced Patient Classification and Regulatory Validation Georgios Panagiotakis,
Maria Puri		 source
poster source		 10
PHUSE US 2024 From Data Iron to Data Gold Ashwini Yermal Shanbhogue source
poster source		 9
PHUSE US 2024 Future Clinical Data Submission Standards: CDISC, FHIR, OMOP, or Hybrid Model Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt		 source
presentation source		 10
PHUSE US 2024 Usage of OMOP-CDM along with CDISC in Clinical Trials: Challenges and Opportunities Parag Shiralkar source
presentation source		 5
PHUSE EU 2023 Get the Full Picture of Your Data with SAS Andy Bayliss source
presentation source		 13
PharmaSUG 2023 Metaverse in the Healthcare - More Real than imagined! Aman Bahl source 14
PHUSE EU 2022 Is Your Analytics Platform Ready for Handling Real-world Data for Regulatory-grade Real-world Evidence? William Kuan,
Olivier Bouchard		 source
presentation source		 7
PHUSE EU 2022 Predictive Analytics Framework for Diversity-focused Trial Enrolment: Synergistic role of Registry Data, Lived Experiences, and Programming Power Kapil Khambholja,
Vatsal Chhaya		 source
presentation source		 5
PharmaSUG 2022 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
PHUSE US 2021 Patient Registries - New Gold Standard for Real World Data [presentation] Lavanya Peddibhotla,
Sivasankar Konda		 source
video		 14
SGF 2021 How Sick Is My Cohort Of Patients? A General Approach to Identify Chronic Conditions Patricia Ferido,
Laura Gascue,
Patricia St. Clair		 source 12
PHUSE EU 2020 Data Standards for Non-interventional Studies [poster] Karen Horton,
Vladlen Ivanushkin		 source
video		 1
PHUSE EU 2020 Unlocking the Potential of Big Data in Clinical Research [presentation] Vishal Kapoor source
video		 15
SESUG 2020 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 source 28
SGF 2020 Accessing Medicare Data at the Centers for Medicare and Medicaid Services using SAS Richard Andrews source 24
SGF 2020 Explanatory Machine Learning Model Plots for Epidemiological and Real-World Evidence Studies David Olaleye source 22
SGF 2020 Network Pattern Match for Identifying Fraud with SAS Visual Investigator James Morris,
Nicholas Ablitt		 source 17
SESUG 2019 Face Recognition Using SAS Viya: Guess Who the Person Is! Pratyush Dash source 6
MWSUG 2019 Look Up Not Down: Advanced Table Lookups in Base SAS Jayanth Iyengar,
Joshua M. Horstman		 24
MWSUG 2019 The SAS EG Process Flow: A Customizable Data Mining Tool in the Search for Healthcare Fraud Andrea McLain 6
PharmaSUG 2019 Artificial Intelligence and Real World Evidence - it takes two to tango Charan Kumar Kuyyamudira Janardhana source 9
PharmaSUG 2019 Innovative Technologies utilization in 21st Novel Clinical Research programs towards Generation of Real World Data. Srinivasa Rao Mandava source 6
PharmaSUG 2019 Patterns of risk factors and drug treatments among Hypertension patients Youngjin Park source 14
PharmaSUG 2019 Real-world data as real-world evidence: Establishing the meaning of data as a prerequisite to determining secondary-use value Jennifer R. Popovic source 7
SGF 2019 Machine Learning and Predictive Analytics in SAS Enterprise Miner and SAS/STAT Software David Richard Cutler source 21
SGF 2019 Predicting Patients at High Risk of Hospital-Acquired Conditions Using the LOGISTIC Procedure Jennifer Hargrove,
Pamela Hipp,
Glenn Sidle		 source 12
SGF 2019 Procedure Code Explosion: Applying SAS Macro Language, HASH Tables, and PROC FCMP to Manage Large Volumes of Procedure Codes in Administrative Data Research Matthew Keller,
