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NHS Performance and Data Quality

NHS performance targets will be remembered as one of the defining features of Labour’s approach to health policy since 1997. However, the previous Conservative government had set targets in the 1990s – for example, guaranteeing a maximum two-year wait for non-emergency surgery and reducing rates of death from specific diseases.

But what was different about Labour's approach to targets in the NHS was the volume of targets and the vigour with which they were performance-managed.

There has been particular criticism of the targets for waiting times and the strong performance management that accompanied them – dubbed 'targets and terror' by some (Bevan and Hood 2006). However, the strength of the target regime in England is also credited with having driven faster reductions in waiting times than other UK countries between 1996 and 2006 (Connolly et al 2009).

More recently, the Conservative government has reduced the number of performance targets, and encouraged a system wide approach. NHS England guidance published in February 2018 conceded that most NHS targets would not be met. However, the number of NHS organisations failing to meet performance targets continues to hit the news headlines on a regular basis.

When I joined Audit Yorkshire in 2013, I was surprised to see the industry behind performance management, and was shocked to find out that NHS organisations faced significant financial penalties for not achieving government targets. While NHS Providers are no longer effectively ‘fined’ for breaching performance targets, financial incentives are being used to encourage NHS organisations to achieve performance targets on an annual basis.

There are still consequences of poor quality data for NHS organisation’s in that decisions are made on / using incomplete and inaccurate date, which can ultimately impact on:

  • Quality and safety
  • Clinical decision making
  • Demand and capacity planning
  • Loss of income
  • Financial planning
  • And many more

In a target driven environment, poor data quality can have a massive impact on whether or not performance targets are achieved. As performance reporting has become more and more automated over the years, Audit Yorkshire conducts regular audits for their clients to provide assurance to management that their reported data meets the Six Dimensions of Data Quality, which requires that data is:

  • Complete
  • Accurate
  • Valid
  • Relevant
  • Reliable, and
  • Produced in a timely manner

 At face value, many people think that data quality audits are nothing but a tick box exercise, checking that the data reported matches the data on the source database or records, and to some extent, this is the case. In reality though, data quality audits look much deeper than this and review processes and controls for end to end data processing.  It can be fascinating to gain a real in depth understanding of data collection, validation and reporting processes.  This holistic view is often unique and particularly important to our clients as the majority of staff and managers only have sight of their element of the process. 

I have conducted numerous data quality audits for both Acute and Mental Health organisations, and audit outcomes continue to surprise me. In my experience, operational delays in recording data on the source database or record, and/or weaknesses in the data validation process have significantly impacted on the quality of data reported. In recent years, data quality audits provided by Audit Yorkshire have enabled clients to improve decision making by improving data quality in their organisation.  In some cases, there have been significant financial savings as a result.