Effect of Patient Navigation on Completion of Lung Cancer Screening in Vulnerable Populations.

BACKGROUND: Although low-dose, CT-based lung cancer screening (LCS) can decrease lung cancer mortality in high-risk individuals, the process may be complex and pose challenges to patients, particularly those from minority underinsured and uninsured populations. We conducted a randomized controlled trial of telephone-based navigation for LCS within an integrated, urban, safety-net health care system. PATIENTS AND METHODS: Patients eligible for LCS were randomized (1:1) to usual care with or without navigation at Parkland Health in Dallas, Texas. The primary endpoint was completion of the first 3 consecutive steps in a patient's LCS process. We explored differences in completion of LCS steps between navigation and usual care groups, controlling for patient characteristics using the chi-square test. RESULTS: Patients (N=447) were randomized to either navigation (n=225) or usual care (n=222). Mean patient age was 62 years, 46% were female, and 69% were racial/ethnic minorities. There was no difference in completion of the first 3 steps of the LCS algorithm between arms (12% vs 9%, respectively; P=.30). For ordered LCS steps, completion rates were higher among patients who received navigation (86% vs 79%; P=.03). The primary reason for step noncompletion was lack of order placement. CONCLUSIONS: In this study, lack of order placement was a key reason for incomplete LCS steps. When orders were placed, patients who received navigation had higher rates of completion. Clinical team education and enhanced electronic health record processes to simplify order placement, coupled with patient navigation, may improve LCS in safety-net health care systems.

Geographic Accessibility and Completion of Initial Low-Dose CT-Based Lung Cancer Screening in an Urban Safety-Net Population.

BACKGROUND: Recent modifications to low-dose CT (LDCT)-based lung cancer screening guidelines increase the number of eligible individuals, particularly among racial and ethnic minorities. Because these populations disproportionately live in metropolitan areas, we analyzed the association between travel time and initial LDCT completion within an integrated, urban safety-net health care system. METHODS: Using Esri's StreetMap Premium, OpenStreetMap, and the r5r package in R, we determined projected private vehicle and public transportation travel times between patient residence and the screening facility for LDCT ordered in March 2017 through December 2022 at Parkland Memorial Hospital in Dallas, Texas. We characterized associations between travel time and LDCT completion in univariable and multivariable analyses. We tested these associations in a simulation of 10,000 permutations of private vehicle and public transportation distribution. RESULTS: A total of 2,287 patients were included in the analysis, of whom 1,553 (68%) completed the initial ordered LDCT. Mean age was 63 years, and 73% were underrepresented minorities. Median travel time from patient residence to the LDCT screening facility was 17 minutes by private vehicle and 67 minutes by public transportation. There was a small difference in travel time to the LDCT screening facility by public transportation for patients who completed LDCT versus those who did not (67 vs 66 min, respectively; P=.04) but no difference in travel time by private vehicle for these patients (17 min for both; P=.67). In multivariable analysis, LDCT completion was not associated with projected travel time to the LDCT facility by private vehicle (odds ratio, 1.01; 95% CI, 0.82-1.25) or public transportation (odds ratio, 1.14; 95% CI, 0.89-1.44). Similar results were noted across travel-type permutations. Black individuals were 29% less likely to complete LDCT screening compared with White individuals. CONCLUSIONS: In an urban population comprising predominantly underrepresented minorities, projected travel time is not associated with initial LDCT completion in an integrated health care system. Other reasons for differences in LDCT completion warrant investigation.

Assessing Barriers and Facilitators to Lung Cancer Screening: Initial Findings from a Patient Navigation Intervention.

Low-dose computed tomography-based lung cancer screening represents a complex clinical undertaking that could require multiple referrals, appointments, and time-intensive procedures. These steps may pose difficulties and raise concerns among patients, particularly minority, under-, and uninsured populations. The authors implemented patient navigation to identify and address these challenges. They conducted a pragmatic randomized controlled trial of telephone-based navigation for lung cancer screening in an integrated, urban safety-net health care system. Following standardized protocols, bilingual (Spanish and English) navigators educated, motivated, and empowered patients to traverse the health system. Navigators made systematic contact with patients, recording standardized call characteristics in a study-specific database. Call type, duration, and content were recorded. Univariable and multivariable multinomial logistic regression was performed to investigate associations between call characteristics and reported barriers. Among 225 patients (mean age 63 years, 46% female, 70% racial/ethnic minority) assigned navigation, a total of 559 barriers to screening were identified during 806 telephone calls. The most common barrier categories were personal (46%), provider (30%), and practical (17%). System (6%) and psychosocial (1%) barriers were described by English-speaking patients, but not by Spanish-speaking patients. Over the course of the lung cancer screening process, provider-related barriers decreased 80% (P = 0.008). The authors conclude that patients undergoing lung cancer screening frequently report personal and health care provider-related barriers to successful participation. Barrier types may differ among patient populations and over the course of the screening process. Further understanding of these concerns may increase screening uptake and adherence. Clinical Trial Registration number: (NCT02758054).