Dustin Stwalley,
Katelin B. Nickel		 source 3
SGF 2019 The Relationship Between Social Determinants of Health and Healthcare Utilization Ryan C. Butterfield,
Melissa Gottschalk,
Laura Soloway,
Paul A. LaBrec		 source 16
SGF 2019 Using SAS to Analyze ICD9 and ICD10 Codes Kathy Hardis Fraeman source 11
SCSUG 2018 Machine Learning in Litigation Prediction - Workers' Compensation Litigation Propensity Predictive Model Mei Najim source 17
PHUSE US 2018 Registry/Observational Studies: Study Designs Data Sources and Key Steps in Designing Such Studies Anupama Sheoran source
presentation source		 6
PharmaSUG 2018 Infrastructure for Healthcare Analytics: A Foundational Approach to Development Jennifer R. Popovic source 11
SGF 2018 Claim Analytics: A Litigation Prediction Case Study Mei Najim source 18
SGF 2018 Development of an Individual-Level Social Determinants of Health (SDoH) Classification Model Ryan C. Butterfield,
Paul A. LaBrec		 source 13
SGF 2018 Infrastructure for Healthcare Analytics: A Foundational Approach to Development Jennifer R. Popovic source 11
SGF 2018 New Ways to Incorporate Continuous Predictors in Generalized Linear Models Anthony Salis,
Angela Wu,
Gordon Johnston		 source 15
SGF 2018 SAS Arrays and Macros Make Processing Claims with Multiple Conditions Easier Shavonne J. Standifer source 10
SGF 2018 The Cox Hazard Model for Claims Data Tanya Kolosova source 16
SGF 2018 Tools Designed to Aid in Quality Control of Administrative Data Research Projects Matthew Keller,
Katelin B. Nickel		 source 10
SGF 2018 Using Market Basket Analysis in SAS Enterprise Miner to Make Course Enrollment Recommendations Shawn Hall source 8
SESUG 2017 Discovering CMS Data for Healthcare Research Laxminarayana Ganapathi,
Matthew Urato,
Jean Hastie,
Merry G. Rabb		 source 9
SCSUG 2017 The Cox Hazard Model for Claims Data Samuel Berestizhevsky,
Tanya Kolosova		 source 17
PHUSE EU 2017 Real World Data Surprises Ewa Sleszynska-Dopiera,
Jan Rudnik		 source
presentation source		 4
MWSUG 2017 Claim Analytics Mei Najim 18
MWSUG 2017 Nothing to SNF At: Evaluating an intervention to reduce skilled nursing home (SNF) length of stay Andrea Frazier 4
MWSUG 2017 The Cox Hazard Model for Claims Data: Bayesian non-parametric approach Samuel Berestizhevsky,
Tanya Kolosova		 17
WUSS 2017 The Cox Hazard Model for Claims Data Samuel Berestizhevsky,
Tanya Kolosova		 source 17
PharmaSUG 2017 Analyzing data from multiple clinical trials using SAS Real World Evidence Jay Paulson,
David Olaleye		 source 13
SGF 2017 Construction of a Disease Network and a Prediction Model for Dementia Jinwoo Cho source 14
SGF 2017 The Development and Application of a Composite Score for Social Determinants of Health Paul A. LaBrec,
Ryan C. Butterfield		 source 16
SGF 2017 What Is Needed for True Population Health Intelligence? Laurie Rose,
Dan Stevens		 source 8
SESUG 2016 I See de Codes: Using SAS to Process and Analyze ICD-9 and ICD-10 Diagnosis Codes Found in Administrative Healthcare Data Kathy Hardis Fraeman source 9
PharmaSUG 2016 Four "Oops" Moments While Using Electronic Health Records to Identify a Cohort of Medication Users Steve Ezzy source 5
PharmaSUG 2016 The Hadoop Initiative: Supporting Today's Data Access and Preparing for the Emergence of Big Data Michael Senderak,
David Tabacco,
Robert Lubwama,
David O'Connell,
Matt Majer,
Bryan Mallitz		 source 9
SGF 2016 Evolving Fraud Types: Can Your Application Keep Up? Gordon Robinson source 11
SGF 2016 Health Care's One Percenters : Hot-Spotting to Identify Areas of Need and Opportunity Paul A. LaBrec source 14
