BY BRIA

N REID

GREG MATTHEW

S

YASH G

AD Ph.D

.

WITH

LUCAS G

ALAN

THE SOCIA

L

ONCOLO

GY

REPORT

A DIVISION OF W2O GROUP

2017

TABLE OF CONTENTS

INTRODUCTION 3

PART ONE: THE SIMILARITIES 4

GENDER 5

GEOGRAPHY 6

PART TWO: THE DIFFERENCES 7

AGE 8

INDUSTRY RELATIONSHIPS 9

JOURNAL PUBLICATIONS 10

AREAS OF FUTURE STUDY 12

CONCLUSION 13

DATA AND METHODS 15

REFERENCES 17

INTRODUCTION

When we talk about social oncology as part of The Social Oncology Project, we have often used social media use as a proxy for two divergent views.

On the one hand, we have sometimes assumed that public, online voices are a reflection of the silent majority of doctors, and that looking at the sub-population of physicians on Twitter can tell us something about medicine and physician sentiment more broadly. This is a hugely useful way to use social media: it becomes a focus group of hundreds, thousands or tens of thousands on any given topic. Analyses can provide quick answers and a window to what a large and sometimes-fractious group thinks, an effort that would have been impossible in the pre-digital age.

For instance, in The Social Oncology Project 2015, we charted physician social media activity around certain cancer types, noticed spikes during awareness months – and not just heavily promoted Breast Cancer Awareness Month – and have concluded that awareness months do an excellent job of focusing not only patient advocacy, but also physician attention and engagement.

But at the same time, we often infuse a sense that the online cohort is fundamentally different and represents a unique and forward-looking group of early adopters. Within that frame, we view the behavior of that online cohort - the MDigitalLife physician, if you will - as less a snapshot of modern medicine than a predictor of future trends.

Last year, this effort focused on “hashtag communities,” online gathering places centered around specific hashtags, and concluded that there was a real trend at work that had begun to create real change at the cutting edge but which still reflected far, far fewer conversations than some of the broader analyses that have been done as a part of The Social Oncology Project.

This year, our goal was to look at the correlations – or lack thereof – between the characteristics of oncologists with Twitter handles and those who are not in the public square. What we found was, predictably, not black and white. In some areas, online oncologists look very much like their offline peers. In others, there are significantly different behaviors. And there are still other areas in which it remains difficult to tell whether there are real differences.

This year’s report will examine the same/different dichotomy. We will first explore sameness – the ways in which the online population reflects the offline population – and then highlight the differences. Finally, we will assess areas where additional analyses may be fruitful. After all, it’s not too early to think about next year’s edition of The Social Oncology Project.

At the end this report, we detail our methodology and caveats in more detail, but the basics bear acknowledgement up front. The analyses to come are pulled from our proprietary database of doctors whose Twitter accounts have been validated against their National Provider ID. This allows us to connect public social media posts with publicly available government data about physicians. We cannot track private information or anonymous accounts and make no effort to do so. We also have access to the same data on physicians who do not have a social media profile, which provides the “control group,” so to speak, for the analyses to follow.

What follows are a number of hypothesis-generating comparisons between oncologists who have social profiles and those who do not. These groups, as we will show, have many similarities and some meaningful differences. However, the nature of our datasets means that we can, at best, show only correlation, and there are no doubt many confounding factors that complicate analyses of this manner. We look forward to continued conversations and deeper research to further flesh out the characteristics of online oncologists.

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Since the dawn of the Internet, there have been certain stereotypes about the online community: that it is young, that it is male, that it is clustered around urban technology hubs. And while that profile may have been accurate at one point, technology has become sufficiently ubiquitous that the Venn diagram of Americans and those online is nearly perfectly overlapping. According to a Pew report this year, broadband penetration rocketed from 1% in 2000 to 73% today, and an even greater number of Americans own a smartphone1. The myth of the geek may soon become as much a part of cultural history as Buffy the Vampire Slayer, Limp Bizkit and other early-2000s phenomena.

Defining the ways that online oncologists look like their offline peers becomes important in understanding what behaviors seen online can be reasonably extrapolated offline, and which ones cannot. The analytics performed for this report show at least two areas where oncologists look the same, no matter their social footprint.

