Grading our quality: An academic and community cancer center dashboard.

Abstract

303 Background: Quality scorecards provide a high-level view of key performance metrics and guide data-driven decision making. Dashboards specific to cancer care have not been widely published. Our goal was to implement a quality dashboard to guide and monitor local improvement efforts at an academic and community cancer center. Methods: With the leadership of a Project Manager and Nursing and Physician Quality Directors of the Cancer Center, and input of key Cancer Center stakeholders, quality metrics across national organizations were evaluated. Metrics were chosen based on their ease of collection and their mapping to institutional priorities of clinical quality, patient safety, access, and financial stability. Additional internal measures and benchmarks were created to capture local improvement efforts. Numerous internal and third-party databases were accessed to extract, analyze and display our data. Additionally, a data dictionary was developed for the measure set. Results: Six months of data from fiscal year 2022 was collected, analyzed, and displayed on 10 core and 3 disease-specific measures for breast (B) and lung (L) cancers. (Breast and lung). As of 5/2022, the measures presented on the dashboard include new patient access, non-template chemotherapy orders, medication harm events, likelihood of recommending practice, preventable admissions and emergency department visits, inpatient mortality, and length of stay, readmission, survivorship care plan (B), return to operating room (L), and adequate lymph node sampling (L). These measures pertain to several of the Institute of Medicine’s domains of healthcare quality: effective, efficient, patient-centered, safe, and timely. Conclusions: Compiling data from multiple sources into a single dashboard may guide Cancer Center leadership in strategic planning and monitoring improvement for ongoing initiatives. The data will be updated quarterly. Future iterations will include more disease specific measures and attempts to build automatic data extraction.