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Pre‐treatment wait time for head and neck cancer patients in Western Australia: description of a new metric and examination of predictive factors
Author(s) -
Flukes Stephanie,
Garry Stephen,
HintonBayre Anton,
Lindsay Andrew
Publication year - 2018
Publication title -
anz journal of surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.426
H-Index - 70
eISSN - 1445-2197
pISSN - 1445-1433
DOI - 10.1111/ans.14860
Subject(s) - medicine , referral , head and neck cancer , biopsy , retrospective cohort study , tertiary referral centre , radiation therapy , cancer , head and neck , metric (unit) , surgery , radiology , family medicine , economics , operations management
Background Prolonged pre‐treatment wait times in head and neck cancer are associated with increased morbidity and reduced survival. Traditional metrics exclude delays prior to biopsy, which represents an important and measurable period of time. This study aims to describe total wait time for head and neck cancer patients in our institution, to define a more accurate representation of the clinically relevant pre‐treatment wait time, and to evaluate predictive factors for prolonged wait times. Methods A retrospective review of head and neck cancer patients treated over 2 years in a tertiary referral centre was conducted. Patient demographics, referral symptoms, tumour details, treatment plan and key dates were analysed to identify total wait time and factors predictive of increased wait time. Results Two hundred and ninety‐four patients were included. Mean total wait time from initial referral to treatment initiation was 71.6 (median 61) days. The period from referral to biopsy represented 29% of mean total wait time. Factors predictive of increased wait time included presenting symptom of hoarseness, laryngeal cancer and treatment with definitive radiotherapy. Conclusions This study demonstrates that time from referral to biopsy represents a significant portion of total wait time, and we suggest that this be incorporated into future wait time metrics for improved clinical relevance. Furthermore, we have identified factors predicting increased wait time which can be targeted for future service improvement.