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Patient-Level Data Tutorial
Date: May 16, 2007.
Venue: Ritz-Carlton, Ten Avenue of the Arts, Philadelphia, PA 19102

Sample of Questions Addressed

Here are some of the questions we will be addressing.

q       Just what is patient-level data? What’s the difference between patient-level and patient-centric data? What does patient-level data really boil down to? What can it achieve that good old physician-level data such as IMS Xponent or NDC Source Prescriber can’t?

q       How does the offering of data vendors such as IMS, NDC/ArcLight, Dendrite, Verispan, PharMetrics, Ingenix, Solucient, Medstat, Premier, AdvancePCS/Caremark to mention the most conspicuous ones differ from one another? What are the implications of working with pharmacy/switch, claims, discharge, or stay data? In what respects do databases from one-plan, multi-plan, PBM, and employer group claims data differ? Why am I better off using one database over another when I am charged with answering certain business questions or analyzing certain therapeutic areas?

q       Some data vendors swear only by cubes. What’s a cube anyway? How does the cube measure up with actual patient-level transactions? Pros and Cons? Why should I care about UB-92, Form 1500, ICD-9, CPT-4, HCPCS, APC, J-code, etc.? What’s the deal with timeliness, coverage, and connectivity?

q       How are pharmaceutical companies using patient-level data today? What is the state of the art? What are the current challenges? What are the emerging trends? What does the industry have in store for us? Is it true patient-level data allows us to measure hospital-retail spillover, identify influencers, leverage system targeting, in addition to performing bread-and-butter persistency, compliance, and switching analyses?

q       Is HIPAA nipping patient-level data in the bud? How come the Bush administration has decided to increase spending by 53% to boost health connectivity and CPOE in the hospitals? How does that jibe with IOM and the Markle Group?

q       Your mandate is to boost the skills and competence of your department. You may even have been charged with equipping your company with patient-level data and turning around patient-level analyses on a regular basis? But which patient-level database to acquire? What questions to ask? Running an evaluation sounds like a good idea. But you have not done that before. How to pull this off without jeopardizing or limiting your career?

q       You are planning on attending patient-level data conferences. Good idea! But how to make sure you get the most out of those events. Indeed, you want an objective lay of the land: vocabulary, state-of-the art, industry trends and perspectives, success stories, failures, etc. More importantly you have a stash of well-articulated and inchoate questions alike that you want answered and put in perspective.


This tutorial is a solid 8:45 a.m. to 4:30 p.m. day and covers the topics listed below. After this tutorial, you’ll have a solid grasp of what patient-level data is, of the nuances among different strands of patient level data and the bearing on the analyses performed. You’ll have a good appreciation of the offering of the major data vendors and what’s brewing in the industry. You’ll have the lowdown on fundamental analyses such as compliance and persistency (adherence), switching, dosing, and the like. You will also be exposed to dramatically novel applications of patient-level data (e.g.. spillover, influencers, molecular targeting, etc.). Last but not least, you’ll be better equipped back in the ranch to advise your company as to the best patient data course to embark on, to vet and select patient-level databases, to build the case for patient-level data to upper management, and to enthuse analysts already overwhelmed with too much data.

8:45 a.m. – 9:00 a.m.
9:00 a.m. – 9:50 a.m.
What's the Deal? Definitions.
10:00 a.m. – 10:50 a.m.
Industry Offering, Trends, and Perspectives
11:00 a.m. – 11:50 a.m.
Compliance, Persistency, Switching, etc.  (Fundamental Analyses) 
12:00 p.m.– 1:00 p.m.
1:00 p.m.– 1:50 p.m.
Review of Material Covered and Open Discussion
2:00 p.m. – 2:50 p.m.
Measuring Spillover, Identifying Influencers, Deploying Molecular Targeting (Advanced Analyses)
3:00 p.m. – 4:20 p.m.
Case Studies
4:20 p.m. – 4:30 p.m.
Evaluation & Conclusion


About the Tutorial Leaders

Jean-Patrick Tsang, PhD & MBA (INSEAD)

