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Using low-dose computed tomography (LDCT) to screen for lung cancer is associated with improved outcomes among eligible current and former smokers (ie, aged 55-77, at least 30-pack–year smoking history, current smoker or former smoker who quit within the past 15 years). However, the overall uptake of LDCT is low, especially in health care settings with limited personnel and financial resources. To increase access to lung cancer screening services, the American Cancer Society partnered with 2 federally qualified health centers (FQHCs) in Tennessee and West Virginia to conduct a pilot project focused on developing and refining the LDCT screening referral processes and practices. Each FQHC was required to partner with an American College of Radiology–designated lung cancer screening center in its area to ensure high-quality patient care. The pilot project was conducted in 2 phases: 6 months of capacity building (January–June 2016) followed by 2 years of implementation (July 2016–June 2018). One site created a sustainable LDCT referral program, and the other site encountered numerous barriers and failed to overcome them. This case study highlights implementation barriers and factors associated with success and improved outcomes in LDCT screening. [ABSTRACT FROM AUTHOR]

Background: As evidence guides practice, it is essential for navigation programs to identify core metrics and standardize data collection to demonstrate program outcomes. Evidence supports that there is a need for heterogeneity with navigation measurements.1 Through extensive literature review, 3 main areas of measurements have been defined: Patient Experience, Clinical Outcomes, and Return on Investment metrics.2 To advance the field toward the goal of standardized metrics, a team from the Academy of Oncology Nurse & Patient Navigators (AONN+), the American Cancer Society, and The Chartis Group, Chartis Oncology Solutions Practice, conducted a pilot study to assess the extent to which navigation programs could implement 10 of the 35 AONN+ national evidence-based metrics, with the goal of validating these metrics and establishing benchmarks. The following metrics were included in the study: barriers to care, time to initial treatment, navigation caseload, hospital readmissions, distress screenings, social support referrals, palliative care referrals, learning style preference, navigator competencies, and patient satisfaction with care. Objectives: * Implement and validate navigation metrics * Identify common barriers and challenges to metric measurement, strategies for overcoming them, and measurement best practices and lessons learned * Develop a Navigation Metrics Implementation Tool Kit based on study findings Methods: Using a mixed methods approach, the study team selected 8 sites to collect the metrics over a 6-month period. Metrics data were uploaded into the ONQiQ NAVmetrics cloud-based IT platform to create site-specific dashboards. Prior to study launch, sites also submitted 3 years of historical data on these metrics, as available. The team also collected qualitative data on facilitators and barriers to metrics tracking by observing monthly calls between each site and the study team, pre/post key informant interviews, and documentation of quality improvement (QI) activities. Results: Across 8 sites, a total of 64 navigators participated, averaging 45 hours per week; 59.3% of time on patient-directed interventions and 40.7% on administrative activities; 4462 navigated patients who equate 53% of abstracted cases. Metrics outcomes summary: 88 cases per navigator; 2.2 barriers per patient; 10.4% readmission rate; 42% of patients received distress screening; 0.4 social support referrals per patient; 0.2 palliative care referrals per patient; 0.7 learning styles per patient identified; and 6% of patients completed a satisfaction survey. Barriers and challenges to metrics implementation: IT challenges, electronic medical record data capture and standardization, health system barriers, unstandardized navigation processes or defined scope, and unclear metric definitions. Each study site completed at least 1 QI activity to improve their implementation of the metrics. Most QI activities focused on distress screening and palliative care referrals. Conclusion: Of the 10 metrics, 5 were found to be core metrics that were applicable across sites: navigator competencies, navigation caseload, barriers to care, psychosocial distress screening, and social support referrals. Involving navigators earlier in the care continuum had a positive effect on barrier assessment, diagnosis to treatment, and social support referrals. Programs faced challenges with metrics implementation and struggled to de- fine processes for data capture and reporting. Continued research around navigation metrics will be vitally important to ensure sustainability of navigation programs. [ABSTRACT FROM AUTHOR]