Beyond ROI: Measuring Digital Health Content's Full Economic Benefits

Ju$tifying th€ Digita£ Health

Content InvestmentWhy It Matters | How to Do It

Ju$tifying th€ Digita£ Health Content Investment | Enspektos, LLC | April 2012Page 2

Use Statement and Acknowledgment

Use Statement

Enspektos, LLC is licensing this content under the Creative Commons License, Attribution-ShareAlike 3.0(http://creativecommons.org/licenses/by-sa/3.0). Please feel free to use material in this ebook in blogs,podcasts, presentations, and other content. You may also e-mail it to your colleagues and othersyou think will benefit from it.

Acknowledgment

We would like to thank Jane Sarasohn-Kahn of THINK-Health for her invaluable assistance in helping us to refine our work on quantifying the economic benefits of behaviors activated or sustained by digital health content. Information about THINK-Health is below.

About THINK-Health

THINK-Health is a strategic health consultancy founded in 1992. Focusing at the nexus of health care and technology, the firm's toolkit includes environmental analysis, scenario, strategic and business planning, forecasting, and health policy analysis.

THINK-Health assists every segment of the health care industry, including technology and medical device companies, educational institutions, pharmaceutical manufacturers and distributors, health care providers, payers and plans, consumer products companies, non-profits and financial services firms.

Learn more about THINK-Health at www.healthpopuli.com.

http://creativecommons.org/licenses/by/3.0




http://www.healthpopuli.com

http://www.healthpopuli.com


Just What Is Digital Health Content?

In this ebook, we'll spend a lot of time talking about digital health content so here's a brief definition.

Digital Health Content: Information about health, medicine or wellness distributed and consumed via digital technologies, such as the Internet and social and mobile media. This includes sites like WebMD, Facebook, Twitter, mobile apps and more.


The Bottom Line: Health Marketers and Communicators Must Justify Investments in Digital Health Content In 2005, Harris Interactive found that 58% of online adults reported going online "sometimes or often" to find health or medical information. (1) By 2011, 73% of online adults were frequently turning to Dr. Web for advice, content and support. (Part of this increase may be attributable to cost-shifting from payers to consumers as they seek to reduce medical costs.)

As the Internet has increased in importance for patients, medical providers, caregivers and others, the health industry has taken notice — and action. For example, government agencies like the U.S. Food and Drug Administration (FDA) and the U.S. Department of Health and Human Services are increasingly leveraging online and social media technologies. Government has been joined by hospitals, pharmaceutical companies and others in the private sector.

However, many health organizations have hesitated to aggressively use these technologies. One reason is regulatory uncertainty. Pharmaceutical companies have not received clear guidance from the FDA on how to employ social media in a compliant fashion. Hospitals and managed care organizations have concerns about violating HIPAA regulations.

Another contributing factor is a lack of clarity about whether investing in digital health content is worth the effort. The health industry is not alone in this regard. For example, according to a January 2012 survey produced by Wildfire, most marketers lack a standard metric for social media success. (2)

Moreover, many are not tying social media activities to standard measures of return on investment (ROI), such as increased sales, revenues and profits.

The public sector's enthusiasm has also been tempered because of uncertainty about whether and how digital content activates changes in health behavior.

For digital health evangelists, this caution has been frustrating. Many fear the industry will fall further behind as patients and other stakeholders embrace these technologies.

Convincing the industry to act will require demonstrating digital health content investments are economically justifiable. Assertions that the health industry must get involved because "everyone's doing it" are unpersuasive.

What Are the Economic Benefits of Digital Health Content?


Here's the bottom line: The health industry won't move forward unless we prove producing, curating and distributing digital health content is worth the effort. This is equally true for the public and private sectors.

Our Goal

We developed this ebook to provide marketers and communicators with a simple and flexible method for justifying digital health content investments.

