Insights & Transformation Consulting
Decades of experience supporting clinical and operational leads to deliver high impact change.
A tried-and-tested ‘triangulation’ approach that builds change consensus, combining leading-edge service analysis with frontline observations.
Frontline engagement from the start, to build rapport and generate buy-in at every level.
A ‘one team’ approach that supplements internal change resource, but doesn’t substitute, to make sure change sticks.
Staff and clinical leads are busy, and often project fatigued. They face significant challenges with fragmented data systems, inefficient workflows, and limited resources. These issues hinder their ability to act quickly and decisively when it comes to optimising service models.
Skilled and experienced change facilitators are essential to support and drive transformation to ensure patients benefit from the best service provision possible. There is large scope for process improvement by taking a Lean approach, which helps eliminate waste, streamline operations, and enhance overall efficiency.
how it works
Getting off to a good start is key. We advocate use of a ‘message house’ to preserve a consistent positive change message with those impacted.
The starting point is an initial ‘4Ns’ listening exercise to build rapport. This ensures those involved can see that the organisation aligns with them on the change they want to see.
With rapport built we can complete a ‘triangulation’ of the status quo and capture the end state vision. Change consensus is delivered through the alignment of data analytics, process walkthrough and staff engagement.
Increasing direct clinical care time, which is normally only a small percentage of total clinician time, is often a focus. This entails addressing the reasons why, for example, administration consumes too much time.
Another feature of our work is exploring ‘time traps’. Mental health diagnosis and need assessment is subject to differing judgment and information needs. Clinicians can find themselves repeating steps or being party to an MDT or review meetings that are not well designed.
More fundamentally, a service model may need to be refined. Packages of care may not be well defined, or service delivery has evolved locally without enough focus on unwarranted variation. Data tools help support here by providing much-needed visibility.
Case studies
Delivering a 70% reduction in wait times by implementing an 'easy-in, easy-out' model in community mental health teams
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