Outcomes of aortic aneurysm surgery in England: a nationwide cohort study using hospital admissions data from 2002 to 2015

• Main Authors: Ahmed Aber (Author), Thaison Tong (Author), Jim Chilcott (Author), Ravi Maheswaran (Author), Steven M. Thomas (Author), Shah Nawaz (Author), Jonathan Michaels (Author)
• Format: Book
• Published: BMC, 2019-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12913-019-4755-0; 1472-6963
• Keywords: Aortic aneurysm; Administrative dataset; Outcomes; Hospital episode statistics; Public aspects of medicine; RA1-1270
• Source: BMC Health Services Research, Vol 19, Iss 1, Pp 1-17 (2019)

Abstract Background The United Kingdom aortic aneurysms (AA) services have undergone reconfiguration to improve outcomes. The National Health Service collects data on all hospital admissions in England. The complex administrative datasets generated have the potential to be used to monitor activity and outcomes, however, there are challenges in using these data as they are primarily collected for administrative purposes. The aim of this study was to develop standardised algorithms with the support of a clinical consensus group to identify all AA activity, classify the AA management into clinically meaningful case mix groups and define outcome measures that could be used to compare outcomes among AA service providers. Methods In-patient data about aortic aneurysm (AA) admissions from the 2002/03 to 2014/15 were acquired. A stepwise approach, with input from a clinical consensus group, was used to identify relevant cases. The data is primarily coded into episodes, these were amalgamated to identify admissions; admissions were linked to understand patient pathways and index admissions. Cases were then divided into case-mix groups based upon examination of individually sampled and aggregate data. Consistent measures of outcome were developed, including length of stay, complications within the index admission, post-operative mortality and re-admission. Results Several issues were identified in the dataset including potential conflict in identifying emergency and elective cases and potential confusion if an inappropriate admission definition is used. Ninety six thousand seven hundred thirty-five patients were identified using the algorithms developed in this study to extract AA cases from Hospital episode statistics. From 2002 to 2015, 83,968 patients (87% of all cases identified) underwent repair for AA and 12,767 patients (13% of all cases identified) died in hospital without any AA repair. Six thousand three hundred twenty-nine patients (7.5%) had repair for complex AA and 77,639 (92.5%) had repair for infra-renal AA. Conclusion The proposed methods define homogeneous clinical groups and outcomes by combining administrative codes in the data. These methodologically robust methods can help examine outcomes associated with previous and current service provisions and aid future reconfiguration of aortic aneurysm surgery services.