The PharmaSUG 2016 San Diego Single-Day Event has now concluded. The slides are available for download below. Thanks to UC San Diego for hosting the event, and to all who presented and attended. Don't forget that all paid registrants will receive a $75 discount for our annual conference coming in Baltimore in May 2017!
|Presentation (click for abstract)
|Presenter (click for bio)
|An Analyst’s Practical Guide for Reducing Time to Market
|Joy King and
|Creating PDF Annotations for aCRF
|Paper (PDF, 277KB)
|Plan for Success: Strategies for Efficient Development of a High Quality Study Data Reviewer’s Guide
|Slides (PDF, 1.14MB)
|Preparing ADaM and Related Files for Submission
|Slides (PDF, 665KB)
|The Study Data Standardization Plan as a Strategic Tool for Analysis & Reporting
|Slides (PDF, 1.48MB)
|Linking Healthcare Claims and Electronic Health Records (EHR) for Patient Management - Diabetes Case Study
|Paper (PDF, 80KB)
|Measuring Medication Adherence in Observational Data
|Paper (PDF, 157KB)
Presentation AbstractsAn Analyst’s Practical Guide for Reducing Time to Market
Joy King and Tho Nguyen
The data sets used for conversion to SDTM format first undergo the detailed and lengthy (months to year) clinical data management process. Today, the approach to clinical data management focuses most analytic resources on the task of hunting and gathering. Building an analytic environment and creating a process that is efficient, effective, and reliable will enable analysts to spend more time focused on gleaning insight from the data. To build such an analytic environment requires two main components:
- Build an integrated, late-binding data warehouse that becomes a safe, central repository of data that is organized and optimized for measurement, analysis, and reporting.
- Let the data warehouse do the “heavy lifting” for your analysts. Building analytic datasets (ADS) inside the data warehouse will greatly reduce, if not completely eliminate, the hunting, gathering and movement of data to build and execute analytic models.
Join us in this session to learn some very practical and useful tips using SAS and Teradata to further reduce analytic time and effort resulting in MUCH faster time to market!
Creating PDF Annotations for aCRF
Annotating a blank Case Report Form (blankcrf.pdf) by hand is an arduous process that can take many hours of precious time. Once again SAS® comes to the rescue! You can have SAS use the Study Data Tabulation Model (SDTM) specifications data to create all the necessary annotations and place them on the appropriate pages of the blankcrf.pdf. In addition you can dynamically color and adjust the font size of these annotations. This approach uses SAS, Adobe Acrobat®’s forms definition format (FDF) language, and Adobe Reader to complete the process. In this paper/presentation I go through each of the steps needed and explain in detail exactly how to accomplish each task.
Plan for Success: Strategies for Efficient Development of a High Quality Study Data Reviewer’s Guide
The US Food & Drug Administration (FDA) has requested that a Study Data Reviewer’s Guide (SDRG) be incorporated into a SDTM submission data package to help facilitate the FDA’s understanding of the study data and its relationship to any study reports associated with that data. The FDA and industry, via the PhUSE/CSS collaboration, have developed a template, completion guidelines and examples of the SDRG in practice. This presentation will explore the strategies you can deploy and steps you can take to work with these tools produce a document that will meet and hopefully exceed agency expectations.
Preparing ADaM and Related Files for Submission
This presentation compiles information from documents produced by FDA, CDISC, and CSS to identify what analysis data and other documentation is to be included in submissions, and where it all needs to go. It not only describes requirements, but also includes recommendations for things that aren’t so cut-and-dry. It focuses on the NDA and subset of BLA submissions that are covered by the FDA binding guidance documents.
The Study Data Standardization Plan as a Strategic Tool for Analysis & Reporting
The Study Data Standardization Plan (SDSP) has been requested by the FDA to facilitate the communication of a Sponsor’s intent to incorporate FDA endorsed data standards into the execution of their non-clinical and clinical development plans. Many regard the SDSP as just another regulatory obligation; this presentation will show how embracing this plan can actually help organize your thoughts and support communications both within your organization and with the FDA while achieving its primary goal of conveying your organization’s plan for implementing standards in route to preparing assets for regulatory filing.