Jean-Patrick Tsang is the Founder and President of Bayser, a Chicago-based consulting firm dedicated to pharmaceuticals sales and marketing.
JP started up Bayser in April 1996 after a two-year stint in a larger consulting firm. JP's contribution to the industry includes: adaptive targeting based on individual promotion response curves, “Hood Robin” principle for portfolio optimization, a probabilistic approach to the managed care masking problem, a quota reallocation scheme to re-level the managed care playing field, a four-point evaluation scheme to assess co-promotion opportunities, a music-like notation to capture the terms of a deal, and a CRM tool to enhance communication and planning between the district  manager  and the sales rep.
JP is a big proponent of patient-level data, not only for the longitudinal analyses, but also for loftier endeavors it supports such as measuring hospital-retail spillover, identifying influencers & spheres of influence, and opening up new targeting paradigms such as system targeting.
JP publishes in Pharmaceutical Executive, Product Management Today, and other trade magazines, and talks at PMSA, PMRG, CBI, SRI, and IIRUSA.  In a previous life, JP worked on the automation of the design process of payloads for satellites, methaners/ethaners, and cruise-liners.  JP earned a Ph.D. in Artificial Intelligence from
Grenoble University and an MBA from INSEAD in France. He can be reached at (847) 920-1000 or bayser@bayser.com.

Igor Rudychev, PhD

Igor Rudychev is currently a Vice President of Bayser. He has intimate working knowledge of patient-level and patient-centric data, having completed several client engagements involving  identification of influencers and influence networks, KOL's and referral patterns, mapping of institutional neighborhoods, measurement of patient compliance and persistence, sources of business, patient segmentation hospital-retail spillover, hospital/retail switching, and the like.
In his patient-level data analyses, Igor leverages techniques from advanced mathematics, statistics, artificial intelligence, and elementary particle physics. In addition to performing and supervising client projects, Igor is involved in fundamental research  pertaining  to  the  deployment  of  patient-level data to solve key business questions of the pharmaceutical industry.
Igor co-authored articles with JP titled  “Distilling Influence Networks and Referral Patterns using Patient-Level Data”, Product Management Today (April 2003 issue), "Taking Compliance and Persistence Out of the Box", Journal of Longitudinal Data, Jan/Feb 2005 and
“Compliance and Persistence: Emerging Issues with Imatinib Therapy”, British Journal of Nursing, upcoming.

Prior to joining Bayser, Igor conducted research in optimization techniques applied to super string theory, the most promising avenue to the unification of quantum mechanics and Einstein's theory of gravity. Igor has a PhD in Theoretical Physics from Texas A&M. His hobbies include guitar and chess (Russian Candidate Chess Master at 13). He can be reached at (847) 679-8278 or igor@bayser.com.


This is what the attendees of the previous sessions are saying:

       “Sign up!”

       “Should be required for anyone using this type of data!”

       “JP’s insights into where the industry is heading, the motivation of the data vendors and the pitfalls of using that data are most interesting. Very helpful!”

       “Excellent review of various vendor capabilities and approach to working with vendors for quality, substance, content.”

       “Review of concepts and appendix thorough!”

       “Provides a complete understanding of the key differences in what elements are included in which sources.”

       “Very good! Should be required for market research department.”

       “Great job! This course applies to all levels of understanding/ knowledge”

       “JP’s humor most welcome! Great overview and explanation of what various databases contain.”

       “JP and Igor were so knowledgeable about specific vendors’ offerings!”

       “Intellectually challenging!”

       “Excellent class notes – plentiful and useful”

Companies that attended

Pharmaceutical companies that attended our tutorials include: Abbott, AstraZeneca, Aventis, Bayer, Bayer Diagnostics, BMS, Boehringer-Ingelheim, Centocor/J&J, Eisai, Eli Lilly, Forest Labs, GSK, Janssen/J&J, Merck, Novartis, Novo Nordisk, Ortho Biotech/J&J, Pfizer, P&G, Takeda, Roche, Roche Diagnostics, Sanofi-Aventis, Solvay, Wyeth, and Yamanouchi. 

Why Bayser?

First off, you'll have an objective evaluation account of the patient industry. We have no vested interest in any patient-level data vendor and will give you the untainted truth straight from the gut. We'll tell you what data vendors are loath to admit.

Second, we have done considerable research and have solid client experience under the belt. Here is a list of recent articles we penned on patient-level data:

  1. “Patient-level data come of age” that appeared in the May 2003 issue of Pharmaceutical Executive and was reproduced in the Nov 2003 issue of the International Pharmaceutical Review.
  2. “Distilling Influence Networks and Referral Patterns using Patient-Level Data” in the April 2003 issue of Product Management Today
  3.  “Hospital to Home: The Rx Spillover effect”, Pharmaceutical Executive, July 2003.
  4. “Patient-Level Data: A New Level of Analysis”, Pharmaceutical Marketing News, Aug 2003.
  5.  “Molecular Targeting”, Medical Marketing Media, February 2004.
  6. “Taking compliance and persistence out of the box”, Journal of Longitudinal Data, Jan/Feb 2005, pp 78-85.
  7. “Compliance and Persistence: Emerging Issues with Imatinib Therapy”, British Journal of Nursing, upcoming.
  8. "Patient-centered sample optimization", work in progress.

