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The Potential of Twitter as a Data Source for Patient Safety

Nakhasi, Atul, MD, MPP*; Bell, Sarah G., BA; Passarella, Ralph J., BA*; Paul, Michael J., PhD; Dredze, Mark, PhD; Pronovost, Peter J., MD, PhD*§∥¶

doi: 10.1097/PTS.0000000000000253
Original Article: PDF Only

Background Error-reporting systems are widely regarded as critical components to improving patient safety, yet current systems do not effectively engage patients. We sought to assess Twitter as a source to gather patient perspective on errors in this feasibility study.

Methods We included publicly accessible tweets in English from any geography. To collect patient safety tweets, we consulted a patient safety expert and constructed a set of highly relevant phrases, such as “doctor screwed up.” We used Twitter’s search application program interface from January to August 2012 to identify tweets that matched the set of phrases. Two researchers used criteria to independently review tweets and choose those relevant to patient safety; a third reviewer resolved discrepancies. Variables included source and sex of tweeter, source and type of error, emotional response, and mention of litigation.

Results Of 1006 tweets analyzed, 839 (83%) identified the type of error: 26% of which were procedural errors, 23% were medication errors, 23% were diagnostic errors, and 14% were surgical errors. A total of 850 (84%) identified a tweet source, 90% of which were by the patient and 9% by a family member. A total of 519 (52%) identified an emotional response, 47% of which expressed anger or frustration, 21% expressed humor or sarcasm, and 14% expressed sadness or grief. Of the tweets, 6.3% mentioned an intent to pursue malpractice litigation.

Conclusions Twitter is a relevant data source to obtain the patient perspective on medical errors. Twitter may provide an opportunity for health systems and providers to identify and communicate with patients who have experienced a medical error. Further research is needed to assess the reliability of the data.

From the *Johns Hopkins University School of Medicine, Baltimore, Maryland; †University of Michigan Medical School, Ann Arbor, Michigan; Departments of ‡Computer Science and Human Language Technology Center of Excellence, and §Anesthesiology and Critical Care Medicine, and ∥Surgery, Johns Hopkins University, Baltimore, Maryland and Armstrong Institute for Patient Safety; ¶Quality, Johns Hopkins University, Baltimore, Maryland.

Correspondence: Atul Nakhasi, MD, MPP, 733 North Broadway, Edward D. Miller Research Building, Suite 137, Baltimore, MD 21205. (e-mail: anakhasi@gmail.com).

M.J.P. is a member of the advisory board to Sickweather, company that does illness forecasting using social media.

M.D. received compensation for travel for talks at various academic, corporate, and governmental entities and consulting for Directing Medicine, Progeny Systems, and Sickweather, company that does illness forecasting using social media.

All other authors declare no support from any organization for the submitted work, no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years, and no other relationships or activities that could appear to have influenced the submitted work.

A.N., S.G.B., and R.J.P. contributed equally as first authors.

A.N. coauthored the primary manuscript draft and all major revisions, led the analysis and interpretation of the data, critically reviewed and edited the manuscript, and have seen and approved the final version.

R.P.J. coauthored the primary manuscript draft and all major revisions, led the analysis and interpretation of data, critically reviewed and edited the manuscript, and have seen and approved the final version.

S.G.B. coauthored the primary manuscript draft and all major revisions, led the analysis and interpretation of the data, critically reviewed and edited the manuscript, and have seen and approved the final version.

M.J.P. helped develop the study protocol and design, coordinated all data collection, designed the statistical plan and conducted the statistical analyses, critically reviewed and edited the manuscript, and have seen and approved the final version.

M.D. performed or directly oversaw all aspects of the study from conception through completion (principal investigator), critically reviewed and edited the manuscript, and have seen and approved the final version.

P.J.P. performed or directly oversaw all aspects of the study from conception through completion (principal investigator), critically reviewed and edited the manuscript, and have seen and approved the final version.

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