The number of patients with more than one long-term health condition needing surgery are increasing in the NHS; for example, a patient with cancer who also has diabetes and heart disease. This is called having multiple long-term health conditions (MTLC) and it can make having surgery more complicated. Since it affects 1-in-3 patients undergoing surgery, who come from diverse backgrounds and communities, caring for them should be a focus for all healthcare professionals, including surgical teams. Using surgical encounters, both surgical disease and MLTC can be addressed efficiently.
However, at present, we do not know how common MLTC is in patients undergoing surgery, and what conditions group together. Further, we do not have information on the outcomes of these patients’ undergoing surgery. To do this we will study a group of people who have surgery and MTLC. By linking data from primary care to hospital and mortality data we can see how these groups of conditions group together and whether people with different groups of conditions do better or worse after surgery. This research will help us make better plans to improve outcomes in people with MLTC undergoing surgery. This will benefit people with MTLC and may reduce the cost of surgical complications to the NHS.
The presence of multiple long-term conditions (MLTC) is a growing problem in the NHS. Early data suggests one of three patients undergoing surgery, who come from diverse backgrounds and communities, have MLTC. Therefore, caring for them should be a focus for all healthcare professionals, including surgical teams. Using surgical encounters, both surgical disease and MLTC can be addressed efficiently.
Over the past decade, research into MLTC has come from primary care defining epidemiology and clusters of disease across all patients in the NHS. However, the prevalence of MLTC and individual long-term health conditions in patients undergoing surgery compared to those not undergoing surgery are unclear. Further, there is no data characterising the impact of surgery in the trajectory of patients living with MLTC. Therefore, as surgeons, we do not have a good understanding of the exact scale of problem to better improve health and care for our patients.
This study aims to understand the prevalence and clusters of multimorbidity in patients undergoing surgery across the UK compared to those not undergoing surgery in the population. We will describe the epidemiology of pre-existing multimorbidity in patients undergoing surgery, multimorbidity clusters, investigate the association of multimorbidity with surgical outcomes and healthcare utilisation in primary and secondary care data.
The primary analysis is the prevalence and patterns of pre-existing MLTC in patients undergoing surgery compared to those not undergoing surgery. The secondary analysis include pre-existing MLTC in patients undergoing surgery stratified by the urgency (i.e., elective or emergency) and indication (i.e., benign or malignant) of surgery. The denominator was the total number of index surgeries. We will describe the MLTC pattern by counts, common combinations and by undertaking unsupervised cluster analysis (i.e., latent class cluster analysis) to determine characteristics and outcomes of patients in these clusters.
> Primary: 30-day mortality
> Secondary: Readmission rates at 30-days, Development of further health conditions.
Sivesh Kathir Kamarajah - Chief Investigator - University of Birmingham
Sivesh Kathir Kamarajah - Corresponding Applicant - University of Birmingham
Francesca Crowe - Collaborator - University of Birmingham
Krishna Gokhale - Collaborator - University of Birmingham
Krishnarajah Nirantharakumar - Collaborator - University of Birmingham
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation