Abstract

229 Background: While clinical guidelines for non-small cell lung cancer (NSCLC) provide recommendations on individual components of care and advocate multidisciplinary collaboration, guidance spanning the complete patient journey is lacking. We aimed to compile quality-focused recommendations for the multidisciplinary team and selected clinical criteria for ideal NSCLC care, and propose a new set of metrics encompassing the entire care continuum. These metrics would be used as a new benchmark for ideal NSCLC care via the Association of Community Cancer Centers’ (ACCC) national quality care initiative for patients with advanced (stage III/IV) NSCLC. Methods: The ACCC convened an expert steering committee of multidisciplinary specialists and representation from patient advocacy to compile evidence-based recommendations via a systematic search of clinical and quality care guidelines and peer-reviewed journals. Quality recommendations were organized within key care areas of the patient journey: care coordination and patient education, diagnosis and biomarker testing, staging and treatment planning, and survivorship. Results: A total of 32 recommendations were included across the 4 key NSCLC care areas. Key quality recommendations are listed (Table). Conclusions: The full set of recommendations define ideal NSCLC care and serve as a valuable guide for multidisciplinary practice and quality improvement initiatives. [Table: see text]

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.