1Internet/Broadband Fact Sheet, Pew Research Center

PART ONE: THE SIMILARITIES

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Oncology, according to our data, is still a male-dominated field; more than two of every three oncologists – 69% – are male. That statistic holds steady in the offline population, too. Among oncologists without a public social profile, 69% are men.

Looking at social oncology provides very much the same snapshot: 71% of tweeting oncologists are men, which is not statistically different from the pool of non-tweeting physicians.

The fact that the gender breakdown of Twitter use reflects the general population of oncologists is not particularly surprising. The Pew Research Center has documented that certain social networks skew female (including Facebook, by a little, and Pinterest, by a lot) and some skew male (LinkedIn), but that Twitter has traditionally had a nearly even female/male split .

This is a metric worth examining, however: as the gender makeup of the oncology community moves toward parity (women represented 10% of their class in the 1960s; 42% in the 2000s), and as younger doctors adopt social media at a higher rate than their older peers (see below), it may be that the demographics in this area will shift as well.

Online OncologistsO�ine Oncologists

69%Male

31%Female

71%Male

29%Female

NO GENDER GAPFemale oncologists are almost exactly as likely as their male counterparts to be on social media.

Source: NPPES Registry; MDigitalLife Online Health Ecosystem N = Based on 22,624 US Oncologists; 1,522 of whom are on social media

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GENDER

Academics who have analyzed the Twitter user base have concluded that the social network tends to be over-represented in urban counties. At the same time, social media use has been positioned as a potential panacea for physicians with rural practices, allowing them to connect with patients and colleagues for whom in-person interactions would be more difficult.

Amidst these seemingly contradictory dynamics, we sought to determine whether there was evidence to support one or the other narrative. Are Twitter-using doctors generally from the technology hubs of coastal, urban areas? Or has it become a vital tool for the rural oncologist seeking to extend in cyberspace a network that is hard to form in more sparsely populated areas?

We found that neither was overwhelmingly true – or false. Twitter penetration remains low. Urban oncologists were slightly more likely to use Twitter, just over 7% of the urban sample had public profiles, than their rural counterparts, of whom 5% were on the social network.

And while that difference is statistically meaningful, it’s not clear that it suggests two radically different populations.

Minnesota Wisconsin Utah13.4% Online 12.9% Online 11.4% Online

HOW WILL YOU KEEP THEM DOWN ON THE FARM?79% of the “o�ine” oncologists live in close proximity to a major urban center. Slightly more – 85% - of online oncologists do so.

Source: CMS Physican Compare Database; MDigitalLife Online Health Ecosystem database N = Based on 22,624 US Oncologists; 1,522 of whom are on social media

Percentage of Online Oncologists Compared to Overall Oncologists in the State

Olmsted32.1% Online

Milwaukee19.7% Online

Salt Lake14.6% Online

O�ine Oncologists Online Oncologists

Note: The more intense the color, the higher density the population.22,624 1,522MAX MAX

2Social Media Fact Sheet, Pew Research Center

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GEOGRAPHY

Online oncologists not only show us more about how things are today – they show us something valuable about the future.

The Future = Teaching and learning today; better health tomorrow. We know from years of study that one of the main reasons physicians go online in the first place is to propagate good science and information (and to quell the bad). Oncologists have been particularly open to getting their hands dirty online – 20% of the participation in online cancer hashtag communities comes from physicians.3 That kind of concern for constantly improving health literacy – for themselves and for others with whom they interact – suggests a kind of thinking that is in itself future-shaping.

The Future = Willingness to trade tradition for innovation. Online doctors are willing to bend (if not break) established norms. In the past, medicine has been defined by what Dr. Bryan Vartabedian calls a “culture of permission.” Yet during a single week in May 2017, U.S. physicians posted over 15,000 times on American health reform, with more than 90% of them expressing concern about the passage of the American Health Care Act by the U.S. House of Representatives.4 They’re also willing to forge non-traditional relationships. As noted above, online physicians regularly engage with (and even learn from) patients – not a “norm” of the archetype patriarchal physician-figure. Online doctors are also more willing to engage with industry – in the form not only of hospitals, but also with digital health companies, medical technology companies and pharmaceutical manufacturers in order to ensure that they always have access to the best and most valuable data.

