Around one million major operations take place in the National Health Service (NHS) each year. One in five patients experience complications, increasing their risk of a longer hospital stay, being re-admitted after discharge home, not returning to their baseline independence, and early death. Additionally, complications lead to increased NHS costs and resource use.
Significant public resources are used to try to better understand the long-term effects of surgery. Clinicians must measure and manually record information about patients' health, quality of care and what happens to them after their hospital stay. Much of this information already exists somewhere within the NHS, in electronic health records held by general practitioners (GPs) or in the routine data collected in hospitals. However, this data is not routinely shared, thus duplicating effort and potentially wasting NHS resources.
Combining patient data from hospitals and GPs in England will provide a more complete picture of the journey undertaken by patients undergoing major surgery. This will improve our understanding of the scale and type of complications occurring after surgery, which patients are more at risk, and whether this affects where and how often they access healthcare. This should help patients and healthcare professionals make better plans together to reduce these risks. Using linked data in this way may reduce the burden of data collection on local hospitals, so contributing to improved patient care and saving NHS resources.
Occurring in 20% of adults undergoing major surgery, perioperative complications have important implications for patients and the NHS: increased healthcare resource utilisation (HCRU); reduced quality of life; reduced long-term survival. Collecting patient data on postoperative complications is burdensome and costly. The Hospital Episode Statistics (HES) coding system does not differentiate between pre-existing comorbidities and complications sustained during a hospital episode. Furthermore, little is known about the prevalence, magnitude and cost of complications which develop or continue after discharge from hospital and are managed in primary care.
This retrospective cohort study will use HES-linked CPRD data to determine the feasibility of using linked data to identify HES discharge diagnoses not present pre-operatively within HES or CPRD, thereby identifying complications. Adult patients undergoing major surgery between 2008 to 2018 will be selected within HES using pre-defined procedure codes. We will develop clinical phenotyping algorithms to discover patients within the CPRD Aurum database who experienced complications within 30 days of surgery. Multivariable Cox proportional hazard models will be used to estimate hazard ratios for the associations between pre-existing co-morbidities, post-operative complications and HCRU. Using a cost-of-illness approach, we will investigate the trajectory, magnitude and determinants of HCRU before and after surgery, and ascertain the patient risk factors that have the greatest impact on different outcomes. We will attempt to validate our methods using a separate group of patients from the CPRD GOLD database.
Achieving a more complete overview of the perioperative pathway using linked patient records could not only improve knowledge, but also reduce the burden of data collection on the NHS therefore saving time, resources and money.
Surgical complications presenting to primary or secondary care; Inpatient length of stay; Number of primary and secondary care interactions in the 12 months preceding and the 12 months after discharge from hospital following the index surgical procedure; Frequency of GP consultations; Admission to hospital; Outpatient department attendance; Attendance at Accident & Emergency; Number of surgical procedures and diagnostic tests; Prescriptions issued in primary care; All-cause mortality.
Dermot McGuckin - Chief Investigator - University College London ( UCL )
Dermot McGuckin - Corresponding Applicant - University College London ( UCL )
Charles Oliver - Collaborator - University College London ( UCL )
Kate Walker - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Melanie Morris - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Snehal Pinto Pereira - Collaborator - University College London ( UCL )
Suneetha Ramani Moonesinghe - Collaborator - University College London ( UCL )
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation