The world of online health communities is morphing and evolving even as we sit here at our keyboards and google "flu symptoms" then tweet that we’ve got a cold. So what IS emerging from the cutting edge of online health communities? How do they differ and what do they have in common? The Health 2.0 conference presented an impressive array of new online breakout health community models. You can get the run-down on them all here. Check it out:

In Irving, Texas, Dr. Jeff Livingston is an Ob-Gyn who has been using MySpace to connect with pregnant teen patients. Now he has a Facebook HIPPA-compliant portal on a page for MacArthur Ob-Gyn. His practice is reaching patients through a variety of multi-media approaches. Patients can talk to him through Facebook. While his patients wait for their exam, they can watch educational videos. So what do his patients think of this? His teen patients say “how are you going to ignore a message, when you see it on Twitter, and on Facebook. This gives you a better way to connect with your doctor, rather than when you just see him face-to-face.”

Dr. Livingston says that when they began to connect with patients on Facebook and MySpace, teen patients began to feel comfortable coming to them. The more information his practice pushed out, the better decisions his patients made. One example he cites is the post-partum visit, where one of the most important choices a patient needs to make is what form of birth control they want. Now, his practice pushes birth control information out at patients through social media at every stage of their pregnancy, and, at that post-partum visit, they now “make really good choices."

In a different type of online community altogether, ACOR is a rich set of narratives from 70,000 people living with cancer. PatientsLikeMe, a similarly-themed community, is set up along more traditional data lines instead of narrative comments – but both founders say their communities are converging. According to ACOR, narratives are just another form of data – the only difference is that narrative is the most expensive to codify and analyze. One example of the richness of data available from ACOR’s community group occurred one week ago. Site administrators began to see a flow of patients reporting the cancellation of appointments for IL-2 for their kidney cancer. ACOR patients found a severe shortage of IL-2 and patients then spontaneously began to organize information about where they could go to get their next treatment.

PatientsLikeMe (80,000+ patients) also has become a platform for analytic research and discovery. The data-driven tools available to PatientsLikeMe communities are both for patients to get a better sense of their disease and education, and for industry to learn from them too. The PatientsLikeMe dashboard is changing dramatically. Treatment reports are reflected back live to users – dosing, side effects, treatment outcomes, etc. The site also includes a narrative forum. PatientsLikeMe reports that they try hard to capture the narrative journey in their analyses, although transferring that into actionable data is a challenge. An example of the valuable narrative information that is found in PatientsLikeMe is when a patient’s life-saving treatment is blocked by such factors as the lack of a caregiver, or the impact of treatment on finances. While that type of qualitative health information is often missing from traditional analysis of treatment compliance, it is, instead, frequently present in online discussions. Both industry and patients benefit when that type of information is available to show why certain chronic medications fail.

But can a client get a PatientsLikeMe level of data in a post-marketing trial? Not under our current system. And PatientsLikeMe showed another facet of its potential recently: an off-label lithium trial for multiple sclerosis that was conducted ad hoc in their online community took 12 months and the same type of post-marketing trial through the FDA/industry group cost $12 million and took years. Both the cost and the timeline shortened online considerably. However, the information collected by this online community is self-reported, and post-marketing only, but this site can also mine the narrative and the data both. Although some people don’t believe this type of data is valid, others recognize value while noting that self-selection of participants is its biggest issue. And the speed of information may be its biggest asset. As the moderator pointed out – when you’re crossing the street, do you want to act on data that’s 5 seconds old? PatientsLikeMe are pushing the envelope on this type of reporting to narrow the time-frame of results.

In yet another approach to mining online health communities’ experiences, First Life Research is a company that mines ten billion posts online – information that grows by 40% each year. First Life is a start-up that has been combing content across a vast number of platforms across the web (in English) – all of it is user-generated content online. Today’s summary overview included 600 million posts, 14 million authors, and over 9,000 medications.

The demo showed that information about the drug Singulaire, for example, could be found and categorized into side effects (then sorted into sub-categories) from over 21, 000 posts. Of this content, 50% of users reported some type of mental disorder while using Singulaire. Then, when the content data is broken down by year, they found that in 2007, Merck published a patient information notice about this side effect, then in 2008 the FDA reported it also. But it was present in online data as early as 2004. Mining all of the internet, then analyzing it, then presenting responsible results is quite a challenge – First Life have been working at it for 3 and a half years.

Through their analysis, they are able to show side effects that the drug leaflet doesn’t even have, and show the percentages reported, which are often different from those represented by the company. They are also able to compare these reports against competitor drugs, which is hard to find with current drug trials. Often it is impossible to have drug companies compare their drugs against ones that are already available. Although First Life mines thousands of sites across the web, many sites, however, are not included – for example PatientsLikeMe is not represented. PatientsLikeMe doesn’t allow access to its user data from those external to the site. Doing so would violate their user agreement. PatientsLikeMe is not open to trade groups or data mining.