The Future = Youth. Thoughts of the future suggest youth. Indeed, conventional wisdom suggests that oncologists who maintain an active online presence are “digital natives.” Certainly, the qualities of flexibility and openness to new ways of being and doing are associated far more readily with youth than with age and experience. Who hasn’t heard the platitude that older doctors are “set in their ways?” While it’s true that online physicians skew (relatively) young, the true impact of age on a physician’s likelihood to maintain an active online presence is surprisingly complex.

The Future = New ways to define influence and drive change. In the minds of many, influence in medicine hasn’t changed for years. Credibility is established by doing leading research, publishing in the most important journals, and handling the toughest cases. The truth is, we believe that all those things are still true. However, they’re no longer the only criteria that define patterns of influence among physicians. Online influence is a long-established fact, but we’ve now learned that the Key Opinion Leader of yesterday doesn’t look as different from the Key Online Influencer of tomorrow as we may have assumed.

3Disease-specific hashtags for online communication about cancer care, by Katz, Matthew S. et al

4Online Physicians Overwhelmingly Oppose Health Reform Bill, by Matthews Greg

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PART TWO: THE DIFFERENCES

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One of the advantages to leveraging the U.S. NPPES database as the spine of our MDigitalLife data set is that it gives us not only interesting metadata (we’ve already explored the comparisons between online and offline physicians relative to gender and location using a comprehensive data set) but it also allows us to link to other valuable data sources. We regularly use it to map things like referral and prescribing data to individual physicians and, through CMS’ Physician Compare data, we can also access a physician’s medical school and graduation year. Like all data generated by massive public sources, it has gaps and flaws – but we were still able to identify nearly 16,000 U.S. oncologists with a noted medical school graduation year.

While there are graduation years as far back as 1947 and as recent as 2013 in the data set, 95% of the oncologists in the data set graduated from medical school between 1970 and 2011.

Based on an average age of 26 at the time of medical school graduation, that leaves us with a group of doctors of whom 95% range in age from 32 to 73.

If you guessed that younger doctors are more likely to be active online than their older peers, you’re right. The average graduation year for offline doctors is 1989 – the average for online doctors is 1995. The percentage of a medical school class maintaining an active online presence ranges from 3% for the classes in the 1970s to 6% for the 1980s classes, 8% for the 1990s, and 18% for the 2000s (the last decade with enough critical mass of data in Physician Compare to be reliable). But before you congratulate yourself for being right about social media being a fad for the kids, consider this: 39% of the online oncologists in our database are over 50 (graduated from medical school before 1994) and 76% are over 40.

Online Oncologists

O�ine Oncologists

Overlap

20151950

4.5% of oncologists in their 60s are on Twitter

18% of oncologists in their30s are on Twitter

GRADUATION YEAR

54.1

48.0

OLDER YOUNGER

MEDIAN AGE

MEDIAN AGE

AGE

FOUNTAIN OF YOUTH Social media usage is increasing rapidly – for both younger and older oncologists.

Source: CMS Physican Compare Database; MDigitalLife Online Health Ecosystem database N = 15,855 US Oncologists w Med Schl Grad Yr; 1,349 of whom are on social media

AGE

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In many ways, the relationships between physicians and industry has deteriorated over the years. However, there is no question that access to the best evidence-based knowledge is critical for physicians – and in many cases that evidence-based knowledge comes from research that is associated with a healthcare company. And healthcare companies recognize that, in order to continue to bring innovative and valuable medicines and technology to the market, they must rely on the knowledge and experience of practicing physicians to inform their work. To avoid conflicts of interest (or the perception thereof) related to physicians’ relationships with healthcare companies, the U.S. Congress enacted the Physician Payments Sunshine Act in 2010 to transparently document any financial connections between physicians and healthcare companies.

These relationships have become “normal” enough since their inception 7 years ago that well more than half of U.S. oncologists (58%) have accepted a payment of some kind from industry (75% of U.S. oncologists have received total payments of less than $560 over the life of the program). That percentage varies only slightly for the online physician (62% to 58%). However, there is a significant difference in the amount of Sunshine Act payments made to online physicians.