SGF 2016 Medicare Payment Models: Past, Present, and Future Paul Gorrell source 9
SGF 2016 Risk Adjustment Methods in Value-Based Reimbursement Strategies Daryl Wansink source 6
SGF 2016 The Use of Statistical Sampling in Auditing Health-Care Insurance Claim Payments Taylor Lewis,
Julie Johnson,
Christine Muha		 source 18
SESUG 2015 A Health Analytics Framework Krisa Tailor,
Jeremy Racine		 source 10
SESUG 2015 Using SAS Programing to Identify Super-utilizers and Improve Healthcare Services An-Tsun Huang source 10
PharmaSUG 2015 Distributed data networks: A paradigm shift in data sharing and healthcare analytics Jennifer R. Popovic source 12
SGF 2015 All Payer Claims Databases (APCDs) in Data Transparency and Quality Improvement Paul A. LaBrec source 17
SGF 2015 Benefits from the Conversion of Medicaid Encounter Data Reporting System to SAS Enterprise Guide [presentation] Eric Sather source 4
SGF 2015 Data Aggregation Using the SAS Hash Object Paul M. Dorfman,
Donald J. Henderson		 source 20
SGF 2015 Establishing a Health Analytics Framework Krisa Tailor,
Jeremy Racine		 source 10
SGF 2015 Member-Level Regression Using SAS Enterprise Guide and SAS Forecast Studio Leigh McCormack,
Prudhvidhar Perati		 source 8
SGF 2015 Methodological and Statistical Issues in Provider Performance Assessment Daryl Wansink source 6
SGF 2015 Privacy, Transparency, and Quality Improvement in the Era of Big Data and Health Care Reform Paul Gorrell source 9
SGF 2015 Take a Bite Out of Crime with SAS Visual Scenario Designer Yue Qi source 10
SGF 2015 Using SAS Macros to Flag Claims Based on Medical Codes Andy Karnopp source
zip		 15
SGF 2015 Your Database Can Do SAS Too! Harry Droogendyk source 18
SESUG 2014 Let SAS Do the Coding for You! Robert Williams source 10
PharmaSUG 2014 Estimating Medication Adherence Using a Patient-Mix Adjustment Method R. Scott Leslie source 9
PharmaSUG 2014 Linking Healthcare Claims and Electronic Health Records (EHR) for Patient Management - Diabetes Case Study Paul A. LaBrec source 17
SGF 2014 Data Visualization in Health Care: Optimizing the Utility of Claims Data through Visual Analysis Krisa Tailor source 16
SGF 2014 SAS Solutions to Identifying Hospital Readmissions Weifeng Fan,
Maryam Sarfarazi		 source 8
SGF 2014 SAS XML Programming Techniques Christopher W. Schacherer source 39
SGF 2014 What's New in SAS Enterprise Miner 13.1 Jared Dean,
Jonathan Wexler		 source 16
WUSS 2013 Estimating Medication Adherence Using a Patient-Mix Adjustment Method R. Scott Leslie source 9
WUSS 2013 Macro to compute Charlson Comorbidity Scores from Medicare Data Irena Stijacic Cenzer,
Kathy Fung,
W. John Boscardin,
Ken Covinsky,
Louise Walter		 source 7
SCSUG 2013 The Concepts and Practice of Analysis with SAS Enterprise Guide Christopher W. Schacherer source 48
SESUG 2013 Fit Discrete Distributions via SAS Macro Fit Discrete Distributions source 5
SESUG 2013 Let SAS Do the Coding for You! Robert Williams source 9
SESUG 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Satish Garla source 15
PHUSE EU 2013 Anatomy of an Epidemiology Study Paul Murray source
presentation source		 12
PHUSE EU 2013 My Big Data Experience - Getting my Feet Wet in the PUddle and Still Treading Water 2 Years Later Robert Walls source
presentation source		 10
MWSUG 2013 Creation and Implementation of an Analytic Dataset for a Multi-Site Surveillance Study using Electronic Health Records (EHR) and Medical Claims Data Renuka Adibhatla,
Gabriela VazquezBenitez,
Mary Becker,
Amy Butani		 11