This is particularly an issue for rare diseases, according to ACOR. Only 5% of what’s on the internet is visible. Thousands of online communities deal with rare diseases, and those are often not "visible". These topics, sites and communities do not show up in data mining activities. As patients, we’ve been having the Who’s Data Is It conversation in health. Now, we may be looking at another type of Who’s Data Is It conversation – this time with online health communities.

In yet another new type of online health community, dLife and iWantGreatCare are two examples of online communities embedded into healthcare delivery models.

dLife paired with Geisinger Health System to create a health community. Behavioral health knowledge and compassion were key part of the success of the collaboration between the two institutions. Geisinger Health System, has been a cutting edge healthcare system, located in rural, central Pennsylvania. Patients are from a large geographic area and many patients have to travel over an hour each way to see their doctor once a year. Diabetes is a pressing issue, not just for this area, but for many areas in America, with one out of every $5 of healthcare in the U.S. now spent on diabetes.

Geisinger cares for over 20,000 type 2 diabetics, with over 800 physicians (who each manage one or two hundred diabetic patients). The goal of the collaboration with dLife and the health community creation is to improve diabetes disease management. The hypothesis is that compared to usual care methods, this online community approach is a system that can significantly improve both subjective and objective measures. It’s a nested case-control randomized clinical trial studying patients with a hgbA1C of 8 or more. The patients included in the study are the least well controlled, and there are twice as many men as women (an unusual proportion for most diabetes trials).

dLife, is a consumer portal, with over a million members. They have a television program with an audience of over half a million a week. The online community includes a personalized website, newsletters, IVR (learning and motivational calls), weekly emails and other features – it’s a constant drumbeat of motivation and information. The goal of the site is to provide empathy and understanding for the day in and day out choices that people must make to improve their health. They report that learning your own personal motivation is a very important part of the interaction. Is it to be able to dance at your grand-daughter’s wedding, or is it, instead, something as poignant and simple as keeping all your toes? Tapping into that motivation is key.

So how does the study work? As a patient randomized to participate in the health community, from the introductory email, you’d go to the site where only one interaction is required – that is the setting up the site (putting in your goals and situation, etc.). For each week, there is a theme and all the content at the site and the content pushed out to the community ties into that same theme. You can ask an expert a question if you want, you can watch one of their 500 video segments, or you can look up recipes.

Early results among study subjects show that, while computer literacy is low, and education level is low, study participants became engaged based on such measures as their  page-views, email openings, and the quizzes that they took. Over half were moderately or hyper-engaged. Those patients who were randomized to dLife were more likely at 3 months to have their blood test drawn, more retention in the study, more compliance with visits and more likely to have a blood test in target range. And set up was simple for enrolling patients in the community. Issues with literacy and language issues were the only “customization” that had to happen.

In yet another new type of health community, Neil Bacon spoke about iWantGreatCare. iWantGreatCare is a site with a completely different type of embedded online community with an existing healthcare system. iWantGreatCare collects and curates healthcare information in the U.K. using structured data analysis that allows institutions to use the information and make decisions. Clearly, better outcome results are important for all stakeholders – the general public and patients, individual healthcare providers, and large organizations. But the outcomes that are important, however, are the ones important to patients. iWantGreatCare allows patients to choose an area or a provider, and then allows you to see ratings. There’s nothing particularly innovative there – other sites exist that already perform the same tasks. But making this data – the insights, and both the quantitative and qualitative data – available and useful to the providers and institutions is what’s new about this community interaction.

For the provider, iWantGreatCare is Google-optimized so that iWantGreatCare comes up higher in a Google search of a physician’s name. They get more awareness and traction that way. iWantGreatCare also provides widgets for doctors to put on their pages. But most importantly, the same data that the patients are using is provided, in real time, to doctors and institutions to allow them to compare themselves across other providers, other institutions and other areas of the country. Providers and institutions can see how they perform. Hospitals are subscribing to this service – this community model is that they provide real insight to hospitals and providers about how they’re doing.

Next up, in terms of breakout health communities online is the building of healthcare apps on non-healthcare platforms. That Health 2.0 panel consisted of Manny Hernandez of Diabetes Hands Foundation, Chris Cartter of MeYou Health, and Alex Ressi of TweetWhatYouEat as well as Josh Elman of Twitter.