For those oncologists who have acknowledged a financial relationship with industry, the average online physician receives payments nearly three times higher than those of offline oncologists ($14,133 vs. $5,558). At the 75th percentile marker, that payment is more than five times higher ($10,508 vs. $1,746).

Average sunshine act payment for online doctors who have accepted payments = $14,133. Average payment for their o�ine peers = $5,558.

ONLINE ONCOLOGISTS THRIVE IN THE SUNSHINEOnline oncologists are just as likely to have a paid relationship with industry, but are paid nearly 3x more on average.

Source: CMS Open Payments Database; MDigitalLife Online Health Ecosystem database N = Based on 22,624 US Oncologists; 1,522 of whom are on social media

INDUSTRY RELATIONSHIPS

5On the impossibility of being expert, by Fraser, Alan G and Dunstan, Frank D

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The research and publication of patient healthcare represents the lifeblood of medical advancement. As physicians advance through their careers, attaining ever-higher levels of experience and achievement, an important part of the mechanism for sharing that knowledge with their peers and especially junior doctors is to conduct rigorous scientific research and to publish it in peer-reviewed journals.

The British Medical Journal estimated in 2010 that, “There are now 25,400 journals in science, technology and medicine, and their number is increasing by 3.5% a year.” However, far fewer than that number are truly relevant to today’s oncologist. In a time when the quantity of research is expanding so rapidly, quality has never been more important. For this study, we focused on two journals published by the American Society of Clinical Oncology: the Journal of Oncology Practice and the Journal of Clinical Oncology.

N = Based on 22,624 US Oncologists; 1,522 of whom are on social mediaSource: PubMed; MDigitalLife Online Health Ecosystem database

None

Number of Publications(at least)

1 - 5

6 - 10

11 - 15

16 - 20

21 - 25

26 - 30

31 - 35

36 - 40

41 - 45

46 - 50

61 - 65

71 - 75

20.28%

3.33%

1.34%

0.64%

0.37%

0.18%

0.11%

0.08%

0.05%

0.02%

0.01%

0.01%

54.53%79.72%

45.47%

12.61%

6.37%

4.01%

2.69%

1.77%

1.38%

0.92%

0.39%

0.39%

0.20%

0.07%

20% 45%

O�ine Oncologists Online Oncologists

of online Oncologists publishedat least 1 article

of o�ine Oncologists publishedat least 1 article

45% of oncologists on social media have published in the Clinical Journal of Oncology or the Journal of Oncology Practice in the last 10 years; 20% of their o�ine peers have done so

ONLINE ONCOLOGISTS ARE 2X MORE LIKELY THAN OFFLINE PEERS TO PUBLISH IN ASCO JOURNALS

JOURNAL PUBLICATIONS

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JOURNAL PUBLICATIONS (CONT’D)

Those two publications are so central to the practice of oncology in the U.S. that 22% of U.S. oncologists have published in at least one of those journals in the last 10 years. However, oncologists who maintain an active online presence are more than twice as likely to have done so (45%) than those who do not (20%). That distinction is at least as apparent when considering that, of those doctors who have published in one of those two journals, online doctors have published an average of 5.8 articles, while the offline doctors have published 3.5 articles.

Online oncologists are already considered bellwethers in terms of their focus on teaching and learning, the deepening of their connectivity with patients, and their willingness to challenge the status quo. Now, too, online physicians are leading the way in an area that conventional wisdom reserves for the “old guard” Key Opinion Leaders – publication in leading medical journals.

When one considers the impact that online physicians can have on their peers and the public through their own highly-developed channels and networks, combined with the amplification they receive from the media (we are tracking over 200 top journalists who follow at least 50 physicians’ twitter accounts), combined with the fact that they can now be shown to have the credibility of publication in prestigious peer-reviewed journals, online physicians truly do point the way to the future.

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The analyses discussed above only scratch the surface of what can be done with social media data and publicly available information about physician behavior, and future research is warranted to more fully define how online oncologists do – or do not – reflect the view of the specialty as a whole.

As part of this effort, we ran similar analyses comparing online and offline doctors on a large dataset that tracks physician referrals within Medicare. The hypothesis we were investigating was a simple one: was connection online linked to referrals, the most basic and important kind of connection offline?

