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George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
George Neumann PM Summit NYC 2009
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George Neumann PM Summit NYC 2009

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  • Transcript

    • 1. Prediction Markets In Health Care George R. Neumann Iowa Electronic health Markets
    • 2. Markets In Health Care The IEhM has worked on 3 different types of health markets Seasonal Influenza Avian Influenza Syphilis I will discuss what we have learned from these markets
    • 3. Markets In Health Care Why are Prediction Markets Important in Health Care?
    • 4. Markets In Health Care Why are Prediction Markets Important in Health Care? Cost savings with greater forecast accuracy o o Influenza causes: 36,000 deaths annually in the U. S. 120,000 hospital admissions Medical treatment can be adjusted if an outbreak of flu is anticipated o Prophylaxis of nursing homes o A vaccine is available as are several medications
    • 5. Markets In Health Care Vaccine effectiveness depends on timing as well as predictions about which strains to put in the vaccine. It takes about 2 weeks for the vaccine to become effective. Antiviral medicines such as Oseltamvir (Tamiflu) require 48 hour advance treatment
    • 6. INFLUENZA MEASURES CDC COLOR DEFINITIONS WIDESPREAD REGIONAL LOCAL SPORADIC NO ACTIVITY DATA MISSING
    • 7. Markets In Health Care The prediction problem with influenza IOW A 20 07-2 008 2006- 2007 2005-2006 2 004- 2005 2003- 2004 20 02-2 003 200 1-20 02 200 0-20 01 1999- 2000 WEEK CO LOR COLOR COLO R COLOR COLOR CO LOR CO LO R CO LO R COLOR Y Y Y Y Y Y Y Y Y 40 Y Y Y Y Y Y Y Y B 41 Y G Y Y Y Y Y Y Y 42 43 Y Y Y Y Y Y Y Y Y 44 Y G Y Y Y Y Y Y G 45 Y G Y Y Y Y Y Y G 46 G G Y Y Y Y G Y B G G Y Y G Y G Y G 47 G G Y Y B Y G G G 48 G G G G R Y Y G G 49 50 G B G G R Y G G G 51 G B G P R Y G G R 52 G B G B R Y G G R 1 P B B B R Y G G R 2 P B B B R G G B R B R B B B G Y B R 3 B R B R B G G R R 4 5 R R B R P B B B G 6 R R B R P R B B G 7 R R B R G R G B G 8 R R R R G R B R Y 9 R R R B Y R B G Y R B R B Y B B G Y 10 R B R P Y G G Y Y 11 12 R P B G Y G G G Y 13 R P B G Y G G Y Y 14 B G P G Y G G Y Y 15 G G G G Y Y G Y Y 16 G G G G Y G G Y Y Y G G Y Y G G Y Y 17 Y Y Y Y Y Y G Y Y 18
    • 8. Markets In Health Care The epi Curve for Iowa The Epi -C urve 6 5 4 2007__Act ual 3 7-Year His tor i cal Aver a ge 2 1 0 Fl u Week
    • 9. Markets In Health Care The CDC provides a state-by-state description of influenza activity but it is two weeks out of date before it becomes available.
    • 10. Markets In Health Care We have run markets in Iowa, North Carolina, and Nebraska Markets by Year and State. Year State Number of Markets 2007-2008 Iowa 31 Nebraska 31 North Carolina 31 2006-2007 Iowa 29 North Carolina 27 2005-2006 Iowa 29 2004-2005 Iowa 14 Total 192
    • 11. Markets In Health Care Who participates? Trader Characteristics in Iowa-2006-2007 Occupation Freq. Percent Cumulative %. -- 1 1.12 1.12 Administrator 3 3.37 4.49 Microbiologist 14 15.73 20.22 Nurse 15 16.85 37.08 Other 21 23.60 60.67 Pharmacist 8 8.99 69.66 Physician 20 22.47 92.13 epidemiologist 7 7.87 100.00 Total 89 100.00
    • 12. Markets In Health Care What did we learn? Trader heterogeneity can be a curse Software and training materials have to be adapted to the knowledge and inclinations of the audience. This is hard to do when the audience differs in background. It is essential to do if members have different amounts and types of information. E.g. microbiologists vs. school nurses. PM’s work well, even with heterogeneous traders
    • 13. FORECAST ACCURACY- IOWA 2004-2008 0.75 0.70 0.65 0.60 0.55 % Ex actly Correct IA_ MKT 0.50 IA_ HIST IA_ MARKOV 0.45 0.40 0.35 0.30 0.25 1 2 3 4 5 WEEKS IN ADV ANCE
    • 14. Forecast Success % Correct Method 5 weeks 3 weeks 1 week Markets 59% 63% 68% History 49% 49% 49% Markov 30% 43% 57%
    • 15. Forecast Success % Δ in No. Correct State 5 weeks 3 weeks 1 week IA 106% 146% 136% NC 78% 125% 150%
    • 16. Avian Flu We partnered with PROMED to recruit traders from around the world. There are about 20,000 members of the International Society for Infectious Disease, located in 155 countries. Promed-mail is their major way to communicate daily.
    • 17. Avian Flu: Trader Locations
    • 18. Avian Flu Contracts typically were about how many cases of Avian H5N1 would occur in a specific region in a specific time period (6 months). Contracts were also traded on whether there would be human to human transmission of Avian Flu in a specific time period.
    • 19. Q.: Will there be human to human transmission of H5N1 in the EU by 12/31/2008
    • 20. Q: Will the World-wide # of deaths from Avian Flu exceed xxx
    • 21. Seasonal and Avian Flu Finding the right audience for a PM can make the job easier. Emphasis on graphical display helps a lot with medical types. Future projects: Virus strain prediction, Vaccine Effectiveness Animal infections
    • 22. Syphilis Markets There are two significant features of syphilis: quantity of cases and gender mix
    • 23. Total New Syphilis Cases-Nationwide 1984-2006 60000 50000 40000 30000 20000 10000 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
    • 24. Syphilis — Reported cases : United States, 1941–2007 Cases (in thousands) 600 P&S Early Latent Total Syphilis 480 360 240 120 0 1941 46 51 56 61 66 71 76 81 86 91 96 2001 06
    • 25. % 0% 10% 20% 30% 40% 50% 60% 19 84 19 85 19 86 19 87 19 88 19 89 19 90 19 91 19 92 19 93 19 94 19 95 19 Year 96 1984-2006 19 97 19 98 19 99 20 00 20 01 20 02 20 Fraction of New Syphilis Cases That Are Female 03 20 04 20 05 20 06
    • 26. Syphilis Markets No results so far –markets go operational in May. But lots of enthusiasm at the CDC. Check it out at http://iehm.uiowa.edu/iehm/index.html

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