Partnering with County Durham and Darlington NHS Foundation Trust on service improvement
- By Philips
- March 03 2025
- 2 min. skaitymo
Through County Durham and Darlington NHS Foundation Trust’s Managed Service strategic partnership, Philips and the Trust launched a service improvement project including an operational informatics solution to provide visibility of performance and help identify ways to improve patient flow.
Trumpai:
- Partneris
- As part of County Durham and Darlington NHS Foundation Trust’s existing Managed Service strategic partnership, Philips and the Trust launched a service improvement project.
- Iššūkis
- The partners identified the need to innovate the radiology service and capitalize on the opportunities of data driven decision making, to transform patient workflows and maximize efficiency of new equipment.
- Sprendimas
- The project consisted of multiple focused workstreams aimed at enabling the Trust to optimize the efficiency of the radiology service through introducing new techniques, service pathways and quality managemen
- Rezultatai
- Over 80 Radiology department staff have been trained, staff feedback has been embodied in departmental change and there has been + 35% increase in MR exam throughput, reduced MR cycle times and better scheduling.
Moving far beyond a traditional supplier partnership to deliver radiology service improvement
In 2018, CDDFT and Philips agreed a 14-year Managed Service partnership focused on introducing the latest, cutting-edge diagnostic imaging equipment, combined with transformational service improvements. Together through CoCreate workshop sessions, Philips and the Trust identified the need to transform the service and capitalize on the opportunities of data driven decision making, to transform their patient workflows and maximize the efficiencies of their new radiology equipment. To achieve this, the partnership launched a service improvement project.
A key challenge for radiology at the Trust was improving service efficiency while enhancing quality and patient experience. This could only be achieved by engaging its increasingly busy staff, at all levels in the department, in systematic improvement activity.
The service improvement project started one year into the Managed Service partnership. The project consisted of multiple focused workstreams aimed at enabling the Trust to optimize the efficiency of the radiology service through introducing new techniques, service pathways and quality management; all elements working together to ultimately improve patient care and satisfaction.
Results*
To date, the first part of the partnership, the service improvement project has delivered:
- Near real-time visibility of departmental workflow: Implementing the Performance Bridge solution making performance data visible to drive continuous improvement
- Ability to highlight areas of criticality: Patient flow improvement opportunities identified through analysing radiology workflow data (CRIS).
- Tangible workflow efficiency: A gain of 50 additional MR patients per week at one site
- Modality leads and teams feel confident to use operational data: Coaching and educational programs delivered staff confident to create their own dashboards
- Over 80 Radiology department staff trained: Staff trained in foundation (or bronze) level quality improvement training to drive a performance improvement culture
- Staff feedback embodied in departmental change: The staff experience survey focused on staff perception regarding identified improvement areas to build the transformation around staff pain points
- Over 35% increase in MR exam throughput: Compared to pre-COVID19 performance patient flow improved, supporting effective management of waiting times.
- Reduced MR cycle times and better scheduling: Released c and improved patient experience
- Dashboards make the patient experience visible: Patient turnaround times (TATs) for cancer, routine and inpatient referrals are tracked as key metrics for each modality and site allowing patient waiting times to be proactively managed.
*Results from case studies are not predictive of results in other cases. Results in other cases may vary.
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