| Summary: | BACKGROUND Patients use Twitter to share feedback about their experience receiving health care. Identifying and analyzing the content of posts sent to each hospital may provide a novel real-time measure of quality, supplementing traditional, survey-based approaches.
OBJECTIVE To assess the use of Twitter as a supplemental data stream for measuring patient-perceived quality of care in U.S. hospitals and compare patient sentiments about hospitals on Twitter to established quality measures.
DESIGN Tweets directed to U.S. hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Additionally, sentiment was calculated for patient experience tweets using natural language processing.
KEY RESULTS Roughly half of the hospitals in the U.S. have a presence on Twitter. Of the tweets directed toward these hospitals, ~9% were related to patient experience. Analyses revealed that specific hospital characteristics were associated with lower sentiment. Finally, hospital sentiment was moderately correlated with a commonly used measure of quality.
CONCLUSIONS Tweets describing patient experiences in hospitals cover a wide range of patient care aspects and can be identified using automated approaches. These tweets represent a reliable predictor of treatment quality and may be valuable to patients, researchers, policy makers and hospital administrators.
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