Our suggested approach is behavior-centric. Unlike other industries, health-related marketing and communications activities are not solely designed to drive revenue and profits. Instead, a major objective is to change or sustain positive health behaviors so people can live long, active lives. This is not just about doing the right thing. Activating behavior change can have significant economic benefits.

We believe quantifying the economic impact of digital health content investments on behavior can help in these ways:

• Ensure marketing communications efforts are evaluated based on their overall economic benefits — not just on organizational profitability

• Encourage communications and marketing professionals to think more strategically about their digital health content initiatives

• Drive widespread adoption of digital technologies within the health industry

Our approach to justifying investments in digital health content is behavior-centric. Health marketing communications initiatives are not just about increasing revenue. Encouraging people to begin or sustain behaviors that lead to long, active lives is vital.

This is not just a "feel good" perspective. Activating behavior change has many economic benefits for health organizations and society.

Health is different. Existing metrics undervalue digital health content. Because of this, we've developed a new one.

In this ebook, we will do the following:

• Illustrate why focusing on behavior change in digital health is important

• Address whether digital health content can change behavior

• Discuss the important but misunderstood art of ROI measurement

• Outline why calculating ROI is not enough in health• Introduce a new method for quantifying the

economic impact of digital health content on behavior

The Bottom Line: Health Marketers and Communicators Must Justify Investments in Digital Health Content


A Single CDC Blog Post Captured the World's Attention, but Did It Change Behavior? Just prior to the 2011 hurricane season, the Office of Public Health Preparedness and Response (OPHPR) published a somewhat tounge-in-cheek blog post focusing on the importance of preparing for a Zombie Apocalypse. (3) The post was designed to raise awareness about the importance of being prepared for disasters.

CDC was unprepared for the massive reaction the post received. Soon after a tweet announcing it was published to Twitter, the agency's website was inundated with visits. Unprepared for the traffic, the CDC's website crashed for a brief period.

Although the public's response to the post was unanticipated, its creation was well planned. According to OPHPR's Margaret Silver:

"CDC’s Joint Information Center [JIC] was actively monitoring social media to track conversation about the [2011 Japan Earthquake] and provide accurate information where appropriate. JIC noticed that people were responding to questions about what disasters they would prepare for with 'zombies.'

In our planning sessions about how how to get people thinking about preparedness as hurricane season approached, we talked about the possibility of doing something around zombies." (4)

After OPHPR's director, Rear Admiral Ali S. Khan, signed off on the idea, the famous post went live.

Figure 1.Did OPHPR's Post Impact Preparedness Behaviors?

Source: Enspektos, LLC, © 2012


A Single CDC Blog Post Captured the World's Attention, but Did It Change Behavior?

Daigle's query highlights a question sometimes asked before, during and after digital health content initiatives. Web and social media have the potential to reach billions of people. But does reach translate into changed hearts and minds?

In the case of the Zombie Apocalypse post, convincing more people to prepare for hurricanes could have had a significant economic and human impact. A few months after the post was published, the Eastern U.S. was pounded by Irene, one of the worst tropical storms on record. Irene was expected to do more damage to the coast, but hit inland areas such as upstate New York and Vermont hard.

Many people in these regions were unprepared for the storm's ferocity. However, because of CDC's Zombie Apocalypse post, did some in these areas prepare? If so, what would have been the economic benefits of these preparedness activities? It is likely they would have been significant.

The Zombie Apocalypse story illustrates why it is so important we begin to routinely measure the behavioral impact of digital health content initiatives. If we don't, we'll never know the economic value generated by a single, massively popular blog post.

Until now we have assumed digital health content can play a role in behavior change. Below we'll address whether this is truly the case.

Overall, OPHPR was pleased by the success of the blog post. For a modest $87 investment (plus staff time), it generated tremendous awareness — especially via sites like Twitter (Figure 2). This demonstrates the power of social media to quickly spread information globally and generate a massive response.