NESUG 2013 Continuous Enrollment Requirements in Epidemiologic Studies Jennifer R. Popovic 12
SGF 2013 Employee Wellness Programming Using SAS Enterprise Guide Sandra Brooks,
Tina Hembree,
Yehia H. Khalil		 source 7
SGF 2013 Extraction, Transformation, and Loading (ETL) for Outcome Measures of Workers? Compensation Benefits Mike Maier source 10
SGF 2013 Healthcare Claims Processing with Base SAS through Denormalization of ANSI 837 Format Roberto Valverde,
Victor Shigaev		 source 7
SGF 2013 Medical Versus Pharmacy Insurance: Which Is More Cost-Effective for Providing the Prescription? Solving the Problem Via SAS Enterprise Guide. Amber Schmitz source 7
SGF 2013 The Concepts and Practice of Analysis with SAS Enterprise Guide Christopher W. Schacherer source 48
SGF 2013 The SAS Programmer's Guide to XML and Web Services Christopher W. Schacherer source 32
SGF 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Albert Hopping,
Rick Monaco,
Sarah Rittman,
Satish Garla		 source 15
NESUG 2012 Remove Voided Claims for Insurance Data Qiling Shi 6
SCSUG 2012 The SAS Programmer's Guide to XML and Web Services Christopher W. Schacherer source 32
PHUSE EU 2012 Novel Programming Methods for Working with Large Claims Databases Richard R. Allen source
presentation source		 12
PHUSE EU 2012 Validation in Epidemiological Studies [presentation] Raimund Storb source 24
MWSUG 2012 Comparative Medication Adherence for Antihypertensive Therapy in Rural Ambulatory Clinics Terrence J. Adam 3
MWSUG 2012 The SAS Programmer's Guide to XML and Web Services Christopher W. Schacherer 32
SGF 2012 Deep Dive into the PIM and DDI Data Michelle Hopkins source 18
SGF 2012 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden source 12
SGF 2012 SAS Solutions Make HEDIS Measures Programming Easier Qingfeng Liang source 9
SESUG 2011 Assign Overpayment to Insurance Data with Adjustments Assign Overpayment source 5
MWSUG 2011 Deep Dive into the PIM and DDI Data Michelle Hopkins 20
MWSUG 2011 Remove Orphan Claims and Third party Claims for Insurance Data Qiling Shi 5
NESUG 2011 Assign Overpayment to Insurance Data with Adlustments Qiling Shi 6
NESUG 2011 Common Sense Tips and Clever Tricks for Programming with Extremely Large SAS Data Sets Kathy Hardis Fraeman 8
NESUG 2011 Drug Surveillance and Effectiveness Epidemiology Research - Questions to Ask Your Epidemiologist Roberta J. Glass 5
NESUG 2011 Using SAS To Identify Cancer Treatment Patterns in Administrative Claims Data Laurie Hamilton 15
SGF 2011 After SAS Performs the Surgery, Excel Applies the Make-Up: Making Healthcare Data Look Pretty Andrea Scott source 5
SGF 2011 Develop Effective Disease Management Program for Managed Care Organization Using SAS Qingfeng Liang source 8
SGF 2011 Healthcare Intelligence: The Challenge of OLAP for Healthcare Data John Leveille source 10
SGF 2011 Quantitative requirements for non-life insurance under Solvency 2 Sverre Grevskott source 8
SGF 2011 Ratemaking Using SAS Enterprise Miner: An Application Study Billie Anderson source 20
NESUG 2010 After SAS Performs the Surgery, Excel Applies the Make-Up: Making Healthcare Data Look Pretty Andrea E. Scott 5
SESUG 2010 Detecting Medicaid Data Anomalies Using Data Mining Techniques Shenjun Zhu,
Qiling Shi,
Aran Canes		 source 9
PharmaSUG 2010 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden 12
SGF 2010 Physician Practice Pattern Variation: Using Data Mining and Predictive Modeling to Identify and Control Costly Treatment Patterns David C. Ogden source 12
