1109 - Pre-Treatment Diagnostic and Staging Efficiency in Patients with Non-Small Cell Lung Cancer (NSCLC): A Systems Operations Audit in an Integrated Health System
Presenter(s)
P. Mohindra1,2, R. K. Kyasaram3, L. Chiec4,5, A. Baydoun1,2, A. Gupta5,6, R. Gilkeson5,6, F. Jacono5,7, B. Young5,7, P. A. Linden5,8, and J. Shanahan3; 1Department of Radiation Oncology, University Hospitals Cleveland Medical Center/ Seidman Cancer Center, Cleveland, OH, 2Case Western Reserve University, Cleveland, OH, 3Cancer Informatics, University Hospitals Cleveland Medical Center/ Seidman Cancer Center, Cleveland, OH, 4Division of Medical Oncology, University Hospitals Cleveland Medical Center/ Seidman Cancer Center,, Cleveland, OH, 5Case Western Reserve University School of Medicine, Cleveland, OH, 6Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, 7Division of Pulmonology, University Hospitals Cleveland Medical Center, Cleveland, OH, 8Division of Thoracic and Esophageal Surgery, University Hospitals Cleveland Medical Center, Cleveland, OH
Purpose/Objective(s):
Timely completion of diagnostics is essential to initiate curative-intent therapy for patients with NSCLC. In real-world health systems, referral and scheduling frictions create unrecognized delays impacting downstream service-lines including radiation oncology (RO). We seek to measure system-wide diagnostic and staging efficiency, with the objective to establish benchmarks, and to inform continuous quality improvement in access to care across diverse care settings.Materials/Methods:
A systems operations analysis (2024–2025) was performed for stage II–III NSCLC patients within an NCCN-member integrated health system with mix of academic and community sites. Data were abstracted via cancer informatics–driven queries across the cancer registry, the EPIC, Mosaiq® and Medlever, Inc. systems. Informatics-led data query was chosen to enable creation of an efficient, reproducible, system-wide dashboard, recognizing the expected noise inherent to large operational datasets. Descriptive analyses are reported to summarize patient demographics; intervals from first specialty visit to diagnostic and staging testing; test-to-treatment intervals; and inter-specialty referral pathways.Results:
We identified 197 patients with stage II–III NSCLC. After excluding patients not treated at our institution, the final analytic cohort included N=170 (median age 70 [44–90]; predominantly males [55%] and white [83%]). At diagnosis, 13.5% patients were hospitalized. Overall diagnostic workup completion rates were high (81-92%), but completion rates within 45 days of the first visit were low (28-42%) (Table 1). Within the thoracic multidisciplinary team, initial specialty visit was under pulmonology (63.5%), thoracic surgery (19%), medical oncology (16%), RO (2%). Within the cohort first seen by pulmonology, 64% of those had a subsequent treatment-specialist visit within 100 days (median 29 days [1–84]). The initial treatment received was systemic therapy (51%), surgery (36%), and radiation (12%).Conclusion:
In a large, real-world setting of an NCCN-member integrated health system, patients with stage II–III NSCLC experienced diagnostic/staging testing delays clustered around MRI scheduling (median 49 days from first visit) and post-PET/bronchoscopy transition to treatment delays (median ~40 days). These patterns illustrate common operational challenges in complex healthcare environments, with direct impact on time to RO referrals and underscore the value of routine system audits to surface actionable bottlenecks. Table 1: Diagnostic/Staging efficiency *Median intervals shown for those with the test within 200 days of first specialty visit.| Test | Ever obtained (% of N=170) | Tests =45 days: N (%) | First visit to Test: Median days (range)* | Test to treatment: Median days (range)* |
| PET-CT | 92% | 53 (31%) | 28 (1–199) | 41 (5–190) |
| Brain MRI | 84% | 47 (28%) | 49 (1–194) | 26 (1–160) |
| Bronchoscopy (±EBUS) | 81% | 72 (42%) | 29 (1–197) | 40 (2–182) |
| Molecular testing | 88% | 70 (41%) | 38 (2–189) | 28 (2–173) |