So what are these communities? Tweet What You Eat is the simplest food diary you could ever keep. It was built in 2007 – Alex Ressi said he wanted it to be as simple as possible, he wanted to never have to look up a calorie count, and he wanted to have an online community to support him. In his demo, he showed how you can use d for Direct message (to keep your food private to yourself), put in foods with comma separations, and you can put a colon into it for known calorie counts.

You must register with the site to use it. Then, when you go to the site, you can see at a glance what everyone has had to eat. The idea behind it is that open food diaries keep yourself accountable. The heart and soul of the community is in the forum, which has a variety of weight loss tips and questions. You can go to My Diary to see what’s in your personal diary. If you’ve eaten that food in the past, the site will grab it and use its calorie count. But if someone else has eaten it, crowd-sourcing provides the calories assigned to it. You can click on calories to see which calorie count is used, and change it to another is you want. Tweet What You Eat was built on Twitter, Alex said, because it was already integrated into his everyday life, is on smartphone and could be done from a desktop.

Chris Cartter focused on behavior change and has a brand new product demo with MeYou Health, a Facebook-based app called Change Reaction. The app sits right on top of a member acquisition funnel. Its simple idea is that people will pledge to do one healthy behavior a week, invite their friends and watch the chains grow.

How does that work? Once a behavior-goal is chosen (“I’ll eat vegetables tonight at dinner!”), there’s a simple pop-up explanation of why this goal is good for your health. The goals are intentionally small – using the philosophy to take big goals and reduce them to tiny steps. You get auto-prompted to invite friends, and to email them or not. When you join a chain, you become the top of the chain, and, as the chain forms, you can drill down and see the links of other people in the same chain who are also tackling this goal, as well as their comments. You get a point for every chain you join, and a point for every time a friend you’ve invited has joined a chain. Your stated goal then shows up on your Facebook wall. So, will this type of health community make a real change? Chris pointed out that micro-behaviors and micro-choices are used to gain traction. As a user looking for support, you get access to your own social graphing from using Facebook and these goals target not your “300″ Facebook friends, but a crucial 8-10 friends who will go on the journey with you. The whole game and all interactions are meant to raise awareness and mindfulness about healthy behaviors.

Healthseeker is also a Facebook game, from the non-profit Diabetes Hands Foundation. Healthseeker was launched intentionally on Facebook to leverage the connectivity and also to target social gamers – women 45 and over are the most hardcore social gamers on Facebook. Diabetes Hands Foundation partnered with Joslyn Diabetes Center to create this game. It works in yet another way to promote behavior change for better health: you choose four different lifestyle goals (on the right side of the page). Then you choose to take on the “missions.” For each mission, you can choose up to 3 actions (all are activities outside-Facebook, in the real world, not the virtual world!). All of these missions are simple to do and you take on this mission for a period of 7 days. Your Facebook social graph becomes your support during that mission. Check out Healthseekergame.org to learn more.

Finally, Josh Elman of Twitter talked about using the social proof of online connection to help drive behavior change. Even in just the existing environment of Twitter, people already share their health challenges publicly, and also support others in the same process. Facebook and Twitter provide the platforms for people to do this with their friends, rather than having people go somewhere else to think about their health.

What’s the take-home message? In the world of micro-financing, publicly declaring your intention to repay your debt dramatically increases your chances for doing so. The model holds true in health-change. Most people know what to do – the challenge is getting yourself to do it. Building your social support to do so is key, as well as breaking it down into tiny steps. So whether it’s a tweeted food diary, or a doctor seeing his patients on Facebook, the world of health communities is changing at the speed of byte.

What do you think? Do you havea favorite online health community? Share your take in the comments section. Are you a Doc Gurley fan? You can follow Doc Gurley on Facebook. Doc Gurley is the only Harvard Medical School graduate, ever, to be awarded the coveted Shoney’s Ten Step Pin for documented excellence in waitressing, and is a practicing board-certified internist. You can get more health posts at www.docgurley.com, or jump on the Twitter bandwagon and follow Doc Gurley. Also check out Doc Gurley’s joyhabit and iwellth twitter feeds – so you can get topic-specific fun, effective, affordable tips on how to nurture your joy and grow your personal wellth.

Posted By: Doc Gurley (Email) | October 09 2010 at 01:01 AM

<a href="http://www.sfgate.com/cgi-bin/blogs/gurley/detail?entry_id=74139tag:news.google.com,2005:cluster=http://www.sfgate.com/cgi-bin/blogs/gurley/detail?entry_id=74139Sat, 09 Oct 2010 08:04:15 GMT 00:00″>Health 2.0: Can you have a doctor visit on Facebook? : Doc Gurley : City Brights

Tags: healthcare delivery models, Doc Gurley, First Life Research, data mining activities, Jeff Livingston

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