Prevalence And Impact of Medical Comorbidities in A Real-World Lung Cancer Screening Population.

BACKGROUND: Lung cancer screening trials generally enroll motivated, relatively healthy, and adherent populations. We therefore evaluated the prevalence and effects of comorbidities in a real-world population undergoing low-dose computed tomography (LDCT) scans. PATIENTS AND METHODS: We calculated the Charlson Comorbidity Index (CCI) of patients for whom an initial low-dose computed tomography (LDCT) for lung cancer screening was ordered between February 2017 and February 2019 in an integrated safety-net healthcare system. We examined the association between CCI and initial LDCT completion using multivariable logistic regression, assessed the association between specific medical comorbidity and LDCT completion using Chi-square test or Fisher's exact test as appropriate, and examined the association between CCI and LDCT Lung-RADS results using Fisher's exact test. RESULTS: A total of 1358 patients were included in the analysis. Mean age was 63 years, 57% were women, and 50% were Black. Patients had moderate comorbidity burden (median CCI 3) with chronic pulmonary disease the most common comorbidity. Overall, 943 LDCT (70%) were completed. There was no difference in 30-day, 90-day, or 1-year completion rates of initial LDCT according to CCI. However, 30-day LDCT completion rates did increase over time (P < .001). Lung-RADS scores were not associated with CCI. CONCLUSION: In a real-world setting, patients undergoing lung cancer screening have moderate comorbidity burden. The degree and type of medical comorbidity are not associated with initial screening completion or results. Timeliness of LDCT completion may improve as program experience increases.

Clinician Variation in Ordering and Completion of Low-Dose Computed Tomography for Lung Cancer Screening in a Safety-Net Medical System.

BACKGROUND: Less than 5% of eligible individuals in the United States undergo lung cancer screening. Variation in clinicians' participation in lung cancer screening has not been determined. PATIENTS AND METHODS: We studied medical providers who ordered ≥ 1 low-dose computed tomography (LDCT) for lung cancer screening from February 2017 through February 2019 in an integrated safety-net healthcare system. We analyzed associations between provider characteristics and LDCT orders and completion using chi-square, Fisher exact, and Student t tests, as well as ANOVA and multinomial logistic regression. RESULTS: Among an estimated 194 adult primary care physicians, 144 (74%) ordered at least 1 LDCT, as did 39 specialists. These 183 medical providers ordered 1594 LDCT (median, 4; interquartile range, 2-9). In univariate and multivariate models, family practice providers (P < .001) and providers aged ≥ 50 years (P = .03) ordered more LDCT than did other clinicians. Across providers, the median proportion of ordered LDCT that were completed was 67%. The total or preceding number of LDCT ordered by a clinician was not associated with the likelihood of LDCT completion. CONCLUSION: In an integrated safety-net healthcare system, most adult primary care providers order LDCT. The number of LDCT ordered varies widely among clinicians, and a substantial proportion of ordered LDCT are not completed.

Tracking the Nonenrolled: Lung Cancer Screening Patterns Among Individuals not Accrued to a Clinical Trial.

INTRODUCTION: For lung cancer screening, the available data are often derived from patients enrolled prospectively in clinical trials. We, therefore, investigated lung cancer screening patterns among individuals eligible for, but not enrolled in, a screening trial. PATIENTS AND METHODS: From February 2017 through February 2019, we enrolled subjects in a trial examining telephone-based navigation during low-dose computed tomography (LDCT) for lung cancer screening. We identified patients for whom LDCT was ordered and who were approached, but not enrolled, in the trial. We categorized nonenrollment as the patient had declined or could not be reached. We compared the characteristics and LDCT completion rates among these groups and the enrolled population using the 2-sample t test and χ2 test. RESULTS: Of 900 individuals approached for participation (mean age, 62 years; 45% women, 53% black), 447 were enrolled in the screening clinical trial. No significant demographic differences were found between the enrolled and nonenrolled cohorts. Of the 453 individuals not enrolled, 251 (55%) had declined participation and 202 (45%) could not be reached, despite up to 6 attempts. LDCT completion was significantly associated with enrollment status: 81% of enrolled individuals, 73% of individuals who declined participation, and 49% of those who could not be reached (P < .001). CONCLUSIONS: In the present single-center study, demographic factors did not predict for participation in a lung cancer screening trial. Lung cancer screening adherence rates were substantially lower for those not enrolled in a screening trial, especially for those who could not be contacted. These findings may inform the broader implementation of screening programs.