Embedding analytics to improve inpatient flow

Sygal Amitay is Principal Analyst in the Information and Insight Department embedded within the Improvement and Transformation Team at Nottingham University Hospitals NHS Trust. 

She spoke to Q member Sophie Bulmer to share perspectives on using data to drive improvement. 

At Nottingham, Sygal delivers analytics as part of a Quality Service Improvement and Redesign (QSIR) methodology to improve flow for inpatient stays and streamline discharge processes. 

The aims are to improve productivity and experience and increase hospital capacity to address backlogs. 

‘The approach is for improvement, operational and clinical leads to work together, supported by data, to come up with an understanding of what needs doing,’ says Sygal. 

Analytical capability is embedded to support improvement projects through their lifetime: ​‘from the gap analysis and understanding the opportunities; understanding the service status quo; designing the measurement plan and delivering it; and finally understanding if the approach worked, why and how.’ 

Analytical products that directly support the improvement project, such as online patient management tools or ​‘knowing how we are doing’ (KHWAD) insight and reporting tools, give consistency and clarity around conversations on improvement at all levels.

‘The problem isn’t that we don’t have data. It’s that the data aren’t organised in a way that helps people to get actionable insight’, says Sygal of a challenge very familiar to the Q community.

To overcome this, they used the Qlik Sense platform to combine information from previously separate data and IT systems. Accessible reports of this combined data give teams a clearer picture of what’s happening.

One project succeeded in improving flow through a specialty, shortening every bit of the patient journey. 

However, it didn’t result in an overall improvement as a lack of capacity in social care created a barrier to safe discharge. 

This issue was compounded by a lack of visibility between organisations, and lack of emphasis on collecting data to better understand delays and bottlenecks.

Sygal says that many problems exist ​‘at the interface between hospitals and social care’ and access to data from outside their organisation to help address this remains an issue. 

Overcoming the perception by staff that data would be used to measure and judge performance, rather than to improve processes, was a consistent challenge.

‘[Staff] always think you’re going to just come up with new ways of measuring and telling them what to do and what they’re doing wrong,’ says Sygal.

The project team built trust by working collaboratively between clinical and improvement teams and patients to co-design measurement plans and tools.

See the Patient Experience Network video on this award-winning co-design project:

At trust level, a Chief Information Officer (CIO) helped improve the credibility and visibility of data-driven decision making. 

Improving the availability and quality of the analytics throughout the project lifecycle is making a difference to how clinical teams can access and use the data for driving improvements in flow. 

Clinical teams understand objectively what improvements have resulted and are able to share this with others. 

Further, Sygal benefited from an improved understanding of ​‘the hospital as a system’ and how services work on the ground. 

This was both professionally rewarding and invaluable insight when supporting teams to understand and design improvement projects and the accompanying measurement plans and analytical tools.

To do more data driven work, you need to work alongside teams at all stages of a project to ​‘make it safe’ for staff to engage with the data or ask for help. 

This also supports staff to feel more ownership of the data and encourages a more rounded understanding of it in context rather than feeling constrained by it, by drawing on the whole team’s expertise.

A major learning is about the interdependence of different parts of the system. 

Any realistic efforts to improve hospital capacity by reducing unnecessary delays to discharge ultimately depend on how different areas of the system work together.