Below conferences we chaired on patient-level data:

  1. “Patient-Level Data – Leverage emerging data to maximize market potential”, Organizer and chairman of conference with CBI, Philadelphia, PA, June 5-6 2003.
  2. “Anonymous Patient-Level Data – Leverage emerging data to maximize market potential”, Organizer and Chairman of conference with CBI, Philadelphia, PA, Nov 16-17 2003.
  3. “Optimizing the use of patient-level data to enhance your marketing capabilities”, chairman and leader of pre-conference workshop “Introduction to classical and advanced patient-level analyses”, PEA Conference, Park Hyatt, Philadelphia, PA, March 22-23, 2004.
  4. Upcoming: “Patient-Level Data and Medicare Part D”, co-chair, IIRUSA, Baltimore, Nov 2-3, 2005.

Below is a selection of conferences where we uncovered some insights regarding patient-level data:

  1. “Measuring Hospital-Retail Spillover: Bridging and Holistic Techniques”, PMSA 2003, Orlando, FL, May 4-7, 2003.
  1.  “Patient-Level Data – Leverage emerging data to maximize market potential”, Organizer and chairman of conference with CBI, Philadelphia, PA, June 5-6, 2003.
  2. “Identification of Influencers using patient-level data”, PMRG Fall 2003, San Diego, Sep 21-23, 2003.
  3. “Nail down true ROI”, PMC 2003 Washington DC, Oct 2003 (co-presentation with Sanofi).
  4. “Anonymous Patient-Level Data – Leverage emerging data to maximize market potential”, Organizer and Chairman of conference with CBI, Philadelphia, PA, Nov 16-17 2003.
  5. “Building sociograms of physicians using upstream targeting”, IIRUSA conference on “Using market research to advance innovation and new product development for pharmaceuticals: Aligning marketing and development for commercial success”, Sheraton Rittenhouse Square Hotel, Philadelphia, PA, Feb 24-26, 2004 (co-presentation with Sepracor).
  6. “Optimizing the use of patient-level data to enhance your marketing capabilities”, chairman and leader of pre-conference workshop “Introduction to classical and advanced patient-level analyses”, PEA Conference, Park Hyatt, Philadelphia, PA, March 22-23, 2004.
  7. “How to harness the power of patient-level data”, workshop leader, Med Ad News Conference on Pharmaceutical Marketing Partnerships, New York, NY, April 19-21, 2004.
  8. “Challenges and opportunities involved in deploying patient-level data in pharmaceutical companies” Panel Moderator, CBI 2nd annual conference on patient-level data, Philadelphia, PA, June 3-4 2004.
  9. “Identifying KOL's for MSL's”, PEA conference on “Best Practices for Medical Science Liaisons”, Allertown Crown Plaza, Chicago, June 25, 2004.
  10. “Transcending Compliance and Persistency using Patient-Level Data”, Fall 2004 PMRG, Westin Copley Place, Boston, Sep 19-21, 2004.
  11. “Patient-Level Data: Overview and Analysis”, PBIRG Education Series, Olde Mill Inn at Basking Ridge, New Jersey, Sep 28, 2004.
  12. “Patient-Level Data Analyses for different departments of the pharmaceutical company”, Panel Moderator with IMS, SDI, and PharMetrics as panelists, SRI's 3rd Annual Pharmaceutical Marketing and Sales Summit, Buena Vista, FL, Feb 13-16, 2005.
  13. “Molecular Targeting – The New Targeting Paradigm”, IIR USA's Leveraging Longitudinal Data for Segmentation, Targeting, and Strategy Formation, West Princeton at Forrestal Village, Princeton, NJ, April 11-12, 2005.
  14. "Leveraging Referral Patterns and Spheres of Influence through Molecular Targeting", co-presentation with Kumar Kantheti, Solvay, PMSA 2005, Gaylord Opryland Hotel, Nashville, TN, May 15-18, 2005.
  15. "Reconstructing the Microcosm of the Physician for Superior Targeting", co-presentation with Sanofi-Aventis, CBI 3rd Annual APLD Conference, Philadelphia, June 2-3, 2005.



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