However, OPHPR wanted to know more. Shortly after the post appeared, the agency's Dave Daigle remarked: "Measuring hits and views is great, but did people make a plan, did we really affect behavior?" (Figure 1)

Figure 2.OPHPR Achieved Its Goal of Generating Awareness



Can Digital Health Content Change Behavior?

Convincing people to stop long-held unhealthy behaviors such as smoking, poor eating and inactivity is incredibly difficult. Given this, it makes sense to ask whether content encountered online or in social media can truly get people to change.

Over the past few years, the public relations firm Edelman has been exploring this question via its global Health Barometer. (5) In the 2011 edition of the study, Edelman conducted an analysis of data it collected among people reporting they engage in negative health activities (such as eating poorly). When asked which factors would motivate them to change behaviors, respondents highly ranked the following:

• Knowing their long-term health would improve• Changes in physical appearance • Reading or hearing about benefits in the news • Joining support networks • Using supportive tools and technologies

The results of this study suggest a combination of factors can motivate people to change behavior. Social influences such as support groups clearly play a role. However, delivering health information digitally via the news or informational articles may also have an influence on behavior.

Knowing digital health content has the potential to change behavior is only the first step. Understanding how is the next.

Evidence suggests digital health content can activate behavior change.

According to the 2011 Edelman Health Barometer study, respondents said they would be motivated to change negative health behaviors because of the following:

• Reading or hearing about benefits [of behavior change] in the news

• Using tools and technologies • Joining a support network

BJ Fogg, director of Stanford University's Persuasive Tech Lab, is perhaps the world's foremost expert on how machines such as computers and mobile devices influence human behavior.

In 2003, Fogg's book, Persuasive Technology: Using Computers to Change What We Think and Do, was published. In the book, Fogg described a new concept he coined in 1996 called "captology." He defined captology as a focus "on the design, research, and analysis of interactive computing products created for the purpose of changing people's attitudes or behaviors. [Captology] describes the area where technology and persuasion overlap." (6)

Since the book's publication, Fogg has continued to refine the captology concept in a range of ways.



In 2009, Fogg introduced the Fogg Behavior Model in order to further describe how persuasive technologies change behavior (Figure 3). In the model, Fogg suggests behavior is a "product of three factors: motivation, ability, and triggers." (7) In order for behavior change to happen (or be sustained), all three factors must be present.

In brief:

• Motivation refers to willingness to engage in the behavior; motivation can be manipulated

• Ability is whether someone can actually perform the behavior; perceived ability can be changed

• Triggers are reminders or cues to engage in the behavior, such as text messages or on-screen alerts

Digital health content can support behavior change by delivering information triggers that motivate and increase perceived ability at the right time (Figure 4). Fogg has suggested the following best ways to activate behavior change:

• Place "hot triggers" in the path of motivated people, i.e., starting with those who want to change first (8)

• Reduce perceived difficulty level by making a task easier to complete or suggesting ways behavior change can be simple to achieve (8)

Figure 3.The Fogg Behavior Model

What are the types of behavior digital health content can influence? We answer this question below.


Can Digital Health Content Change Behavior? Figure 4.

How Digital Health Content Supports Behavior Change




On the next page, we outline a framework called the Health Behavior Levels Matrix (Figure 5). It is designed to outline the types of behavior those producing digital health content can activate or sustain. Behaviors indirectly and directly related to health are included in the matrix because they are activated in the context of this topic. The Matrix describes four levels of behavior:

• Level I: Engagement or activity behaviors commonly associated with consumption of online health content. These can include watching videos or sharing a Twitter post.

• Level II: Purchase or donation behaviors activated by online health content, including decisions to seek or prescribe medication or donate to a cause.

• Level III: Short-term health behaviors which do not require a long-term commitment such as getting screened for heart disease or being vaccinated.

• Level IV: Long-term health behaviors which require a significant commitment such as taking medication for life or maintaining an exercise program.

