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The Wisdom of Crowds: Can Online Clinician Engagement Impact Health Technology Assessment?

The Wisdom of Crowds: Can Online Clinician Engagement Impact Health Technology Assessment?. Carl N. Kraus, M.D. Vice President, Medical Affairs Medscape September 10, 2012 2012 AHRQ Annual Conference.

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The Wisdom of Crowds: Can Online Clinician Engagement Impact Health Technology Assessment?

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  1. The Wisdom of Crowds: Can Online Clinician Engagement Impact Health Technology Assessment? Carl N. Kraus, M.D. Vice President, Medical Affairs Medscape September 10, 2012 2012 AHRQ Annual Conference Disclaimer: Any views or opinions presented here are solely those of myself and do not necessarily represent those of Medscape. The examples included in this presentation are intended for discussion purposes only. I have no financial relationship with anti-obesity manufacturers.

  2. Outline Crowdsourcing and online clinician content consumption Stakeholder disparity in health technologies Case Study: Obesity

  3. Background • 2004: James Surowiecki – thesis is that independently deciding individuals (groups) can make better decisions and predictions than individuals/experts. • There are differences between “wise” crowds and “irrational” crowds: • Diversity of opinion • Independence of opinion • Decentralization • Ability to aggregate opinion

  4. Medscape’s Role in Content Consumption Oath of care Improve patient care REMS Access to therapies MoL, MoC Ability to practice 2.6 million U.S. physician visits per month 33 distinct specialty sites 539,000 12-month active U.S. physicians 312,000 U.S. Physicians using Medscape via Mobile

  5. Medscape Environment as a Platform for “Crowdsourcing?” • Diversity of opinion • Multiple specialties • Multiple professions • Multiple geographic locales • Independence of opinion • Response of one participant does not impact that of another • Decentralization • Experience of each individual influences responses locally • Ability to aggregate opinion • Data capture is electronically structured and can be subsequently analyzed Conclusion: leveraging the opinion of clinicians “may” provide insight into the future value of health technologies

  6. Primary Stakeholders in Health Technology Adoption Superiority vs NI ex vivo -omics BR Comm FIH PP vs ITT • Technology assessors • CDER • CBER • CDRH • CMS • AHRQ/NICE • Insurers • Venture Capital • CROs (risk sharing) • Technology users • Physicians • Patients • Caregivers • Nurse practitioners • Physician assistants • pharmacists What “developer/assessor” variables might be of impact to the user community? • Technology developers • Biotech • Pharma • Device manufacturers • Application developers

  7. Why Opinions Vary Modified Oath of Geneva: • “The health and life of my patient will be my first consideration; I will maintain by all means in my power, the honor and the noble traditions of the medical profession” • Credible accessible data for analysis: • Curbside information • Product label • Peer reviewed clinical studies • CME • Promotional education 21CFR314.126 (new drug regulations): • FDA’s role is to determine whether “an investigation is adequate and well-controlled…. the primary basis for determining whether there is ``substantial evidence'' to support the claims of effectiveness for new drugs.” • Credible accessible data for analysis: • Pharm/tox • Clin/pharm • Efficacy • safety

  8. Why Clinicians Face Learning Curve Constraints on New Technologies • Follow-up from last visit (lab results, films, consults) • Interval changes • Stratify diagnostic/therapeutic interventions based on CC/PMH/HPI • Use of scoring tools with documentation (e.g., CHADS2, Depression scales) • Monitor for any drug toxicity or futility • Preventive health (US Preventive Services Task Force) – age, gender specific. • What to expect next • Questions and education on critical topics Triage Average length of encounter (adult medicine: 11 minutes) Prevent Health 2 min Average length of encounter (pediatric medicine: 14 minutes) Tox 1 min History/exam/Dx/Rx Plan 3 min Follow up 1 min Change 1 min Scoring 2 min Edu 1 min Average time spent on staying current/week: 35 min)

  9. To be clear: factor that impact an FDA decision and expert opinion may not necessarily equal a clinician’s decision to prescribe Adverse Event Signal • Bench/ex vivo • Animal • Frequency/severity/character of AE • Duration of effect • Magnitude of effect • Presence of prolonged prodrome • Confidence of attribution Marketplace Parameters Need in the marketplace Individual benefit Route of delivery History of safe utilization Limits of tolerance (society vs individual) Projected utilization

  10. Are there Developer/Assessor Variables that Can be Evaluated by Users? - Obesity Source: AHRQ Healthcare Horizon Scanning System Priority Area 10 - Obesity The country is becoming more obese Almost every doctor takes care of obese patients Congress and FDA believe that the lack of drugs is an unmet medical need (“concerns over lack of availability of pharmacotherapies approved by the U.S. Food and Drug Administration (FDA) for treating obesity were expressed in September 2011 by the U.S. Congressional Committee on Appropriations. The committee stated “the lack of obesity medications is a significant unmet medical need.” This committee directed FDA to develop a pathway by March 30, 2012, to support development of antiobesitytreatments”) Experts generally indicated that both patient and clinician acceptance would be high for combination drug because the potential to eliminate long-term sequelae of obesity-related diseases is critically important

