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dc.contributor.authorHawkins, Jared Ben_US
dc.contributor.authorBrownstein, John Sen_US
dc.contributor.authorTuli, Gauraven_US
dc.contributor.authorRunels, Tessaen_US
dc.contributor.authorBroecker, Katherineen_US
dc.contributor.authorNsoesie, Elaine Oen_US
dc.contributor.authorMcIver, David Jen_US
dc.contributor.authorRozenblum, Ronenen_US
dc.contributor.authorWright, Adamen_US
dc.contributor.authorBourgeois, Florence Ten_US
dc.contributor.authorGreaves, Felixen_US
dc.date.accessioned2016-07-14T19:19:35Z
dc.date.issued2016en_US
dc.identifier.citationHawkins, J. B., J. S. Brownstein, G. Tuli, T. Runels, K. Broecker, E. O. Nsoesie, D. J. McIver, et al. 2016. “Measuring patient-perceived quality of care in US hospitals using Twitter.” BMJ Quality & Safety 25 (6): 404-413. doi:10.1136/bmjqs-2015-004309. http://dx.doi.org/10.1136/bmjqs-2015-004309.en
dc.identifier.issn2044-5415en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:27662283
dc.description.abstractBackground: Patients routinely use Twitter to share feedback about their experience receiving healthcare. Identifying and analysing the content of posts sent to hospitals 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 US hospitals and compare patient sentiments about hospitals with established quality measures. Design: 404 065 tweets directed to 2349 US hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Sentiment was calculated for these tweets using natural language processing. 11 602 tweets were manually categorised into patient experience topics. Finally, hospitals with ≥50 patient experience tweets were surveyed to understand how they use Twitter to interact with patients. Key results Roughly half of the hospitals in the US have a presence on Twitter. Of the tweets directed toward these hospitals, 34 725 (9.4%) were related to patient experience and covered diverse topics. Analyses limited to hospitals with ≥50 patient experience tweets revealed that they were more active on Twitter, more likely to be below the national median of Medicare patients (p<0.001) and above the national median for nurse/patient ratio (p=0.006), and to be a non-profit hospital (p<0.001). After adjusting for hospital characteristics, we found that Twitter sentiment was not associated with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings (but having a Twitter account was), although there was a weak association with 30-day hospital readmission rates (p=0.003). 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 potentially untapped indicator of quality and may be valuable to patients, researchers, policy makers and hospital administrators.en
dc.language.isoen_USen
dc.publisherBMJ Publishing Groupen
dc.relation.isversionofdoi:10.1136/bmjqs-2015-004309en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878682/pdf/en
dash.licenseLAAen_US
dc.subjectHealthcare quality improvementen
dc.subjectPatient satisfactionen
dc.subjectQuality measurementen
dc.subjectPerformance measuresen
dc.subjectQuality improvement methodologiesen
dc.titleMeasuring patient-perceived quality of care in US hospitals using Twitteren
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalBMJ Quality & Safetyen
dash.depositing.authorHawkins, Jared Ben_US
dc.date.available2016-07-14T19:19:35Z
dc.identifier.doi10.1136/bmjqs-2015-004309*
dash.authorsorderedfalse
dash.identifier.orcid0000-0002-6352-1618en_US
dash.contributor.affiliatedHawkins, Jared
dash.contributor.affiliatedRozenblum, Ronen
dash.contributor.affiliatedWright, Adam
dash.contributor.affiliatedBrownstein, John
dash.contributor.affiliatedBourgeois, Florence


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