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Use of diagnostic information submitted to the United Kingdom Central Cardiac Audit Database: development of categorisation and allocation algorithms

Published online by Cambridge University Press:  02 October 2012

Kate L. Brown*
Affiliation:
Cardiac Unit, Great Ormond Street Hospital NHS Trust, London, United Kingdom
Sonya Crowe
Affiliation:
Clinical Operational Research Unit, University College London, London, United Kingdom
Christina Pagel
Affiliation:
Clinical Operational Research Unit, University College London, London, United Kingdom
Catherine Bull
Affiliation:
Cardiac Unit, Great Ormond Street Hospital NHS Trust, London, United Kingdom
Nagarajan Muthialu
Affiliation:
Cardiac Unit, Great Ormond Street Hospital NHS Trust, London, United Kingdom
John Gibbs
Affiliation:
National Institute Cardiovascular Outcomes Research, Central Cardiac Audit Database, University College London, London, United Kingdom
David Cunningham
Affiliation:
National Institute Cardiovascular Outcomes Research, Central Cardiac Audit Database, University College London, London, United Kingdom
Martin Utley
Affiliation:
Clinical Operational Research Unit, University College London, London, United Kingdom
Victor T. Tsang
Affiliation:
Cardiac Unit, Great Ormond Street Hospital NHS Trust, London, United Kingdom
Rodney Franklin
Affiliation:
Paediatric Cardiology, Royal Brompton and Harefield Hospitals, London, United Kingdom
*
Correspondence to: Dr K. L. Brown, Consultant, Cardiac Unit, Great Ormond Street Hospital NHS Trust, London WC1N 3JH, United Kingdom. Tel: +44 207 813 8180; Fax: +44 207 829 8673; E-mail: brownk@gosh.nhs.uk

Abstract

Objective

To categorise records according to primary cardiac diagnosis in the United Kingdom Central Cardiac Audit Database in order to add this information to a risk adjustment model for paediatric cardiac surgery.

Design

Codes from the International Paediatric Congenital Cardiac Code were mapped to recognisable primary cardiac diagnosis groupings, allocated using a hierarchy and less refined diagnosis groups, based on the number of functional ventricles and presence of aortic obstruction.

Setting

A National Clinical Audit Database.

Patients

Children undergoing cardiac interventions: the proportions for each diagnosis scheme are presented for 13,551 first patient surgical episodes since 2004.

Results

In Scheme 1, the most prevalent diagnoses nationally were ventricular septal defect (13%), patent ductus arteriosus (10.4%), and tetralogy of Fallot (9.5%). In Scheme 2, the prevalence of a biventricular heart without aortic obstruction was 64.2% and with aortic obstruction was 14.1%; the prevalence of a functionally univentricular heart without aortic obstruction was 4.3% and with aortic obstruction was 4.7%; the prevalence of unknown (ambiguous) number of ventricles was 8.4%; and the prevalence of acquired heart disease only was 2.2%. Diagnostic groups added to procedural information: of the 17% of all operations classed as “not a specific procedure”, 97.1% had a diagnosis identified in Scheme 1 and 97.2% in Scheme 2.

Conclusions

Diagnostic information adds to surgical procedural data when the complexity of case mix is analysed in a national database. These diagnostic categorisation schemes may be used for future investigation of the frequency of conditions and evaluation of long-term outcome over a series of procedures.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2012 

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