SGF 2010 Segmenting Textual Data on Automobile Insurance Claims David Dobson source 9
NESUG 2009 All Rolled Up Into One: Using SAS to Generate Patient-Level Analysis Files from Insurance Claims Data Kathy Hardis Fraeman 12
PHUSE EU 2008 Automated Drug Safety Signal Detection with Guided Ana Eric C. Brinsfield,
David Olaleye		 source 7
NESUG 2008 Common Sense Tips and Clever Tricks for Programming with Extremely Large SAS Data Sets Kathy Hardis Fraeman 7
NESUG 2008 Just What the Doctor Ordered: Using SAS to Calculate Patient Drug Dose with Electronic Medical Record (EMR) Prescription Data Kathy Hardis Fraeman 9
NESUG 2008 Orchestrating SAS Processes Using Business Process Management (BPM) Software Kimball Lewis 11
SGF 2008 Using PROC GENMOD to find a fair house insurance rate for the Norwegian market Sverre Grevskott,
Sten Sture		 source 9
SESUG 2007 Data Mining Episode Groupers Patricia B. Cerrito source 13
PharmaSUG 2007 Efficient Storage and Processing of Sequential Indicators Using SAS Bitwise Functions Gerhardt Pohl,
Wenyu Ye		 5
SGF 2007 Critical Success Factors for Rate Making with SAS Enterprise Miner Hrushikesh Khopkar,
Jay King		 source 17
SGF 2007 Pipes and Threads: Performance Testing of Advanced Scalability Features in SAS9 Gerhardt Forst,
Fred R. Widel,
Mario Burger,
Thomas H. Pohl		 source 10
SESUG 2006 Many to One Using a SAS DATA Step and PROC MEANS Jennifer L. Waller source 9
NESUG 2006 Linking SAS Analytics, U.S. Census Gazetteer Data and ArcView Geocoding Software for Medicare Fraud Screening Laurie Hamilton 10
PharmaSUG 2006 The Skinny on Processing Very Large Health Claims Data Sets Gopal Rajagopal,
Blue Bell		 10
SUGI 2006 80 Ways to Spell "Refrigerator" Joshua P. Becker,
John Wallace		 source 10
SUGI 2006 Efficient Construction of a "One-Row-per-Subject" Data Mart for Data Mining Gerhard Svolba source 16
NESUG 2005 Automated Conversion of Medicare Data Files into SAS Data Sets Stephanie Raymond,
Jia Lan,
David Shamlin		 7
PharmaSUG 2005 Programming and Data Differences Between Clinical Trials and Observational Studies Margaret M. Coughlin 6
NESUG 2002 Improving Upon Success: An Integrated Healthcare Business Solution Craig Dickstein,
Christopher Yindra,
Alan Dickson		 10
SEUGI 2002 Medicaid Data Warehouse [presentation] Anthony Simmons source 12
SUGI 2002 Using the Magical Keyword 'INTO:' in PROC SQL Thiru Satchi source 7
NESUG 2001 Processing Dates in Health Care Enrollment Data Thiru Satchi 3
NESUG 2001 Recyclable Code - Building and Using Generic SAS Macros for Ragged Data Marts Ralph W. Leighton 10
NESUG 2001 Using the Magical Keyword 'INTO:' in PROC SQL Thiru Satchi 7
SEUGI 2001 Business Process Management: A Key IT Management Challenge [presentation] Daniel J. Squillace source 28
SUGI 2001 Summarizing to the One-Record-per-Person using PROC SUMMARY: When to Use CLASS and When to Use BY Sylvia C. Tze source 4
SUGI 2001 Tips for Using PROC SQL to Extract Information from Medical Claims Data Sets Clayton Wells source 4
WUSS 2000 Summarizing to the One-Record-Pere-Oerson Using PROC SUMMARY: When to Use CLASS and When to Use BY Jenny Yu source 6
SUGI 2000 Building a Low Cost SAS Data Warehouse on NT Workstation Zhuan (John) Xu source 4
SUGI 2000 Using the Magical Keyword 'INTO:' in PROC SQL Thiru Satchi source 8
MWSUG 1999 Informing Doctors Who Manage Care: A SAS - based Physicia Profiling and Incentive System Mary F. MacDougall,
William C. Murphy		 4
NESUG 1998 Dealing With Health Care Data Using the SAS Alan C. Wilson,
Marge Scerbo		 6