The results were inconsistent. Offline physicians seemed to have larger referral networks, though the numbers jumped around from year to year. Referral data is one place where confounding data – particularly geography and age – must be carefully considered to ensure that the snapshot generated is as accurate as possible. Still, such research could provide an important understanding of how the online and offline worlds collide.

Another area in which additional work may be fruitful is assessing whether online oncologists have different prescribing patterns than their peers who are not on public social media. The MDigitalLife Health Ecosystem Database can be tied into government data that links physicians with Medicare Part D prescribing behavior, which allows a comparison between the volume and type of prescribing of these two large groups of physicians.

Deepening our understanding of medication prescribing may reveal important truths about how information flows through offline and online communities and help define new approaches to ensure that the right patients receive the right medications at the right time.

AREAS OF FUTURE STUDY

At the time of our analysis, we were tracking exactly 1,522 oncologists with public social media profiles. While not a small group, that group of social-savvy oncologists still represents a fraction of the overall oncology community, which tops 22,000, according to government data.

The math works out to about 7% of oncologists with an active presence on social media, a minority to be sure. Yet much of the communication around medicine is moving toward online forums. One of the first acts that the new FDA commissioner, Scott Gottlieb, performed was launching a new Twitter account. Every major journal and every major healthcare company is seeking out that 7%.

Even ASCO, in promotional materials for its 2017 Annual Meeting, adopted the hashtagged shorthand for the meeting—#ASCO17—throughout the document. This was no coincidence. Over and over, the innovative leaps in how the community communicates has come from the online minority.

And as the analysis on publication patterns shows, the sliver of social oncologists is disproportionally represented in the specialties’ publications.

That outsized influence carries with it both benefits and hazards. The hazards are clear enough: while this is a group that in some ways mirrors the larger community – in terms of its gender makeup and broad measures of geographic diversity – it is without question a group that has its own well-defined demographics and perhaps a fundamentally different view of the world than the online community. Consequently, the views of online oncologists cannot be used as a proxy for their colleagues; when an analysis shows, for instance, that nine in 10 oppose a specific piece of legislation, that conclusion can only be applied to the online cohort, no further.

But the benefit of having a unique group on the technological cutting edge brings great advantages, too, especially to those trying to handicap where the future of medicine lies. Past versions of The Social Oncology Project have shown that physicians on social media are increasingly hubs in an online ecosystem that stretches to patients, advocates, industry and beyond. Given that degree of connection, it is not at all surprising that online oncologists appear more closely linked to pharmaceutical companies. They are more closely linked to everyone.

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CONCLUSION

The reality of social media use by physicians is that it is a dynamic and growing phenomenon, making these analyses useful and interesting, but soon to be dated. If the current trends continue and more and more doctors begin to engage online, and as new tools emerge to allow for that engagement, we may see the online and offline communities converge. Alternatively, we could see continued bifurcation if the number of social oncologists grows only modestly, leaving a gap between a group using technology in increasingly sophisticated ways and a more traditional majority.

Regardless, we will continue to keep tabs on social media activity online, because while it may not reveal the heart of medicine, there is no doubt that it gives powerful hints about the future of patient care.

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CONCLUSION (CONT’D)

The MDigitalLife Health Ecosystem Database catalogs online behavior, showing the digital footprints (social accounts, blogs, websites, etc.) of more than 730,000 stakeholders (including doctors, patients, advocacy organizations, reporters and media outlets among many others) in 157 countries. This database is the first to link U.S. physicians’ online content to their national physician identifier (NPI), correlating prescribing data, referral patterns, medical school information and geographic location, among other factors, to physicians’ online presence in order to gain insights into the networks, relationships and social activities of online physicians. Potential digital properties for all stakeholders in the health ecosystem are obtained through manual and automated mechanisms, and human validated to ensure accuracy (http://mdigitallife.com/).

The current study utilizes all physicians in the NPI database whose specialty is classified under “Oncologists” by Medicare: Surgical Oncology, Radiation Oncology, Pediatric Hematology-Oncology, Medical Oncology, Hematology and Oncology, Hematology and Gynecologic Oncology. While there are over 27,000 oncologists in the NPI database, not all of them had complete data for this analysis.

