Abstract
We describe a risk adjustment algorithm to benchmark and report free flap failure
rates after immediate reconstruction of head and neck defects. A dataset of surgical
care episodes for curative surgery for head and neck cancer and immediate reconstruction
(n = 1593) was compiled from multiple NHS hospitals (n = 8). The outcome variable
was complete flap failure. Classification models using preoperative patient demographic
data, operation data, functional status data and tumour stage data, were built. Machine
learning processes are described to model free flap failure. Overall complete flap
failure was uncommon (4.7%) with a non-statistical difference seen between hospitals.
The champion predictive model had acceptable discrimination (AUROC 0.66). This model
was used to risk-adjust cumulative sum (CuSUM) charts. The use of CuSUM charts is
a viable way to monitor in a ‘Live Dashboard’ this quality metric as part of the quality
outcomes in oral and maxillofacial surgery audit.
Keywords
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Article info
Publication history
Published online: September 29, 2022
Accepted:
September 22,
2022
Received in revised form:
September 20,
2022
Received:
August 17,
2022
Identification
Copyright
Crown Copyright © 2022 Published by Elsevier Ltd on behalf of The British Association of Oral and Maxillofacial Surgeons. All rights reserved.
