Lee Aase (@LeeAase)Mayo Clinic Center for Social MediaApril 26, 2014

#NACCDOPAN

Strategic Application of Digital Media in Oncology Marketing and Communications

When we were last together...

THE Book on Social Media in Health Care

• Essays from 30 thought leaders

• The “Why?” of social media in health care

• Net proceeds fund patient scholarships

• Available on Amazon and discount bulk orders on CreateSpace (with offer code Z4L7DBSN)

Agenda• What’s happened since April 2009• Making marketing and communications better

through social and digital platforms• Demonstrating bottom-line benefits

The revolutionary impact of consumer-grade video

Dramatically increased number of videos and depth of content

YouTube Playlists

YouTube Playlists

YouTube Playlists

A Case Study in Media Synergy

My Excellent Phillies Adventure

Social and Traditional Media Synergy• YouTube video leads to USA Today story• USA Today story leads to #wristpain Twitter chat

with explanatory videos and trainee list• Twitter chat leads to patient procedure and blog

post• Blog post leads to USA Today story

Twitter Chats Today• Social Media/Media Relations combo• Typically 3-4 chats per week with Mayo experts• Reach consumers/patients directly and cultivate

journalist relationship• #MayoUSAToday (circa 2009-2010)• #ABCDrBChat

TW 110: How to Effectively Participate in a Twitter Chat

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A 2009 Email from Dr. Noseworthy• Paraphrased version: I know we’re doing a lot in

social media, but have we considered whether a bigger investment is warranted?

• January 2010 meeting Dr. Noseworthy and Shirley Weis endorsed concept of Center for Social Media

• Planning team from across Mayo gathered• Announced MCCSM in July 2010

Mayo Clinic Center for Social Media• The Mayo Clinic Center for Social Media exists

to improve health globally by accelerating effective application of social media tools throughout Mayo Clinic and spurring broader and deeper engagement in social media by hospitals, medical professionals and patients.

• Our Mission: Lead the social media revolution in health care, contributing to health and well being for people everywhere.

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A Catalyst for Social Media

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Social Media Health Network• Membership group associated with Mayo Clinic

Center for Social Media

• For organizations wanting to use social media to promote health, fight disease and improve health care

• Much content available through free Guest account

• Dues based on organization revenues, and individual paid memberships also are available

Measuring the Benefits of Social Media:Reuben Mesa, M.D. and Myelofibrosis

Unique Myelofibrosis Patients

0

100

200

300

400

2008 2009 2010 2011 2012 2013

MCF MCA

Impact of Videos• The Data

• 3 Videos• 23:11 Total Running Time• 4,959 Total Views

• The Benefits• Time saving in office explanations• Elevating quality of patient conversations• Increased patient volumes• Enhanced professional stature among peers

Lee’s Social Media Measurement Maxim:

As I approaches 0, ROI approaches

∞

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Big Ideas• Measurement only matters in the context of

making or evaluating a decision• Measurement reduces uncertainty and the

risk of being wrong• A little measurement can give you a big

reduction in uncertainty

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One Quick Uncertainty-Reducing Method: The Rule of 5

• Random sample of 5 values• High and low valutes give you 93.75%

confidence interval (CI) of the median• In a normal distribution, median and mean

will be the same

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Case Study: “Massive” Exercise in Salt Lake City

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Research Exercise• Enter your weight in pounds. Feel free to round

down to the nearest 5.

• Enter the lower and upper bounds for your estimate of the average (mean) weight for everyone in the course.

• “I am 90 percent certain that the average weight of people in this room is between ____ and ____ pounds.”

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Review of Results• Smallest range guessed: 10 (150-160 and 165-175)• Largest range guessed 195 (100-295)• Percent of those including the mean: 83%• Average range of those including mean: 93.7• Average range of those not including mean: 35.0• Actual Mean for Population: 167.2

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n=5 n=8 n=11

155 100 100165 115 115175 155 135220 165 145250 175 155

200 165220 175250 180

200220250

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“Mathless” CIs for Small SamplesSample Size (n)

_th smallest

_th largest

Confidence

5 1st 93.75%

8 2nd 93.0%

11 3rd 93.5%

13 4th 90.8%

16 5th 92.3%

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n=5 n=8 n=11

155 100 100165 115 115175 155 135220 165 145250 175 155

200 165220 175250 180

200220250

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n=5 n=8 n=11

155 100 100165 115 115175 155 135220 165 145250 175 155

200 165220 175250 180

200220250

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Lessons

• If you have a lot of uncertainty, just a few measurements can tell you a lot

• The Mathless Method can get you a quick answer that is better than most expert estimates

• In this case, sampling produced better ranges• n=5 produced a better range than 49 of 87• n=11 produced a better range nearly 3X as

often as human guessing did (63 vs. 23)

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Unraveling the Fermi Decomposition

• Named after Nobel Prize winner Enrico Fermi• For a big unknown, break the problem into

components you can measure or more confidently estimate

• Classic question: How many piano tuners are in Chicago?