Linking Healthcare Claims and Electronic Health Records (EHR) for Patient Management - Diabetes Case Study
Treo Solutions conducted a pilot project to assess the feasibility of linking healthcare administrative claims data to an electronic health record (EHR) data extract to enhance patient case management activities. We linked one year of healthcare claims data (2012) to the equivalent year of medical record data abstracted from the EHR system of a large Midwest commercial insurer. The claims database identified over 400,000 patients receiving services during 2012. Over 30,000 of these patients (7%) had a diabetes diagnosis. The EHR extract identified over 750,000 test records on over 92,000 patients in 2012 and included over 50 data elements. Measures identified in the EHR database included physical measures (the most common records), health history, health behaviors, radiologic and endoscopic tests, select prescription data and laboratory values. We used a subset of diabetes-related measures identified by the National Quality Forum for use in this analysis. These include blood pressure, hemoglobin A1c, low-density lipoprotein, microalbumin, retinal and foot exams. From this combined database we calculated that the majority of patients with a diabetes diagnosis on claims had no diabetes test results for the study year. Furthermore, a small number of patients without a known diabetes diagnosis had at least one out-of-range diabetes test. We summarize the strengths and weaknesses of administrative claims versus EHR data for patient classification and compliance analyses, as well as methodological issues in combining claims and clinical databases. Planned follow-up analyses include medication fill rate calculations, allowed cost comparisons for various patient groups, and health outcomes analyses.
Measuring Medication Adherence in Observational Data
Poor adherence to medication continues to be a worldwide problem despite decades of research, numerous multi-modal interventions and nationwide promotional campaigns. The Centers for Medicaid and Medicare Services (CMS) and several national health care quality organizations regard medication adherence as a major attribute of quality of care. The preferred method of measuring medication adherence is the Proportion of Days Covered (PDC) by medication(s) over a specified review period. This presentation describes importance of measuring adherence and the PDC measurement method using observational, or "real world", data. Included is a macro used to calculate PDC to estimate medication adherence.
Presenter BiographiesSteve Black
Steve Black has been programming in SAS for the past 15 years. He has presented at several national conferences and one day events. Steve enjoys finding new ways to get SAS to do all the nitty gritty work and he especially enjoys sharing with others the skills and techniques that he has learned.
Dave Izard currently serves as Senior Director of Clinical Data Standards and Chiltern International Limited. Supporting pharma/biotech since 1997 in a number of roles that focus on understanding and preparing clinical data for regulatory submission coupled with management of the interactions between sponsor and regulator, Dave is a frequent author, presenter and seminar instructor at PharmaSUG, SCDM and regional SAS events and participant in PhUSE/CSS efforts in support of optimizing the use of data standards.
Joy King is Principal Consultant and Practice Lead for Life Sciences Consulting at Teradata -- the world leader in analytical data warehousing. She consults with customers and prospects to evaluate, position and develop deployment strategies for Teradata solutions within their organizations. Ms. King is responsible for providing life sciences subject matter expertise in developing and executing the life sciences strategies for Teradata. She also supports public speaking engagements, events and industry press relations.
Paul LaBrec is Director of Research for the 3M Health Information Systems Populations and Payment Solutions group. He leads a team of research analysts in planning and conducting various research projects including the development and evaluation of analytic products, predictive models, health care program evaluations, or ad hoc research investigations for 3M customers. His academic background is in epidemiology and social science.
Scott Leslie is a Manager of Advanced Analytics for MedImpact Healthcare Systems, Inc. with 15 years of SAS® experience in the pharmacy benefits and medical management field. His SAS skills include SAS/STAT, SQL, Enterprise Guide, and Visual Analytics. Scott has presented at local, regional and international SAS user group conferences as well at various clinical and scientific conferences. He is an executive committee member of the Western Users of SAS Software (WUSS) and involved with the San Diego SAS Users’ Group (SANDS).
Sandra Minjoe is a Senior ADaM consultant at Octagon Research Solutions Inc, now part of Accenture Life Sciences. She has been an active member of the CDISC ADaM team since 2001 and joined the CDISC SDS team in 2010. Sandra has been in the Pharma/biotech industry since 1993, has led and worked on filings to both CDER and CBER, and is a regular presenter of papers, training classes, and tutorials.
Tho Nguyen is a Business Solutions Manager at Teradata Corporation. With more than 18 years in the information technology industry, Tho works closely with customers globally, R&D, and strategic partners to drive and deliver value-added business solutions in analytics, data warehousing and data management. Tho has written a book Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics which will be currently available online and at bookstores. It focuses on analytics and data management in an integrated environment with a collection of real world customer successes. All proceeds from the book will be donated to charities.