SUGI 1998 Enhanced Data Support Methodology (EDSM): Using Technology for Competitive Advantage for Managed Health Care William J. Glosenmeyer source 7
SUGI 1998 Purge Those MERGE Problems: Realistic Solutions for Accurate and More Complete Matching of Inexact Data Fields that Occur in the Everyday World Judy Palermo source 6
PNWSUG 1997 PROC REPORT, A Guided Tour Martin Haase 7
WUSS 1997 Managing Large Health Insurance Claims-Based Files: Tricks and Techniques Miriam G. Cisternas,
Marcia Stoddard		 source 4
NESUG 1997 From 50,000,000 Claims to One Analytical File Louise S. Hadden,
Mike Murphy,
Alan J. White		 6
NESUG 1997 Tips and Techniques for Processing Complex Databases: An Example With Health Care Claims Files Linda Nelsen 8
SUGI 1997 From 50,000,000 Claims to One Analytical File Louise S. Hadden,
Mike Murphy,
Alan J. White		 source 6
SCSUG 1996 Why Knowing About Our Customers Helps Our Business Mark Brown 4
NESUG 1996 Using PROC TRANSPOSE to Facilitate the Processing, Analysis and Reporting of Health Care Claims Data Bryan K. Beverly 6
WUSS 1996 Measuring Performance Between PROC SQL and the Merge Approach Martin Haase source 5
WUSS 1996 PROC SQL as an Alternative to Multiple SORT/MERGE Statements Robert Bachler source 3
PNWSUG 1996 Receiving and Distributing Data Nationality: A SAS Solution to HEDIS Reporting Sue Freimuth,
Christopher Yindra		 6
SUGI 1996 Database Marketing and Business Geographies Mark Brown,
Jack Bulkley		 source 6
SUGI 1996 Receiving &Distributing Data Nationally: A SAS Software Solution to HEDIS Reporting Christopher Yindra,
Sue Freimuth		 source 7
SUGI 1996 SAS Software: One Stop Shopping for Re-engineering Diane E. Brown source 5
MWSUG 1995 Using SAS/QC To Automate The "Magnificent Seven" Tools of Quality Roderick Lashley 8
NESUG 1995 PROC FORMAT: Use of the CNTLIN Option For Efficient Programming Karuna Nerukar,
Andrea Robertson		 7
NESUG 1995 The Adoption of Computer Interface Technologies in Health Services Delivery Richard Switalski 9
WUSS 1995 PROC REPORT, A Guided Tour Martin Haase source 6
SUGI 1995 Fuzzy Joins using SOL Jack N. Shoemaker source 10
SUGI 1995 SAS: The Complete Solution for Medical Data Analysis Diane E. Brown source 6
SUGI 1995 The Other Five Percent - Writing SAS Code for Multiple Operating Systems Ryan K. Carr,
Daniel R. Bretheim		 source 6
SCSUG 1994 Predicting Managed Care Hospital Discharges and Bed Days Marsha S. Weston,
Darlene M. Reinhard		 17
NESUG 1994 Fuzzy Joins Using SQL Jack N. Shoemaker 10
MWSUG 1994 SAS: The Complete Solution for Medical Data Analysis Diane E. Brown 10
MWSUG 1994 The Other Five Percent - Writing SAS Code for Multiple Operating Systems Ryan K. Carr,
Daniel R. Bretheim		 6
SUGI 1993 SAS Software to Fit the Generalized Linear Model Gordon Johnston source 8
SESUG 1993 Using SAS to Analyze Health Status in Insurance Claims Richard N. Lieberman 10
NESUG 1992 PROC FORMAT Jack N. Shoemaker 6
SUGI 1991 SAS Report Writing in an HMO Claims Database Environment for Utilization Review Lynn M. Thome,
David Olagunju		 source 6
SUGI 1990 The SAS System for PCs: Management Reporting Using Data from External Sources Hugh G. McCabe source 3
NESUG 1989 Using the SAS System for Strategic Health Planning Stephan Parente 3
SUGI 1989 Generation of Form Letters with SAS Software John B. Nail source 5
SUGI 1989 SAS Applications in the Health Care Industry William J. McDonald,
J. Jon Veloski		 source 7
SUGI 1988 Extraction from Enormous Sequential Health Care Claims Data Files Using Multiple Format Tables Nancy Fox,
Craig K. Ray		 source 7

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