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Number of Piano Tuners = Population/people per household x percent of households w/tuned pianosx tunings per piano per year/(tunings per tuner per day x workdays per year)

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Develop Your 90% CI

• For each formula component, estimate the 90 percent confidence interval through

• Calibrated estimates of experts• Rules of thumb/historical performance• Surveys and sampling• Direct measures where practical

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Monte Carlo Simulation

• Run a large number of calculations (5,000 to 10,000) with randomly generated values for each variable, based on your 90% CI

• Expected outcome = value x probability

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Disclaimer:

All Numbers in the Following Example are Hypothetical!

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Example: Adding staffer for demand-generating videos

• Proposal is to hire an employee to shoot, edit and upload videos to YouTube and add annotations linking to appointment request page, along with a phone number

• Goal is to increase demand in areas of practice with favorable reimbursement

• Is this likely to generate demand that would pay for the new employee?

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Break it down like Fermi• Costs = Salary & Benefits + equipment +

software + travel• Annual Benefit =

• NOI per patient x• Number of New Patients

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Continuing the Decomposition

Annual Benefit = NOI/Patient x Patients/Video x Videos/Week x Weeks/Year

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Continuing the Decomposition

Annual Benefit = NOI/Patient x Patients/Video x Videos/Week x Weeks/Year

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Continuing the Decomposition

Annual Benefit = NOI/Patient x Patients/Video x Videos/Week x Weeks/Year

Annual Benefit = NOI/Patient x Patients/Viewx Views/Videox Videos/Week x Weeks/Year

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Continuing the Decomposition

Annual Benefit = NOI/Patient x Patients/Video x Videos/Week x Weeks/Year

Annual Benefit = NOI/Patient x Patients/Viewx Views/Videox Videos/Week x Weeks/Year

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Completing the Decomposition

Annual Benefit = NOI/Patient x Views/Videox Patients/View x Videos/Week x Weeks/Year

Annual Benefit = NOI/Patient x Views/Videox Clicks to Web Site/Viewx (Online Appt Reqs/View + Phone Req/View)x Patients/Appt Req x Videos/Weekx Weeks/Year

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Developing the 90% CI• How might you estimate

• Weeks per year worked by new employee?• Average videos produced per week?• Views per video?• Annotation clicks per view?• Appointment requests per annotation click?• Phone appointment requests related to videos?• Percent of requests likely to be fulfilled?• NOI per patient?

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Do the Monte Carlo Simulation• Apply the formula in 10,000 simulations with

random values from your 90% CI• Videos/week (8-12)• Weeks worked/year (48-50)• Views/Video (500-1500)• Annotation Clicks/Video View (.005-.02)• Online appointment requests/annotation click

(0.01-0.03)• Phone appointment requests/annotation click

(0.01-0.03)• Appointments scheduled/request (0.5-0.8)• NOI/Patient ($400-$800)

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Monte Carlo Simulation

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Monte Carlo Simulation

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Monte Carlo Simulation

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Monte Carlo Simulation

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• If it’s really that important, it’s something you can define. If it’s something you think exists at all, it’s something you’ve already observed somehow

• If it’s something important and something uncertain, you have a cost of being wrong and a chance of being wrong

• You can quantify your current uncertainty with calibrated estimates

Summary of Philosophy

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Summary of Philosophy• You can compute the value of additional

information by knowing the “threshold” of the measurement where it begins to make a difference compared to your existing uncertainty.

• Once you know what it is worth to measure something, you can put the measurement effort in context and decide on the effort it should take.

• Knowing just a few methods for random sampling, controlled experiments, Bayesian methods or even merely improving on the judgments of experts can lead to a significant reduction in uncertainty.

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Simulate Before AND After• Lack of CRM perfection isn’t insurmountable

barrier to demonstrating ROI• Get stakeholder/leadership agreement on CIs• Refine measurements and CIs based on

ongoing experience. Iterate!

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Other Measurement Applications

• Adding a blog version of a print newsletter• Better gauge of readership by adding

interaction• Estimate costs/benefits of reducing print

• Building seminar attendance through• Traditional methods (including advertising)• Facebook ads

Practical Example:Patient Education Collaboration Opportunities

• Videos covering FAQs

• Short, procedurally focused videos are ideal

• Huge potential savings - competing vs. non-production

• Crossover potential for demand generation

Calculating ROI• Cost of shooting and editing < $200

• Cost of storage: $0

• Cost of distribution: $0

• Value of time saved: $?,???• Develop 90% CIs for each variable• NG pts/year x minutes/pt x $/hr/60 x self-

serve %• Run a Monte Carlo simulation

• Increase in patient satisfaction: $?,???

• Other “marketing” benefits: $?

Applying Capabilities• Mayo Clinic Connect community

• Mayo Clinic News Network• Adding interaction and bonus features to

publications

• Research• Recruitment for clinical trials• Therapeutic applications

• Education• Continuing education promotion• Integration within courses

For Further Interaction:• Google Lee Aase or MCCSM

• @LeeAase on Twitter

• For Social Media Health Network information• http://network.socialmedia.mayoclinic.org/

mccsm/joining-the-network/

• Contact Mayo Clinic Center for Social Media • By email: socialmediacenter@mayo.edu • By phone: 507-538-1091