  11. Method Case vignette: Ms. Lawrence is an obese businesswoman that is interested in making a change; getting tired, little time and has heard there may be some “new options.” More information clinician management opinion More information More information

  12. Deciphering the Crystal Ball in Obesity: Can you predict the future of care? What is your profession? • 230 Respondents • 98% Respondents Physicians • 84% > 10 Obese Patients/Month Cumulative Respondents 8/25/12 – 9/5/12 (14 days) How many obese patients do you encounter on average each month? 6 Question Survey Posted 8/25/2012 Results Through 9/7/2012

  13. Who Provides Care to Ms. Lawrence? National Encounter Estimates by Physician Specialty, 2009 Women with a BMI ≥ 40 Between 45-55 y.o. Deciphering the Crystal Ball in Obesity: Can you predict the future of care? n=5,553,813 n=230 Source: United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Health Statistics. National Ambulatory Medical Care Survey, 2009 [Computer file]. ICPSR31482-v3. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2011-11-17. doi:10.3886/ICPSR31482.v3

  14. Who is Ms. Lawrence? Race National Encounter Estimates, 2009 Women with a BMI ≥ 40 Between 45-55 y.o. Top 10 Drugs Top 10 Diagnoses Region Source: United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Health Statistics. National Ambulatory Medical Care Survey, 2009 [Computer file]. ICPSR31482-v3. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2011-11-17. doi:10.3886/ICPSR31482.v3

  15. Deciphering the Crystal Ball in ObesityAssessing Time on Market • Case Summary • Ms. Lawrence is a 50 year old morbidly obese woman (BMI = 41) with a 5 year history of hypertension and a 3 year history of type 2 diabetes. She is a busy executive and travels frequently, does not have a diet or exercise plan and is easily fatigued. She is current on a regimen of metformin and insulin glargine (high dose) as well as losartan with good glycemic (HbA1c = 7.2) and blood pressure control (averaging 120s/80s mm Hg). Because of her very busy lifestyle, increasing fatigue and poor self image, she seeks your recommendations on weight loss options. • Labs • Hg: 12.1 g/dL, LDL: 125 mg/dL, HbA1c: 7.2, LFTs: AST – 22 IU/L ; ALT – 27 IU/L, Thyroid studies normal

  16. Time on Market: Recommended TherapyPercent of Respondents Answering 4 or 5 (Recommend) PCP: surgery > RxComb > RxNME Surgeons: new surgery > established > Rx Endo: RxCombo > RxNME > surgery (n=83) (n=39) (n=12)

  17. Deciphering the Crystal Ball in ObesityImpact of Nonclinical Data • Case Summary • Mr. Lawrence is very engaged during the clinical encounter, and after hearing your recommendation she decides that a surgical procedure is not a treatment option she wants to consider now. She wants more information about the two new drug treatments you have brought to her attention. After reviewing more of the product label you learn that one of the drugs had a significant animal safety signal which the other did not..

  18. Non-clinical: Recommended TherapyPercent of Respondents Answering 4 or 5 (Recommend) There is agreement between PCP/Surgeon on the need for caution re: animal signal; not so for endocrinologists (n=74) (n=37) (n=12)

  19. Deciphering the Crystal Ball in ObesityAssessing Clinical Trial Subject Cohort • Case Summary • Ms. Lawrence doesn’t want to wait 5 years and is eager to do something as soon as possible. You discuss the data available in both product labels and show her that the non-combination product had more data on women in her BMI category, as well as in her age range, than the other product label did (albeit with slightly lower efficacy).

  20. Clinical Trial Subject Cohort: Recommended TherapyPercent of Respondents Answering 4 or 5 Endo> PCP > Surgeon consider trial subject cohort important

  21. Conclusions Different “crowds” have different responses to the same data This disparity in opinion regarding anti-obesity interventions is present and can be characterized – sources are not here assessed (e.g., variable information burden by specialty) “Horizon scanning,” using a group of experts, could be augmented with larger technology user groups. Similarly, “safety scanning” might be a useful, proactive means of assessing a technology’s market risk if the user community does not understand how to best use such a technology

  22. Medscape Team: Acknowledgements This is new – using an education platform for a different purpose. Can this… 1. better assess tolerability of harm? 2. Inform benefit/risk communications? 3. Improve REMS development? Collaboration welcome! Thanks to the Medscape Team Alan Baldwin Karen Overstreet Cyndi Grimes Linda Giering Lisa Miele Victoria Anderson

  23. Thank YouCarl N. Kraus, M.D.ckraus@medscape.net

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