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The transparent reporting of ward-by-ward staffing levels has been highlighted as a key action in the government’s response to the Francis Inquiry. Here we look at a tool being developed by Imperial College Healthcare NHS Trust which will alert multidisciplinary teams to staffing level risks on patient safety.

Sickness. High numbers of agency staff. Posts that aren’t filled when staff leave.

These are just three of the things that can affect staffing levels in many hospitals and which have an impact on patient safety. ‘The impact of staffing levels on patient care was a critical feature of the Francis report,’ says Eleanor Murray, Head of Programme Management at Imperial College Healthcare NHS Trust.

This is one of the reasons why Eleanor and her team are working with the Health Foundation to develop a new tool to help better plan staff rosters in three intensive care units (ICU). The bespoke software will evaluate how staffing levels could impact on patient care and safety. That way, staff will know earlier if rosters need to change because wards are understaffed or under-skilled.

‘This programme is taking a highly exploratory and innovative approach to identify what impact multidisciplinary workforce factors have on patient outcomes, and translate that knowledge into a workable tool,’ says Eleanor.

Learning so far

After starting work in July 2012, the project team are currently gathering together daily roster and clinical outcome data from their various ICU staff. This has been challenging because they have found that staffing tends to be planned within professions in silos and each uses a different system. ‘Although there have been improvements in NHS information systems, many have evolved historically and incrementally and this makes attempts to collate and analyse multidisciplinary data very complex,’ says Eleanor.

The idea is that the new tool would be used by clinical leads for nursing, allied health professions and doctors to jointly plan staffing rosters in advance. Eleanor says this would create a more flexible, resilient response to patient demand than the current fixed staffing ratios for ICUs.

‘When a clinical team leader is planning their staff roster, staff numbers and skill mix, alongside data such as bed numbers, would be entered into the tool,’ says Eleanor. ‘This would provide objective information about the potential impact of multidisciplinary staff numbers, skill mix and experience on clinical outcome measures for the clinical area.’

Building and testing

It is essential to the success of the tool that any links identified between staffing numbers and clinical outcomes have sufficient statistical power. Professor Stefan Scholtes at the University of Cambridge will help to do the analysis of local data. A review of existing literature and interviews with staff will also help identify links between workforce and clinical outcomes.

Two patient representatives also input into the project. ‘They help bring new ideas, and approaches from other projects that they are involved in at the hospital,’ says Eleanor.

Testing of the actual tool will take place in the three ICUs over a one-year period. It will be evaluated through staff interviews to understand how wards and units were operating before the tool, compared to how they do during and after they have piloted it. An attitude survey will also measure changes on the impact of safety and workforce issues.

Potential impact

If these evaluation results are positive, the tool could be used in general ward areas – and learning could be applied across the NHS. Eleanor is optimistic that, if the tool can be built using evidence-based principles, it will achieve its aim to improve patient safety and experience, and clinical team efficiency.

‘Success would be a dynamic tool that enables multidisciplinary teams to have objective conversations about staffing requirements in relation to clinical outcomes, and to have a means to escalate potential issues at an early stage, based on a clearly argued case using objective data,’ says Eleanor. ‘The project team is resilient and persistent and there is great enthusiasm to find answers to such a complex issue.’

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