Vascular Society VBHOM, a data economic model for predicting the outcome after open abdominal aortic aneurysm surgery T. Tang 1 , S. R. Walsh 1 , D. R. Prytherch 2 , T. Lees 3 , K. Varty 1 and J. R. Boyle 1 , in Association with the Audit and Research Committee of the Vascular Society of Great Britain and Ireland 1 Regional Vascular Unit, Cambridge University Hospital NHS Foundation Trust, Cambridge, 2 Centre for Healthcare Modelling and Informatics, School of Computing, University of Portsmouth, Portsmouth, and 3 Northern Vascular Centre, Freeman Hospital, Newcastle upon Tyne, UK Correspondence to: Mr J. R. Boyle, Regional Vascular Unit, Box 201, Level 7, Cambridge University Hospital NHS Foundation Trust, Hills Road, Cambridge CB2 2QQ, UK (e-mail: jonboyle@doctors.org.uk) Background: Vascular Biochemistry and Haematology Outcome Models (VBHOM) adopted the approach of using a minimum data set to model outcome. This study aimed to test such a model on a cohort of patients undergoing open elective and non-elective abdominal aortic aneurysm (AAA) repair. Methods: A binary logistic regression model of risk of in-hospital mortality was built from the 2002 – 2004 submission to the UK National Vascular Database (NVD) (2718 patients). The subset of NVD data items used comprised serum levels of urea, sodium and potassium, haemoglobin, white cell count, sex, age and mode of admission. The model was applied prospectively using Hosmer–Lemeshow methodology to a test data set from the Cambridge Vascular Unit. Results: The validation set contained 327 patients, of whom 208 had elective AAA repair and 119 had emergency repair of a ruptured AAA. Outcome following elective and non-elective AAA repair could be described accurately using the same model. The overall mean predicted risk of death was 14·13 per cent, and 48 deaths were predicted. The actual number of deaths was 53 (χ 2 = 8·40, 10 d.f., P = 0·590; no evidence of lack of fit). The model also demonstrated good discrimination (c-index = 0·852). Conclusion: The VBHOM approach has the advantage of using simple, objective clinical data that are easy to collect routinely. The VBHOM data items potentially allow prediction of risk in an individual patient before aneurysm surgery. Paper accepted 23 April 2007 Published online in Wiley InterScience (www.bjs.co.uk). DOI: 10.1002/bjs.5808 Introduction Clinical governance and professional revalidation has made the entire healthcare profession, especially surgeons, increasingly accountable to their patients, professional organizations and employing hospital trusts. Vascular surgeons operate on difficult and complex cases. The UK National Vascular Database (NVD) 1 was set up not only to meet these challenges but also to compare vascular surgical performance in a fair and robust manner. Data items collected for the NVD are predominantly based on the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) data set 2 , and include additional vascular procedure-specific items. A major drawback of the NVD has been the large number of data items required. The logistics associated with collecting such a large data set have undoubtedly been one of the factors inhibiting its universal adoption by vascular surgeons. The POSSUM approach requires collection of up to 12 preoperative physiological and six operative variables per patient 2 . Furthermore, some of the data required are subjective and are not necessarily required as part of routine clinical care. Copeland and colleagues 2 have argued that all hospitals within the UK have the ability to collect the POSSUM data set without difficulty, but in practice it requires considerable effort, commitment and understanding, and effective information technology support. Difficulties in the application of POSSUM have been reported 3 . Another problem encountered with the POSSUM models is that they require operative variables, and are not suitable for Copyright  2007 British Journal of Surgery Society Ltd British Journal of Surgery 2007; 94: 717–721 Published by John Wiley & Sons Ltd