The Health Behavior Levels Matrix can be useful for health marketing and communications professionals working on online initiatives.

They can use the Matrix to determine how difficult behavior change will be to achieve. (Higher level behaviors are harder to activate.) They can also use it to plan how best to evaluate digital health content initiatives.

In the next section of this ebook, we outline a method for justifying digital health content investments. As we will discover, in the field of health, using ROI as the sole method of evaluation is often inappropriate.

The Health Behavior Levels Matrix is designed to help those developing digital health initiatives to:

• Understand the types of behavior they seek to influence

• Use the appropriate levels of measurement for their activities

• Determine how difficult it will be to activate or sustain behavior change


Can Digital Health Content Change Behavior? Figure 5.

The Health Behavior Levels Matrix



ROI: Important, but Often Misunderstood and Misapplied The debate over return on investment (ROI) has been one of the most heated in the digital world. One major reason for the argument is that ROI is misunderstood. According to a 2012 survey of corporate marketing decision makers produced by the Columbia School of Business Center on Global Brand Leadership: (9)

• 82% of respondents did not realize "ROI consists of both financial return and spending"

• 37% did not define ROI as a measure of financial outcomes

• 31% believe determining ROI begins and ends with measuring audience reach

It is important to understand that ROI is purely a financial metric. It is used to determine if an investment (such as a social media campaign) results in returns (profits or donations). As Columbia University found, many people substitute easier-to-calculate metrics such as online awareness (clicks) and engagement (Facebook Likes, retweets) for ROI. These metrics are useful, but unless they are linked to financial return, they are not relevant to the ROI conversation. To clear up confusion about ROI, we have provided a guide below on how to calculate the metric(Figure 7).

Another part of the debate centers on whether it is appropriate to evaluate digital and social media using ROI. Revenues or donations are the lifeblood of an organization. Given this, they have no choice but to determine if these tools yield positive financial returns.

Return on Investment is purely a financial metric. It measures whether an investment (such as using financial and human resources to produce social media content) results in a return (profits or donations) to an organization.

Many people substitute measures such as increased awareness (visits, advertising equivalency value) or engagement (Web traffic, Facebook Likes, retweets) for ROI. This is not appropriate.

These non-financial metrics can be useful. However, quantifying the impact of awareness and engagement on profits (or donations) is required to calculate ROI.

However, the decision about whether ROI is an appropriate metric also depends on the investment's time horizon. Some activities must yield a return immediately. Others, such as building relationships online or experimentation, can boost or protect profits in the future. In these cases, it will take longer to demonstrate positive ROI.

Having a clear understanding of the investment's time horizon is important. This can prevent efforts to use ROI analysis to inappropriately and prematurely cancel worthwhile projects.


ROI: Important, but Often Misunderstood and Misapplied

Figure 7. Calculating ROI



Why Focusing on ROI Is a Mistake in Health

Figure 8. ROI-Oriented Thinking: How Do Benefits Flow to Us?

We've spent a lot of time defining ROI and talking about its importance, but using ROI as the sole means of evaluating digital health content investments is a mistake. Health is different. Here's why.

Promoting health is not just about increasing profits. The ultimate goal of any marketing or communications initiative is to convince people to change or sustain positive health behaviors. Government, pharmaceutical companies and managed care alike have a shared goal of helping people live longer and more productive lives. They disagree on how to get there, but there is a shared consensus that improving health can deliver significant economic benefits to society.

Moreover, health organizations are being financially incentivized to demonstrate they improve overall health and wellness. For example:

• Pharmaceutical companies: Private and public sector payers have the most influence on drug firms' financial fortunes. To succeed, companies must prove their medications (and support activities) deliver economic benefits to society.

• Hospitals: Increasingly, hospitals with high in-hospital infection rates, readmissions and poor-quality care are being financially punished.

• Government: Programs that fail to improve health are being eliminated.



