Intervention to optimize guideline-recommended interdependent care delivery in breast and lung cancers with the 4R Oncology model.

Abstract

34 Background: Team-based care improves quality, reduces fragmentation and lowers clinician burnout related to ad hoc care coordination. A key teamwork principle is managing timing and sequence of interdependent care (Vogel JOP 2016). The 4R Oncology model featured by the NCI ASCO Teams initiative fosters effective teamwork by facilitating systematic timing / sequence of interdependent care.1 4R is Right Info / Care / Patient / Time. Using a 4R intervention, a large health system created a high-functioning care team and conducted optimizations of guideline-based interdependent care in breast and lung cancers Oct 2020 - Dec 2021.2 We present results of these optimizations. Methods: We compared data from electronic health record on timing and sequence of care between historical control cohorts of patients who received care pre-4R (breast n=274, lung n=173) to the post-optimization 4R cohorts (breast n=211, lung n=140). Patient and tumor characteristics between control and 4R cohorts in both cancers were similar. Results: Timing and sequence of care for 6 of the 7 breast cancer metrics and all 7 lung cancer metrics was significantly improved between the control and 4R cohorts (Table). Despite significant increase, the rate of timely care for some metrics remained low, such as referrals based on distress screening in breast cancer and palliative care consult in lung cancer. Conclusions: The 4R Oncology model is effective in applying teamwork principles and improving timing and sequence of guideline-based care. Opportunities for further care optimizations exist to expand the 4R benefit to a higher number of patients. A learning system established in our institution will inform iterative optimizations. 1. Trosman JOP 2016. 2. Liu JCOOP 2022. [Table: see text]