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Complaints data is untapped resource for NHS improvement

The NHS can better utilise the vast potential of patient complaint data, according to a new study by the London School of Economics and Political Science (LSE).

In their research paper (1), published in BMJ: Quality & Safety, Dr Alex Gillespie and Dr DrTom Reader of the Department of Social Psychology argue that adopting a consistent system to assess the nature and severity of complaints across the NHS will both improve service levels and enable benchmarking across hospitals and trusts. They have developed the Healthcare Complaints Analysis Tool (HCAT), the first reliable method of coding and systemising healthcare complaints.

Due to the complex nature of many complaints, one of the major challenges of complaints data analysis is developing a consistent approach to coding and management. To address this, HCAT conceptualises complaints in clinical, management and relationship domains, using seven distinct categories: quality, safety, environment, institutional processes, listening, communication, and respect and patient rights. HCAT also reliably identifies problems at four levels of severity, enabling complaints to be organised by severity.

The tool offers a range of benefits to the NHS’ management of quality and safety. HCAT is designed to be integrated into the management of care— as an additional measurement of performance within departments— across hospitals and regions. It also responds to health regulators and policymaker’s urgings for better handling and learning from complaints.

Dr Tom Reader said: “HCAT offers a reliable method for categorising, analysing and aggregating the data across the healthcare system. One of the benefits of a national health system is that complaints can be collated nationally and used as a source of learning across the entire system. HCAT allows for comparison and benchmarking of complaints within hospitals, trusts and over different time periods and geographic areas.”

Dr Alex Gillespie said: “The central innovation of HCAT is the ability to accurately measure the severity of complaints which will help hospitals and policy makers identify key areas of concern.

“HCAT will allow the NHS to unlock the potential of healthcare complaints data, bringing huge benefits at every stage of the care process. Central to our research is the championing of the patient voice, putting patients at the centre of healthcare provision in the UK, and learning from their observations and concerns. HCAT is now freely available to download and use and we are working with Trusts, for example United Lincolnshire Hospitals NHS Trust, to implement it.”

The research used a sample redacted NHS complaints data from 2011-2012, and replicated conditions of NHS staff managing the complaints data (2).

Notes

  1. 2. HCAT was developed from the analysis of a random sample of 1% (1,082) of the 107,000 healthcare complaints NHS Trusts received between April 2011 and March 2012. The researchers recruited 14 students to analyse redacted complaints, replicating the environment and skillset of NHS administrative staff expected to complete the task. Through a three-stage iterative process, the researchers refined the coding system to identify the seven problem categories, and developed their 4 stage method of categorising the severity of complaints.

The NHS receives approximately 110,000 complaints each year; the complex nature and the lack of formal systematic learning from complaints means that monitoring the level and severity across the service is not carried out at an national level. Litigation expenses arising from negligence or unacceptable care are accounting for increasing amounts of the NHS’ expenditure, with the NHS Litigation Authority setting aside £26bn to cover medical negligence claims against NHS hospitals in 2015.

The Department of Social Psychology at LSE is a leading international centre dedicated to consolidating and expanding the contribution of social psychology to the understanding and knowledge of key social, economic, political and cultural issues.

To interview the authors, please email Dr Alex Gillespie: A.T.Gillespie@lse.ac.uk and Dr Tom Reader: T.W.Reader@lse.ac.uk

14 January 2016

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