In this context, health organizations cannot afford to engage in ROI-oriented thinking (Figure 8). For the private sector, having executives evaluate digital health content investments solely on whether benefits are flowing from customers and stakeholders to the company is a mistake. More importantly, turning a profit isn't what motivates organizations such as non-profit hospitals, government and charities.

If ROI isn't appropriate, what metric should we use? We suggest the health industry adopt a metric called Return on Health Behavior or ROhB. ROhB was developed in 2012 by the health marketing communications innovation consultancy Enspektos, LLC. It measures the aggregate short- and long-term economic value associated with activating and sustaining positive health behaviors via digital health content. ROhB's benefits include the following:

• ROhB recognizes the new financial reality: It quantifies how the economic benefits of digital health content flow between organizations and society (Figure 9).

• Both the public and private sectors can use ROhB: It allows the public and private sectors to speak the same language when quantifying digital health content's benefits.

• ROhB encourages innovation: It can help justify experimental or long-term investments. Positive ROhB = worthwhile activity.

A new metric for evaluating digital health content: Return on Health Behavior.

Developed by Enspektos, LLC, ROhB quantifies the aggregate economic benefits associated with activating and sustaining positive health behaviors via digital content.

Figure 9. ROhB-Oriented Thinking: How Do Benefits Flow Between Us and Others?

Quantifying Digital Health Content's Economic Benefits



ROI, ROhB and Health Behavior

To help you understand why ROhB is a more appropriate metric for digital health content, we discuss it in the context of the Health Behavior Levels Matrix introduced earlier (Figure 6).

As outlined in Figure 10, ROI is primarily designed to help organizations determine if people are buying or donating. Because of this, it is best suited for measuring Level II health behaviors associated with making purchases or donations.

To properly calculate ROI, one has to accurately attribute digital content consumption directly to a purchase or donation. Digital attribution analysis is a complex subject, but companies like Adobe and IBM have designed tools to help organizations conduct it more easily. (10, 11)

However, ROI does not provide information on whether digital health content impacts short- and long-term non-purchase health behaviors. As discussed previously, understanding this is an imperative for the health industry.

ROI is also being used inappropriately. There are instances where the immediate goal is not to drive revenue. However, if a project does not demonstrate short-term ROI, a worthwhile initiative may be ended prematurely. Moreover, ROI is not an appropriate metric for non-profits and government.

Quantifying Digital Health Content's Economic BenefitsFigure 10. The Pros and Cons of ROI



ROhB is a more flexible metric, as described in Figure 11. Most importantly it does the following:

• Recognizes Financial Reality: ROhB does not ignore the fact that private sector organizations must turn a profit.

• Refocuses Non-Profits and Government from Evaluations Based on Activity to Economic Benefit: Sometimes non-profits and government executives are rewarded based on how much they produce and distribute. ROhB realigns the focus from what was made to health outcomes with proven economic benefits.

• Justifies the Use of Digital Media to Shape the Market and Build Relationships: ROhB enables health organizations to quantify activities such as relationship building or shaping the market. For example, proving that building an online community boosts medication compliance has many economic benefits, including these:

- Preventing illness (reducing medical costs)- Improved adherence (increasing drug revenue)- Improved productivity (boosting profits)

See Figure 12 for a sample ROhB calculation. Profits plus quantified economic benefits to society are compared to digital health content's costs to generate a ROhB figure.

Quantifying Digital Health Content's Economic Benefits

Figure 11. The Pros and Cons of ROhB



Quantifying Digital Health Content's Economic BenefitsFigure 12. Calculating ROhB (Thanks to Jane Sarasohn-Kahn of THINK-Health for Assistance with This Calculation)



Measuring Digital Health Content's Behavioral Impact

Figure 12. Few Studies Illustrate Digital Health Content's Impact on Behavior

You may agree it is important to link digital health content to health behavior change. You could also accept the argument that ROhB is a more appropriate metric for evaluating health online and social media initiatives. The question is how?

