Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department
- Kevin A Padrez ,
- Lyle Ungar ,
- Hansen Andrew Schwartz ,
- Robert J Smith ,
- Shawndra Hill ,
- Tadas Antanavicius ,
- Dana M Brown ,
- Patrick Crutchley ,
- David A Asch ,
- Raina M Merchant
BMJ quality & safety |
Background: Social media may offer insight into the relationship between an individual’s health and their everyday life, as well as attitudes towards health and the perceived quality of healthcare
services.
Objective: To determine the acceptability to patients and potential utility to researchers of a database linking patients’ social media content with their electronic medical record (EMR) data.
Methods: Adult Facebook/Twitter users who presented to an emergency department were queried about their willingness to share their social media data and EMR data with health researchers for the purpose of building a databank for research purposes. Shared posts were searched for select terms about health and healthcare.
Results: Of the 5256 patients approached, 2717 (52%) were Facebook and/or Twitter users. 1432 (53%) of those patients agreed to participate in the study. Of these participants, 1008 (71%) consented to share their social media data for the purposes of comparing it with their EMR. Social media data consisted of 1 395 720 posts/tweets to Facebook and Twitter. Participants sharing social media data were slightly younger (29.1±9.8 vs 31.9±10.4 years old; p<0.001), more likely to post at least once a day (42% vs 29%; p=0.003) and more likely to present to the emergency room via self-arrival mode and have private insurance. Of Facebook posts, 7.5% (95% CI 4.8% to 10.2%) were related to health. Individuals with a given diagnosis in their EMR were significantly more likely to use terms related to that diagnosis on Facebook than patients without that diagnosis in their EMR (p<0.0008).
Conclusions: Many patients are willing to share and link their social media data with EMR data. Sharing patients have several demographic and clinical differences compared with non-sharers. A database that merges social media with EMR data has the potential to provide insights about individuals’ health and health outcomes.