This study demonstrates a comprehensive implementation of a multidisciplinary model of lung cancer care, which will advance the science behind implementing this much-advocated clinical care model.

PURPOSE: Multidisciplinary lung cancer care is assumed to improve care delivery by increasing transparency, objectivity, and shared decision making; however, there is a lack of high-level evidence demonstrating its benefits, especially in community-based health care systems. We used implementation and team science principles to establish a colocated multidisciplinary lung cancer clinic in a large community-based health care system and evaluated patient experience and outcomes within and outside this clinic. METHODS: We conducted a prospective frequency-matched comparative effectiveness study (ClinicalTrials.gov identifier: NCT02123797 ) evaluating the thoroughness of lung cancer staging, receipt of stage-appropriate treatment, and survival between patients receiving care in the multidisciplinary clinic and those receiving usual serial care. Target enrollment was 150 patients on the multidisciplinary arm and 300 on the serial care arm. We frequency-matched patients by clinical stage, performance status, insurance type, race, and age. RESULTS: A total of 526 patients were enrolled: 178 on the multidisciplinary arm and 348 on the serial care arm. After adjusting for other factors, multidisciplinary patients had significantly higher odds (odds ratio [OR]: 2.3 [95% CI, 1.5 to 3.4]) of trimodality staging compared with serial care. Patients on the multidisciplinary arm also had higher odds of receiving invasive stage confirmation (OR: 2.0 [95% CI, 1.4 to 3.1]) and mediastinal stage confirmation (OR: 1.9 [95% CI, 1.3 to 2.8]). Additionally, patients receiving multidisciplinary care were significantly more likely to receive stage-appropriate treatment (OR: 1.8 [95% CI, 1.1 to 3.0]). We found no significant difference in overall or progression-free survival between study arms. CONCLUSION: The multidisciplinary clinic delivered significant improvements in evidence-based quality care on multiple levels. Even in the absence of a demonstrable survival benefit, these findings provide a strong rationale for recommending this model of care.

WORK-IN-PROGRESS & LESSONS LEARNEDhealth, 2 lifestyle behaviors (e.g., physical activity, diet), 3 health disparities, 4,5 and social influences. 2,[6][7][8] Moreover, when disease outcomes most relevant to a community are selected, 7,9 they can be built upon to identify and develop more effective health programs. Community-based participatory research (CBPR)approaches have been widely used in developing and implementing community health needs assessments. 6,7,[9][10][11]

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Purpose/Objective(s): Optimal treatment for nonesmall cell lung cancer (NSCLC), depending on patients' clinical stage, performance status, and preferences, may include surgical resection, radiation therapy, chemotherapy (in various combinations), or no treatment. We evaluated variation in stage-stratified use of treatment modalities in and out of a multidisciplinary (MultiD) program in a large community-based healthcare system. We hypothesized that MultiD care will optimize modality use. Materials/Methods: 2014-2015 NSCLC Tumor Registry data from 4 hospitals within 1 tri-state healthcare system retrospectively reviewed; MultiD data prospectively collected from a weekly MultiD tumor conference. MultiD data were analyzed separately from the tumor registry data. Any MultiD patients present in the tumor registry data were removed. Staging was based on information available before commencement of any treatment modality (defined as the actual treatment received). Patients were clustered into 3 stage groupings: I-II, III, and IV. Stage-stratified frequencies of treatment modalities across the 4 hospitals and the MultiD program were compared using Chi-squared tests. Results: 1,614 NSCLC patients were seen outside and 248 within the MultiD program. Demographics were similar except MultiD had a higher proportion of African American (26% v 33%, PZ.01) and Medicaid/ uninsured (8.3% v 22%) and fewer commercially insured (55% v 40%) patients (P<.001). Stage distributions for non-MultiD versus MultiD were: 29% versus 46% (stage I/II); 20% versus 25% (stage III); 52% versus 29% (stage IV). There were striking differences in use of modalities for non-MultiD versus MultiD: surgery for stage I/II disease 48% versus 63% and no treatment, 16% versus 6% (PZ.01); multimodality therapy for stage III, 62% versus 75%, and no treatment 19% versus 10% (PZ.02); chemotherapy for stage IV, 57% versus 70% stage IV, radiation only, 12% versus 13%, and no treatment 29% versus 9% (P<.001). Patient demographics were similar across the 4 hospitals, but modality use varied widely. For stage I/II, surgical resection rates ranged from 24%-62% and no treatment from 7%-42%; for stage III, multimodality treatment ranged from 40%-81%, and no treatment from 13%-36%; for stage IV, chemotherapy rates ranged from 47%-59%, and no treatment from 25%-43% (P<.001 for all stages). Conclusion: Despite less favorable patient demographics, stage-stratified care within a community-based MultiD Program was more directed towards active and multimodality care. Great heterogeneity in pattern of care exists across hospitals within the same healthcare system. Further research into the causes of stage-stratified treatment variation, and the potential use of structured MultiD Programs to improve access to care is warranted.