The first place some turn to for answers is in academic literature. In 2010, Peel Public Health in Canada commissioned a literature review examining the effectiveness of social media on health. (12) The concern was that public health organizations and others were embracing these technologies with little proof they work.

The authors found there were few peer-reviewed studies demonstrating social media was effective at increasing issue-related awareness and prompting adoption of desired behaviors (Figure 12).

In other words, there's little evidence social media drives health behavior change. However, the Peel Public Health paper has done little to dampen enthusiasm for social media in the health industry. People are using these technologies, so health organizations feel they must follow suit.

If we've hit a dead end with the academic literature, then what to do? This is another area where the Health Behavior Levels Matrix can be helpful (Figure 6). The Matrix stratifies digital-influenced behaviors by type. Measuring these behaviors requires different techniques and technologies, as outlined below.



Use Web and Social Analytics to Measure Level I Behaviors

The first goal of any digital health content initiative is to drive awareness and engagement. Level I of the Matrix accounts for these behaviors. These can be measured using a range of technology, as described below.

Web Analytics: Web analytics platforms can provide a wealth of information about how people arrive at and consume health content on a website. This data can also be used to examine the types of content that improve awareness and sales.

Social Analytics: There are many technologies that reveal how people engage with (Likes, tweets, retweets) and may perceive (sentiment) online content.

Measure Level II Behaviors with Digital Analytics, Surveys and CRM Platforms

Ignoring sales, revenue and profits is perilous, especially for private sector organizations like pharmaceutical companies and hospitals.

Digital analytics and surveys can reveal how online health content is driving hospital visits and coupon redemptions. It can also help organizations properly attribute social media to increased revenues and profits.

In the case of surveys, asking people how they heard about an event or why they redeemed a coupon can reveal a lot about what is driving purchase behavior.

Customer relationship marketing (CRM) programs can be leveraged to provide a range of data on the following:

• Acquisition: How potential customers are acquired (via newsletters, Web content or other means)

• Conversion: Which touchpoints (such as e-mail, events, white papers, in-person detailing, etc.) move people from consideration to purchase

• Social Media Impact: Social media being used by customers and prospects, and which content drives online purchase behavior (clicks, likes, additional sales)

Measuring Level III and IV Behaviors: A New Frontier

Existing techniques and technologies do a good job of providing data on Level I and II behaviors. However, teasing out how digital content influences Level III and IV actions is more difficult.

The authors of Peel's literature review of health and social media tackled this question. (12) They wrote: "When controlled research included an evaluative component, the results were often confounded by a failure to isolate the [social media] intervention from other communication strategies."



Clearly, measuring the behavioral impact of digital health content is a difficult task. However, as discussed above, doing so is critical.

Many existing platforms fall down when it comes to measuring Level III and IV behaviors. Content activity, sentiment and engagement data don't provide information about health behavior.

In the paid content arena, technology is more advanced. For example, in 2011, Westat partnered with Lotame to examine how online advertising impacted health behavior. Amelia Burke, Senior Director of Digital Media for Westat, reported:

"[D]ata were analyzed from audience engagement with . . . banner advertisements and surveys . . . [and] metrics such as increase in awareness, intent, and likelihood to recommend to a friend [were examined]. Across recent public health campaigns, specific . . . results included increases in intent of upwards of 24% and increases in likelihood to recommend to a friend/family member of upwards of 16%." (13)

However, much of the health content people consume online is earned, or non-advertising. How can we measure its performance? This is the next frontier in health behavior measurement. To the right are some key requirements for projects or technologies developed to tackle this problem.

Requirements for successfully quantifying the impact of earned digital content on health behavior:

Isolating Digital Inputs: Analyzing digital inputs separately allows for direct comparison. For example, health content received via Facebook may perform differently than information posted to a blog.

Accounting for Offline Effects: Behavior is influenced by many factors. What is the relative role of online content versus offline influencers?

