Abstract

Wright L. Diagnosis and Treatment of CT Constraints. Journal of Improvement Science 2023: 102; 1-31.

Computerised Tomography (CT) is a medical imaging technique essential for diagnosing and monitoring patients in most clinical pathways, including emergency medicine, cancer, stroke, general and neurological conditions. Since the lifting of COVID-19 restrictions in summer 2020, all acute trust Imaging departments have been under pressure to increase activity to 120% of pre COVID-19 levels and ensure compliance with Department of Health (DH) DMO1 requirements to image all elective patients within 42 days, all fast-track patients within 28 days and suspected cancer patients within 14 days.

Supported by NHSE South-East, the Kent and Medway Imaging Network (KMIN) engaged in a network wide approach to diagnose and treat the constraints of poor patient flow in CT. The approach used the Healthcare Systems Engineering (HCSE) methodology to train a member of the Radiology staff in each of the four trusts to HCSE Level 1, to develop inhouse improvement capability. This case study describes how each site used visible data to diagnose and treat the constraints that were pertinent to their specific CT service and to improve patient flow.

Using a Diagnostics Vitals Chart (DVC) each site was able to visualise the flow data of weekly requests, cancellations, images, work-in-progress (backlog), and lead times. There were some common findings including a high cancellation rate and many patients breaching waiting time targets.

Three of the sites measured the average utilisation of their CT scanners which was found to be low (38% to 70%) and immediately disproved the frequent assumption that lack of staffed CT capacity is the cause of target breaches. A deeper look into the processes revealed counterproductive booking policies, and bottlenecks upstream of the CT scanners.

Making the diagnosis of the different types of constraints is critical for trust managers delivering the service and for Imaging Networks planning new services. Once the diagnosis is made, improvements can be implemented to improve patient flow using focussed tests-of-change (ToCs).

The sites undertook several ToCs which allowed them to study the impact of the change before committing to rolling it out. These included Maidstone & Tunbridge Wells removing the time-trap policy and booking patients into the next available slot.

This has been an innovative approach to looking at a specific diagnostic service across a whole network. In building inhouse improvement technical skills and capability, and the benefit of almost real-time visible data, the clinical teams have been coached in the interventions required to deliver the service against the specification and become a self-managing, self-healing service.

6M Design (6M); Activity; Batching; Batching; Business Intelligence (BI); COVID-19; Carveout; Computer Tomography (CT); Cycle Time; DMO1; Demand; Diagnostic Vitals Chart (DVC); Diagnostics; Flow Capacity; Gantt Chart; Health Care Systems Engineering (HCSE); Healthcare; Imaging Networks; Integrated Care Board (ICB); Lead Time; Little's Law; Load; Medical Imaging; Policy Constraint; Radiology Information System (RIS); Test of Change (ToC); Time Trap; Touch Time; Work In Progress (WIP)