Introduction: The average age of patients presenting to healthcare services with complex arrythmias needing intervention is increasing. With the average life span of a pacemaker generator ranging from 5 to 12 years, this often means that these already older patients have become even older with complex comorbidities and frailty by the time the device goes into elective replacement indicator (ERI). Questions subsequently arise about what happens when these generators reach ERI and need changing in these patient groups. This led us to develop an initiative using Plan-Do-Study-Act (PDSA) cycles to come up with a pathway for frail older patients who are being considered for pacemaker generator change. The focus is to provide efficient, consistent, patient-centered care and to ensure a multidisciplinary team (MDT) approach is embedded.
Methods: Multiple PDSA cycles were utilised at Sheffield Teaching Hospitals NHS Foundation Trust. The pathway devised was a traffic light system incorporating the Clinical Frailty Scale (CFS) as well as the indication for a pacemaker. Patient were stratified by their procedural risk (CFS) and indication risk. Patients with a low CFS and high indication were deemed green and therefore went straight to generator change. Patients with a moderate CFS and intermediate indication were deemed amber and went for MDT discussion. Patients with a high CFS and a low indication were deemed red and also went on to have an MDT discussion (see Figure for algorithm).
Results: The results, at 1 year, were that patients with moderate and high clinical frailty were all discussed at an MDT meeting, with 56% going on to have a review and further in-depth discussion around best interest decisions with the patient and their next of kin. Overall, 65% of patients had a change in management. The average CFS of patients on the pathway was 6 (amber on the pathway). This is where people need help with all outside activities and with keeping house. Inside, they often have problems with stairs and need help with bathing and might need minimal assistance (cueing, standby) with dressing. When compared with generator changes in 2018, the pathway did not increase admission rates or mortality. All-cause mortality was 9% for both datasets. Qualitative data showed that professionals and patients were supportive of the pathway. Other learning points included how to facilitate service development across multiple specialties.
Conclusions: The pathway appeared to work well and altered the outcomes for patients and facilitated discussions around future care. We can infer from the data that the pathway does not increase readmission rates or mortality. Further data are needed to conclude whether the pathway reduces readmission rates and whether further statistical significance can be given to the CFS score and the ultimate outcomes decided. ❑