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

Assessment?Carl N. Kraus, M.D.

Vice President, Medical AffairsMedscape

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.

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Outline

• Crowdsourcing and online clinician content consumption

• Stakeholder disparity in health technologies

• Case Study: Obesity

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• 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

Background

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• 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

Medscape’s Role in Content Consumption

Improve patient care

Access to therapies

REMS

MoL, MoC

Oath of care

Ability to practice

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• 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

Medscape Environment as a Platform for “Crowdsourcing?”

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• Technology developers

– Biotech– Pharma– Device

manufacturers– Application

developers

Primary Stakeholders in Health Technology Adoption

• 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?

FIHex vivo -omics PP vs ITT Superiorityvs NI

BR Comm

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Why Opinions Vary

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

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

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1. Follow-up from last visit (lab results, films, consults)2. Interval changes3. Stratify diagnostic/therapeutic interventions based on CC/PMH/HPI4. Use of scoring tools with documentation (e.g., CHADS2, Depression scales)5. Monitor for any drug toxicity or futility6. Preventive health (US Preventive Services Task Force) – age, gender specific.7. What to expect next8. Questions and education on critical topics

Triage Follow up1 min

Change1 min

History/exam/Dx/Rx Plan3 min

Scoring2 min

Tox1 min

Prevent Health2 min

Edu1 min

Average length of encounter (adult medicine: 11 minutes)

Average length of encounter (pediatric medicine: 14 minutes)

Average time spent on staying current/week: 35 min)

Why Clinicians Face Learning Curve Constraints on New Technologies

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Marketplace Parameters • Need in the marketplace• Individual benefit• Route of delivery• History of safe utilization• Limits of tolerance (society vs individual)

• Projected utilization

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

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• 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 antiobesity treatments”)

• 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

Are there Developer/Assessor Variables that Can be Evaluated by Users? - Obesity

Source: AHRQ Healthcare Horizon Scanning System Priority Area 10 - Obesity

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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.”

clinician management

opinion

More information

More information

More information

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Deciphering the Crystal Ball in Obesity: Can you predict the future of care?

25-Aug

26-Aug

27-Aug

28-Aug

29-Aug

30-Aug

31-Aug

1-Sep

2-Sep

3-Sep

4-Sep

5-Sep

6-Sep

7-Sep

0%

20%

40%

60%

80%

100%

1% 5%

21%39%

46% 51% 53% 55% 58%

74%80%

93%97% 100%

• 6 Question Survey• Posted 8/25/2012• Results Through 9/7/2012

• 230 Respondents• 98% Respondents Physicians• 84% > 10 Obese Patients/Month

Physician98%

All Other2%

02%

1-21%

3-54%

6-108%

>1084%

How many obese patients do you encounter on average each month?

What is your profession?

Cumulative Respondents 8/25/12 – 9/5/12 (14 days)

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Who Provides Care to Ms. Lawrence?

Primary Care53%

Surgery14%

Ob/Gyn9%

Cardio2%

All Other22%

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

National Encounter Estimates by Physician Specialty, 2009Women with a BMI ≥ 40 Between 45-55 y.o.

Primary Care50%

Surgery25%

Cardio3%

Ob/Gyn1%

All Other/

Unk21%

Deciphering the Crystal Ball in Obesity: Can youpredict the future of care?

n=230n=5,553,813

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Who is Ms. Lawrence?

MIDWEST28%

NORTHEAST

13%SOUTH

41%

WEST18%

WHITE66%

BLACK14%

ASIAN0.6%

ALL OTHER

1%

UNK19%

DrugEstimated Encounte

rsMetformin 680,071

Levothyroxine 387,678

Lasix 363,407Lisinopril 360,204Vytorin 358,967

Cymbalta 324,692Nexium 318,056Lipitor 317,137

Percocet-5 295,044Benicar 288,628All Other 16,112,833

National Encounter Estimates, 2009Women with a BMI ≥ 40 Between 45-55 y.o.

Diagnosis

Estimated

Encounters

Hypertension 1,056,193Diabetes Type II 949,671

Obesity 325,396Backache 240,515

Routine Medical Exam 224,340Routine Gyn Exam 201,090Postsurgical States 198,707

Lumbago 191,458Myalgia and Myositis 179,426

Disc Degeneration 177,972

Race

Region

Top 10 Drugs Top 10 Diagnoses

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

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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

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Time on Market: Recommended TherapyPercent of Respondents Answering 4 or 5

(Recommend) New Combo Therapy

New Therapy

Est Surgery Proc

New Surg Proc 0%

50%

100%

Primary Care PhysiciansSurgeonsEndocrinologists(n=12)

(n=39)

(n=83)

Specialty

New Combo Therap

y

New Therap

y

Established

Surgical Procedur

e

New Surgical Procedure

PCP 31.3% 24.1% 39.5% 21.7%

Surgeons

13.5% 18.4% 28.9% 43.6%

Endo 58.3% 50.0% 16.7% 16.7%

PCP: surgery > RxComb > RxNMESurgeons: new surgery > established > RxEndo: RxCombo > RxNME > surgery

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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..

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Non-clinical: Recommended TherapyPercent of Respondents Answering 4 or 5

(Recommend)Animal Signal Concerning

Wait 5 YrsAnimal Signal Not Concerning

0%

20%

40%

60%

80%

100%

Primary Care Physicians

Surgeons

Endocrinology

(n=74)

(n=37)

(n=12)

Specialty

Animal Signal

Concerning

Wait 5 Years

Animal Signal Not

Concerning

PCP 31.1% 33.8% 21.6%

Surgeons 33.3% 34.3% 13.5%

Endo 25.0% 25.0% 72.7%

There is agreement between PCP/Surgeon on the need for caution re: animal signal; not so for endocrinologists

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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).

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Clinical Trial Subject Cohort: Recommended Therapy

Percent of Respondents Answering 4 or 5 Trial Subj Cohort Important

Lifestyle ChangeTrial Subj Cohort Not Important

0%

20%

40%

60%

80%

100%

Primary Care Physicians

Surgeons

Endocrinologists

(n=63)

(n=27)

(n=10)

SpecialtyTrial Subj

Cohort Important

About Lifestyle Change

Trial Subj Cohort

Not Important

PCP 44.4% 59.7% 24.2%

Surgeons 26.9% 48.1% 26.9%

Endo 60.0% 60.0% 40.0%

Endo> PCP > Surgeon consider trial subject cohort important

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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

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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

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Thank You

Carl N. Kraus, M.D.

ckraus@medscape.net