SESSION TITLE: Lung Cancer Screening & Diagnosis Posters
SESSION TYPE: Original Investigation Poster
PRESENTED ON: Wednesday, October 28, 2015 at 01:30 PM - 02:30 PM
PURPOSE: The incidence of lung cancer is increasing. A large numbers of patients are seen in clinic and discharged at first visit with a normal Computerised Tomography (CT) scan. This has an impact on clinic waiting times. We implemented a pathway in 2013 of an abnormal CT triggering a referral to Lung cancer clinic rather than an abnormal chest X-ray (CXR).
METHODS: We reviewed all Lung cancer clinic referrals and assessed the impact of change in the pathway comparing 2012 and 2014. Dates of CXR, CT scan and clinic reviews were noted. CXR and CT reports were used to identify abnormality and MDT discussions/biopsy results considered for diagnosis. We analysed the access times which was calculated as the time from an abnormal chest X-ray to clinic review. We also analysed the conversion rates defined as a percentage of abnormal CXRs diagnosed as cancer.
RESULTS: In 2012, there were 611 referrals with 29% (n=182) diagnosed as cancer with a median access time of 20 days to clinic review. The conversion rate was 35.2%. In 2014 there were 439 referrals with 38% (n=169) diagnosed as cancer. The median access time was reduced to 18 days. There was an added advantage of increased conversion rate of 47.7%. There was a 28% reduction in the number of clinic referrals after the change in pathway. There was a 12% increase in the conversion rates.
CONCLUSIONS: We were able to demonstrate reduction in access times, anxiety and numbers reviewed in the clinic. This has also led to a reduction in the clinic waiting time’s thereby providing service efficiency and cost savings.
CLINICAL IMPLICATIONS: Implementing pathways with appropriate criteria can reduce clinic waiting times, lead to early diagnosis and enables more efficient use of resources.
DISCLOSURE: The following authors have nothing to disclose: Jayanth Bhat, Javed Ibrahim, Subashini Chandrapalan, Ashwin Rajhan, Nick Watson, Imran Hussain
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