BMJ Qual Saf. 2014 Apr 19. doi: 10.1136/bmjqs-2014-002875. [Epub ahead of print]

Tweets about hospital quality: a mixed methods study.

Greaves F1, Laverty AA, Ramirez Cano D, Moilanen K, Pulman S, Darzi A, Millett C.

Author information

• 1Centre for Health Policy, Imperial College London, St Mary's Hospital, , London, UK.

Abstract

BACKGROUND:

Twitter is increasingly being used by patients to comment on their experience of healthcare. This may provide information for understanding the quality of healthcare providers and improving services.

OBJECTIVE:

To examine whether tweets sent to hospitals in the English National Health Service contain information about quality of care. To compare sentiment on Twitter about hospitals with established survey measures of patient experience and standardised mortality rates.

DESIGN:

A mixed methods study including a quantitative analysis of all 198 499 tweets sent to English hospitals over a year and a qualitative directed content analysis of 1000 random tweets. Twitter sentiment and conventional quality metrics were compared using Spearman's rank correlation coefficient.

KEY RESULTS:

11% of tweets to hospitals contained information about care quality, with the most frequent topic being patient experience (8%). Comments on effectiveness or safety of care were present, but less common (3%). 77% of tweets about care quality were positive in tone. Other topics mentioned in tweets included messages of support to patients, fundraising activity, self-promotion and dissemination of health information. No associations were observed between Twitter sentiment and conventional quality metrics.

CONCLUSIONS:

Only a small proportion of tweets directed at hospitals discuss quality of care and there was no clear relationship between Twitter sentiment and other measures of quality, potentially limiting Twitter as a medium for quality monitoring. However, tweets did contain information useful to target quality improvement activity. Recent enthusiasm by policy makers to use social media as a quality monitoring and improvement tool needs to be carefully considered and subjected to formal evaluation.