Each NPI number provides a unique key into the databases from the Centers for Medicare & Medicaid Services which were utilized in this study. The Physician Compare dataset (data.medicare.gov/data/physician-compare) provides medical school graduation year and location, demographic information, hospital and practice affiliations, and basic quality of care metrics. Referrals for 2013-2015 (measured by number of encounters across physicians over certain time intervals) were obtained from publicly available datasets (https://questions.cms.gov/faq.php?faqId=7977), with the 30-day interval data used in this study. Open Payment for 2015 (https://www.cms.gov/OpenPayments/Explore-the-Data/Dataset-Downloads.html) show industry payments to physicians.

To examine the proximity of oncologists to urban centers (as defined by U.S. Census https://www.census.gov/geo/maps-data/data/ua_rel_download.html) we queried the practice city and state within the “2010 Urban Area to Place Relationship File” and gave a classification of urban if the city did not have an entry of “Not in a 2010 urban area.”

To see what publications oncologists have made in two primary ASCO journals, we searched PubMed (https://www.ncbi.nlm.nih.gov/pubmed) for all publications in the last 10 years from the Journal of Oncology Practice and the Journal of Clinical Oncology. Each author who authored or coauthored one of these publications was then matched to the list of oncologists from the NPI database.

For each observed metric, two datasets were constructed for oncologists who did or did not have a social presence in the MDigitalLife Health Ecosystem Database, and who also have a value for the observed metric. In the case of numerical data, a one-way ANOVA was performed to examine statistical significance of any differences. In the case of categorical data (such as gender) or binary data (such as proximity to urban areas or receipt of industry payments), a T-test was performed to ascertain statistical significance.

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DATA AND METHODS

Founded and led by CEO Jim Weiss in 2001, W2O Group is an independent, fast-growing network of integrated marketing and communications firms focused on digital business solutions to drive insight-driven change and growth for the world’s leading brands and organizations. W2O Group firms employ proprietary analytics models, methodologies and approaches that uncover key insights leading to precise communications and marketing strategies and engagement to deliver business results. W2O Group’s network includes WCG, Twist Mktg, Pure, Marketeching and Sentient, with a growing footprint of offices in the United States and Europe. For more information, please visit www.w2ogroup.com.

ABOUT W2O GROUP

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[1] “Internet/Broadband Fact Sheet”, Pew Research Center: Internet, Science & Tech, 2017. [Online]. Available: http://www.pewinternet.org/fact-sheet/internet-broadband/.

[2] A. Mislove, S. Lehman, Y. Ahn, J. Onnela and J. Rosenquist, “Understanding the Demographics of Twitter Users”, ICWSM, 2011. [Online]. Available: http://www.ccs.neu.edu/home/amislove/publications/Twitter-ICWSM.pdf.

[3] “Social Media Fact Sheet”, Pew Research Center: Internet, Science & Tech, 2017. [Online]. Available: http://www.pewinternet.org/fact-sheet/social-media/.

[4] B. Vartabedian, “Doctors and the Culture of Permission”, 33 Charts, 2013. [Online]. Available: http://33charts.com/2013/07/doctors-culture-of-permission.html.

[5] M. Katz, A. Utengen, P. Anderson, M. Thompson, D. Attai, C. Johnston and D. Dizon, “Disease-Specific Hashtags for Online Communication About Cancer Care”, JAMA Oncology, vol. 2, no. 3, p. 392, 2016.

[6] G. Matthews, “Online Physicians Overwhelmingly Oppose Health Reform Bill”, MDigitalLife, 2017. [Online]. Available: http://mdigitallife.com/online-physicians-overwhelmingly-oppose-health-reform-bill/.

[7] “National Provider Identifier”, En.wikipedia.org, 2017. [Online]. Available: https://en.wikipedia.org/wiki/National_Provider_Identifier.

[8] “Physician Compare Initiative - Centers for Medicare & Medicaid Services”, Cms.gov, 2017. [Online]. Available: https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/physician-compare-initiative/.

[9] “Physician Payments Sunshine Act”, En.wikipedia.org, 2017. [Online]. Available: https://en.wikipedia.org/wiki/Physician_Payments_Sunshine_Act.

10] A. Fraser and F. Dunstan, “On the impossibility of being expert”, BMJ, vol. 341, no. 141, pp. c6815-c6815, 2010.

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REFERENCES

2017