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Social Media Feedback Can Identify High Risk Hospitals

Online patient feedback, including Twitter and Facebook posts, can provide accurate near real-time representations of the quality of care in NHS hospitals – thereby identifying high risk hospitals in need of inspection.  

These are the findings of a new study by researchers from the London School of Economics and Political Science (LSE) published in the BMJ Quality & Safety.

The researchers developed and tested algorithms that can reliably read and synthesise thousands of patient comments posted every day on platforms such as Twitter, Facebook and NHS Choices. Remarkably, when tested, the synthesised data was shown to effectively predict the outcome of hospital inspections by the Care Quality Commission (CQC).

At a time when the CQC is facing significant budget cuts and needs to focus its resources, this system could be used to highlight the hospitals most likely to be performing poorly and flag them for inspection.

Following the tragic events at the Mid-Staffordshire Trust in the late 2000s where an estimated 400-1200 patients died unnecessarily, there have been widespread calls to make better use of patient feedback in addition to traditional performance indicators which were slow to identify the unacceptable levels of care.

The study’s authors believe the near real-time information captured by their system offers hospitals and regulators a much quicker insight into their performance than existing surveys and official data collections.

Dr Alex Griffiths, a researcher at LSE’s Centre for Analysis of Risk and Regulation and one of the study’s authors, said: “The use of automated, near real-time patient feedback provides an opportunity not only to spot and rectify declining standards of care before they become too serious, but also to quickly identify improvements in care and learn what is behind them.”

“Aggregating comments from multiple sources allows us to gain insight from different demographics helping to reduce the obvious problem of bias that comes with using a single source of information, such as Twitter. Moreover, it gives us an understanding of aspects of care not captured by existing surveys, such as interactions between staff and carers at multiple points along care pathways, and often at a more granular level.”

The study’s authors are currently in discussion with the Care Quality Commission, the independent regulator of health and social care in England, over how the system may be used to help prioritise their inspections.

Dr Alex Griffiths and Meghan Leaver are respectively members of the Centre for Analysis of Risk and Regulation (CARR) and Department of Psychological and Behavioural Science at LSE.

For a copy of the article, please visit:

Source: London School of Economics and Political Science

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