The 40th Alliance Annual Meeting, held January 14th-17th, 2015, wrapped up in Grapevine, TX, with Global staff members among the more than 1200 attendees and 60 exhibitors from the medical education community. The meeting was a huge success for Global and the CME community as a whole. Global received an award from The National Association of Medical Education Companies (NAMEC), and Amanda Glazar, Senior Director of Education Strategy, presented a breakout session on next level outcomes reporting. Pictures and highlights of Global's presence at the conference can be found at the bottom of the page. While the conference featured a number of informative and engaging sessions, the one that stuck out and made an impact throughout the conference was the Day 1 Keynote Session by Jennifer Goldbeck, titled “Big Social Data.” Jennifer discussed the rise of social media and its impact on data analytics, as well as how new data mining techniques can reveal hidden traits and characteristics of millions of people online. When Jennifer showed the Take This Lollipop video to the audience, which showed just how accessible your private FaceBook data through third party apps really is, the reaction in the room and across social media was incredible. The conference hashtag #acehp15 was flooded with audience members voicing their opinions and reactions. Some of the stand-out tweets included messages such as "I am literally terrified," "People are furiously uninstalling Facebook apps all across the room," and "Dude. #Creepy." It really is creepy when you realize how much companies can access and use your data. If you’ve ever searched for a product online, and then navigated to a social media site like Facebook, for instance, you might notice that the product you just searched for is now appearing as a paid advertisement on your Facebook home page. This sort of targeted advertising has existed for quite some time and is an advertising strategy for companies to target their products directly to consumers who might be interested.

The Creepy Side of Data Collection and Analysis

When Jennifer shared the Target Pregnancy Story on predictive analysis, the creepiness of public data collection and analysis was verified. In short, Target was able to predict that a teenage girl was pregnant before she had told her parents and family, and sent her coupons for baby formula and diapers. The girl’s father complained to their local Target store, asking why they had sent coupons meant for a pregnant woman to their daughter. The local Target store had no idea, as ads and coupons are typically sent from corporate offices. The father then returned to the store a few days later and apologized to the store manager after discovering his daughter was pregnant. When the story broke the question had to be asked: How could a big box chain store know a random shopper was pregnant before her family did? As it turns out Target was using her purchase history data and predicted that she might be pregnant based on recent purchases that she made. The items that she purchased were vitamins, a large purse, and a bright rug. If you examine these items as stand-alone purchases it doesn’t really tell you much- these are common items purchased every day throughout the country. However, by digging deep into the data and matching other shoppers’ purchase history data to this young woman’s, Target guessed that she might be pregnant and sent her coupons for items commonly purchased by women who are expecting (diapers, a bottle, formula, etc). Jennifer’s presentation opened a lot of eyes to the realities of data collection and analysis in the social media driven world we live in today. Companies like Target will likely always use our data for the benefit of their marketing and advertising initiatives. However, there are also practical benefits to collecting and analyzing big data, particularly in the field of healthcare, that Jennifer did not mention. Two recent studies in particular showed how social media data can be collected, analyzed, and used to predict disease outbreaks in local communities, as well as a specific cause of death in a population area.

The Not So Creepy Side of Data Collection and Analysis

The first study, "Digital Disease Detection: Using Social Media To Predict Flu Trends", was discussed in an article posted by the Digital Disease Daily. The study discussed the role data collection through social media can play in disease trend prediction.

"Researches compiled tweets containing flu-related terms (flu, influenza, Tamiflu), the time at which each tweet is published and the geographical location from which the tweet is sent."[1]

The results showed that data collected using this method strongly correlates with more traditional and robust methods used by the CDC. While traditional methods used by the CDC are much more accurate in case identification, they are often times much slower in overall data collection and eventual publication of the results to the public. Social media data is collected in real-time and may help provide information in a more timely manner. The article concluded that

"the vast amount of data available through social media can be used in combination with traditional data sources for making better public health decisions."[1]

The data collected and analyzed through Twitter won’t replace traditional reporting methods used by the CDC, but there might be potential to use the data as a supplement to the more traditional methods, which can assist researchers in accurately forecasting flu activity. Another great example of using data collection and predictive analysis in healthcare comes from a study conducted by The University of Pennsylvania. Over the past several years the study examined the relationship between a person’s psychological state and coronary heart disease by collecting Tweets where the “Tweeter” made their public location available. They were able to segment and collect the data, county by county in The United States, the same way that public health officials do when collecting and analyzing data for cause of death on death certificates. The study showed that:

"negative emotional language and topics, such as words like “hate” or expletives, remained strongly correlated with heart disease mortality, even after variables like income and education were taken into account. Positive emotional language showed the opposite correlation, suggesting that optimism and positive experiences, words like “wonderful” or “friends,” may be protective against heart disease"[2]

The data and conclusions made by the research team suggested that the correlation between language tone and heart disease mortality are fairly accurate and might be useful in predicting heart disease deaths. The attached image from the study shows strikingly similar rates of heart disease between actual reported heart disease deaths, and language and emotion data collected from Twitter. While the data collected from Twitter will likely never give a completely accurate prediction of the number of heart attacks in a region, it may give health officials a more accurate description of where health interventions are needed. The amount of data made available and collected in a public forum is staggering, and continues to grow and grow every single day. According to Digital Insights, a social media analytics company, there were over 500 million tweets sent per day in the first half of 2014, and over 1 billion total twitter accounts. Facebook saw an average of 1.28 billion active users per month. While there is a high probability that some of this data will be misused as a form of advertising, there is still a great potential for the data to be used for health benefits and education of communities as a whole, as demonstrated by the two studies above. The opportunity is there and it’s up to us as leaders in the medical education community to find new and innovative ways to use and apply this data effectively and responsibly. Overall the conference was a great success and we were pleased to meet and catch-up with so many of you. Check out more pictures of Global staff members below as they participated in various sessions and exhibited in the hall. If you have any questions about the keynote review, The Alliance Conference, or any CME related question in general, please don't hesitate to contact us here today. [1]: http://www.healthmap.org/site/diseasedaily/article/digital-disease-detection-using-social-media-predict-flu-trends-31114 [2]:http://www.upenn.edu/pennnews/news/twitter-can-predict-rates-coronary-heart-disease-according-penn-research [caption id="attachment_2694" align="alignleft" width="300"] Amanda Glazar, Senior Director of Education Strategy, presents at The ACEhp Annual Meeting[/caption] [caption id="attachment_2692" align="alignright" width="300"] Seth Fritts and Amanda Jamrogiewicz, Global's Directors of Education Partnerships, and John McCormick, Program Coordinator, at the Global Booth in the exhibit hall[/caption]
[caption id="attachment_2699" align="alignleft" width="300"] Kurt Boyce (ACE) and Amanda Glazar receive the Best Practice in Learner Outcomes Award from NAMEC for REMEDIES: Focus on Opioid Tolerance[/caption]