Controlling for Motivation and Ability: How does content perform among individuals with high versus low motivation and ability?

Understanding the Full Digital Environment: People do not consume digital health content in isolation. What else are they seeing online? Does this information contain positive or negative messages? How is this content influencing behavior?

Right-Time Data: Digital media is ever-moving. Is data provided at the right time?



Mobile, Big Data and Health Behavior Change

In the mobile arena, a range of companies and organizations are tackling the health behavior change problem firsthand.

For example, in March 2012, Johns Hopkins University launched an effort to rigorously evaluate mobile health (mHealth) apps. These applications are being tested to determine if they help people begin or sustain behaviors such as exercising, quitting smoking and improving eating habits. (14)

In addition, a few companies are leveraging mobile to determine how multiple influencers, including content received via SMS and e-mail, reflect or predict health behavior. One firm is Ginger.io, which has developed a mobile behavioral analytics platform. The company "taps into the continuous sensor data from . . . mobile phone[s] and other devices to predict individual behavior changes and identify aggregate trends." (15) While not designed to activate behavior change, Ginger.io's technology can help us better understand the factors influencing a range of health choices.

There is much excitement about the potential of Big Data to revolutionize our understanding of a range of subjects, including health. Big Data refers to the ability to automatically process and analyze large amounts of information using sophisticated algorithms. A major source of data currently being analyzed comes from the Web and social media.

Much of the promising work in this area is being conducted to understand patients' real-world clinical outcomes. For example, data can be mined from social media channels to understand the following:

• What medication-related decisions consumers are making

• Why patients made these choices — e.g., because of medication side effects or other factors

Two companies, Prism Ideas and dMetrics, launched a partnership in 2012 to analyze "social media to determine patient actions and insights, profiling patient needs, symptoms and response to treatment."

Despite these advances, more work is required. First, many consumers in various health stages (pre-diagnosed, recently diagnosed, considering treatment, etc.) are not actively discussing their conditions online. Second, the Web is changing constantly. We need a better understanding of how ever-evolving digital information triggers influence the vast majority of people consuming rather than creating digital content.

This information can be used to help people:

• Understand how individual pieces of digital content influence health behavior

• Provide the appropriate level of evidence required to accurately calculate ROhB


Demonstrating ROhB: A Competitive Advantage

Digital technologies will only grow in importance as patients, health providers and other stakeholders embrace them. Because of this, health organizations will continue to invest in these tools.

But the private and public sectors will not be well served by simply focusing on the low-hanging fruit of digital measurement: revenues and content engagement.

We predict organizations that invest in demonstrating positive ROhB will be at a significant competitive advantage. They will be more likely to innovate. These organizations will also reap the economic rewards associated with consistently delivering effective and engaging digital health content.

We hope this ebook serves as a roadmap for those organizations ready, willing and able to understand the full value of their digital health content investments.

Health organizations that measure ROhB will have a significant competitive advantage. They will become hubs for innovation and understand how to produce digital health content initiatives that deliver maximum economic benefit.


End Notes

1. The Growing Influence and Use Of Health Care Information Obtained Online, Harris Interactive, September 15, 2011, http://bit.ly/qNNCzZ, Accessed March 22, 2012

2. Measuring the Business Impact of Social Media, Wildfire, January 19, 2012, http://bit.ly/yal8XS, Accessed March 22, 2012

3. Social Media: Preparedness 101: Zombie Apocalypse, Public Health Matters Blog, May 16, 2011, http://www.bt.cdc.gov/socialmedia/zombies_blog.asp, Accessed March 1, 2012

4. Revisiting CDC’s Zombie Apocalypse: It Sparked a Global Conversation, But Did it Change Behavior?, Walking the Path Blog, March 16, 2012, http://bit.ly/yyfdnY, Accessed March 17, 2012

5. Edelman Health Barometer 2011: Global Findings, Edelman Public Relations, October 2011, http://bit.ly/p63MuJ, Accessed March 25, 2012

