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Pragmatic approach to quality metrics development in cancer.
Abstracts that were granted an exception in accordance with ASCO's Conflict of Interest Policy are designated with a caret symbol (^).
Background: London Cancer aims to use transparency of service and quality measures to drive improvement in cancer care in North and East London and surrounding areas, serving our population of 3.5m people. Whilst the on-going implementation of the National Outcome and Service Dataset for UK is expected to take 18 months we have chosen to develop quality measures with the teams accountable to deliver the service by using available data from a variety of existent sources and illustrate this in value scorecards tracking the patient pathway. Methods: Building on an engagement exercise with patients, clinicians and charities in 2011 to identify which outcomes mattered most to patients, a small set of key pathways metrics was identified for each site specific cancer pathway board to monitor their progress in implementing integrated cancer care. Metrics were selected only if (a) clinically useful, in line with the current work plan and improvement effort; (b) accessible on a recurrent basis and requiring minimal manual effort; (c) facilitate the understanding of the patient pathway; (d) align with London Cancer objectives in improving survival, patient experience, and access to innovation and clinical trials. Pathway boards were invited to contribute with the intention to provide a pathway metrics value scorecards on a quarterly basis. Results: The first set pathway metrics scorecards, with 31 metrics, were published by June 2013. Key items include adherence to established best practice (16), data completeness (6), survival (3), pathway efficiency (3), and patient experience (3). Conclusions: Pathway metrics are reported at a system level, reflecting the care for our local population, against measures that are important to them and will allow visibility of success. Whilst current pathway metric development is limited by the availability of meaningful data we aim to build on the existing metrics in an iterative fashion. For this we are working with stakeholders to improve data quality.