Abstract
BackgroundThe 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.MethodsIn-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.ResultsSeveral 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.ConclusionThe 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.
Highlights
The United Kingdom aortic aneurysms (AA) services have undergone reconfiguration to improve outcomes
Developing case mix groups The development of the case-mix groups was based on the anatomy of the AA disease, admission method, ruptured vs intact AA, type of the procedure, and a subgroup of patients dying in-hospital from AA with no previous AA operation
Admission method in Hospital Episode Statistics (HES) data defines elective and emergency admissions, OPCS codes differentiate between elective and emergency procedures (See Tables 11-15 in Appendix 2) and ICD-10 codes can describe whether AA is intact or ruptured (See Tables 16-17 in Appendix 2)
Summary
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 United Kingdom had the highest mortality rate for the elective repair of aortic aneurysms (AA) compared to other western European countries in 2007 (7.9% UK vs 3.5% Europe) [1] Improvement of outcomes such as postoperative mortality following AA repair was a major drive for vascular services reconfiguration in the National Health Service (NHS). The basic unit of activity measured in HES is the finished consultant episode (FCE) This is a single period of care under one consultant and does not necessarily equate to a single hospital admission, which may comprise more than one episode if care is transferred between consultants or providers. FCEs include information such as patient demographics, type of admission, source of admission as well as length of stay in critical care and other important clinical and administrative information
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