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In contrast to traditional randomized controlled trials, embedded pragmatic clinical trials (ePCTs) are conducted within healthcare settings with real-world patient populations. ePCTs are intentionally designed to align with health system priorities leveraging existing healthcare system infrastructure and resources to ease intervention implementation and increase the likelihood that effective interventions translate into routine practice following the trial. The NIH Pragmatic Trials Collaboratory, funded by the National Institutes of Health (NIH), supports the conduct of large-scale ePCT Demonstration Projects that address major public health issues within healthcare systems. The Collaboratory has a unique opportunity to draw on the Demonstration Project experiences to generate lessons learned related to ePCTs and the dissemination and implementation of interventions tested in ePCTs. In this article, we use case studies from six completed Demonstration Projects to summarize the Collaboratory's experience with post-trial interpretation of results, and implications for sustainment (or de-implementation) of tested interventions. We highlight three key lessons learned. First, ineffective interventions (i.e., ePCT is null for the primary outcome) may be sustained if they have other measured benefits (e.g., secondary outcome or subgroup) or even perceived benefits (e.g., staff like the intervention). Second, effective interventions-even those solicited by the health system and/or designed with significant health system partner buy-in-may not be sustained if they require significant resources. Third, alignment with policy incentives is essential for achieving sustainment and scale-up of effective interventions. Our experiences point to several recommendations to aid in considering post-trial sustainment or de-implementation of interventions tested in ePCTs: (1) include secondary outcome measures that are salient to health system partners; (2) collect all appropriate data to allow for post hoc analysis of subgroups; (3) collect experience data from clinicians and staff; (4) engage policy-makers before starting the trial.

PurposeRacial/ethnic differences in cancer symptom burden are well documented, but limited research has evaluated modifiable factors underlying these differences. Our objective was to examine the role of patient-provider interactions to help explain the relationship between race/ethnicity and cancer-specific physical well-being (PWB) among women with breast cancer.MethodsThe Pathways Study is a prospective cohort study of 4505 women diagnosed with breast cancer at Kaiser Permanente Northern California between 2006 and 2013. Our analysis included white, black, Hispanic, and Asian participants who completed baseline assessments of PWB, measured using the Functional Assessment of Cancer Therapy for Breast Cancer, and patient-provider interactions, measured by the Interpersonal Processes of Care Survey (IPC) (N = 4002). Using step-wise linear regression, we examined associations of race/ethnicity with PWB, and changes in associations when IPC domains were added.ResultsWe observed racial/ethnic differences in PWB, with minorities reporting lower scores than whites (beta, black: - 1.79; beta, Hispanic: - 1.92; beta, Asian: - 1.68; p

Background Racial and ethnic disparities in genomic testing could exacerbate disparities in access to precision cancer therapies and survival—particularly in the context of lung cancer where genomic testing has been recommended for the past decade. However, prior studies assessing disparities in genomic testing have yielded mixed results. Methods We conducted a systemic review to examine racial and ethnic disparities in the use of genomic testing among lung cancer patients in the United States. Two comprehensive searches in PubMed, Embase, and Scopus were conducted (September 2022, May 2023). Original studies that assessed rates of genomic testing by race or ethnicity were included. Findings were narratively synthesized by outcome. Results The search yielded 2739 unique records, resulting in 18 included studies. All but 1 study were limited to patients diagnosed with non–small cell lung cancer. Diagnosis years ranged from 2007 to 2022. Of the 18 studies, 11 found statistically significant differences in the likelihood of genomic testing by race or ethnicity; in 7 of these studies, testing was lower among Black patients compared with White or Asian patients. However, many studies lacked adjustment for key covariates and included patients with unclear eligibility for testing. Conclusions A majority of studies, though not all, observed racial and ethnic disparities in the use of genomic testing among patients with lung cancer. Heterogeneity of study results throughout a period of changing clinical guidelines suggests that minoritized populations—Black patients in particular—have faced additional barriers to genomic testing, even if not universally observed at all institutions. [ABSTRACT FROM AUTHOR]

Clinical and health services researchers seek to discover effective programs, practices, and interventions to improve people's health. The current paradigm for evidence generation is incremental and misaligned to translate evidence-based discoveries into real-world settings. This persistent challenge are "valleys of death" that represent missed opportunities and preventable missteps to actually use scientific advancements in real-world clinical settings where they can improve health and well-being (De Geest S, Zúñiga F, Brunkert T et al. Powering Swiss health care for the future: implementation science to bridge "the valley of death". 2020;150:w20323). Only one in seven of evidence-based interventions is ever implemented. It is after an average of 17 years. We propose embedding the principles of implementation science throughout the research pipeline, from discovery to adoption, to efficiently translate discoveries into real-world contexts (Balas EA, Boren SA. Managing clinical knowledge for health care improvement. 2000;9:65–70). We outline implications for capacity building, including composition of the research team, study design, and competencies that could bolster the value proposition of implementation science. We describe a research paradigm that recognizes scientists' responsibility to ensure their discoveries be translated into real-world settings. [ABSTRACT FROM AUTHOR]