6. B.J. Fogg, Persuasive Technology: Using Computers to Change What We Think and Do, 2003

7. B.J. Fogg, A Behavior Model for Persuasive Design, 2009

8. BJ Fogg’s 5 Secrets of Behavior Change, Sachin Rekhi's Blog, May 13, 2011, http://bit.ly/jLzkca, Accessed March 3, 2012

9. Marketing ROI in the Era of Big Data, Columbia Business School, Center on Global Brand Leadership, March 2012

10. Why marketers aren’t giving social the credit it deserves, Adobe Digital Index Report, Adobe, March 2012

11. Appropriate Attribution: Addressing the Dramatic Inaccuracies Associated with Last-Based Campaign Attribution in Digital Analytics, IBM Coremetrics, Web Analytics Demystified, 2011

12. R. Schein, K. Wilson, J. Keelen, Literature review on effectiveness of the use of social media, Peel Public Health, 2010

13. Finally! Identifying and Setting Social Media Benchmarks for Public Health Campaigns, Walking the Path Blog, September 7, 2011, http://bit.ly/mYwvbK, Accessed March 26, 2012

14. Hopkins researchers aim to uncover which mobile health applications work, Baltimore Sun, March 14, 2012, http://bit.ly/xoZhuS, Accessed March 27, 2012

15. The Science, Ginger.io Website, 2012, http://ginger.io/the-science/, Accessed March 27, 2012

http://www.harrisinteractive.com/NewsRoom/HarrisPolls/tabid/447/ctl/ReadCustom%20Default/mid/1508/ArticleId/863/Default.aspx

http://blog.wildfireapp.com/2012/01/19/measuring-the-business-impact-of-social-media-infographic/

http://blog.wildfireapp.com/2012/01/19/measuring-the-business-impact-of-social-media-infographic/

http://www.bt.cdc.gov/socialmedia/zombies_blog.asp





http://blog.pathoftheblueeye.com/2012/03/16/revisiting-cdcs-zombie-apocalypse-it-sparked-a-global-conversation-but-did-it-change-behavior/

http://blog.pathoftheblueeye.com/2012/03/16/revisiting-cdcs-zombie-apocalypse-it-sparked-a-global-conversation-but-did-it-change-behavior/

http://healthbarometer.edelman.com/2011/10/health-barometer-2011-global-findings/

http://healthbarometer.edelman.com/2011/10/health-barometer-2011-global-findings/

http://www.sachinrekhi.com/blog/2011/05/13/bj-fogg-5-secrets-of-behavior-change

http://bit.ly/mYwvbK

http://bit.ly/mYwvbK

http://bit.ly/xoZhuS

http://bit.ly/xoZhuS

http://ginger.io/the-science/




End Notes

16. Prism Ideas and dMetrics Launch Pioneering Service Analysing Patient–Reported Action, Behaviours and Outcomes with Social Media, Prism Ideas/dMetrics Press Release, January 25, 2012

Get More Insight

In September 2012, Enspektos, LLC launched digihealth pulse. This is the world's first ongoing tracking study investigating the impact of online and social media health content on the perceptions and behaviors of active digital health consumers (or e-patients).

Visit www.digihealthpulse.info for more information about the study.

http://www.digihealthpulse.info


About Enspektos

Founded in 2005, Enspektos, LLC is a digital health marketing communications innovation consultancy. We work with a range of health organizations, including pharmaceutical companies, payers, non-profits and government agencies.

We exist to help our clients (and the broad health industry) use digital technologies to inspire patients, caregivers and others to take action around health and wellness. We achieve this goal by developing and deploying a range of products and services, including enmoebius, a patent pending digital surveillance and behavioral measurement engine that reveals the link between digital health content and behavior change.

Learn more about Enspektos at www.enspektos.com.

http://www.enspektos.com

http://www.enspektos.com