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Background: Cancer patients who receive evidence-based tobacco-dependence treatment are more likely to quit and remain abstinent, but tobacco treatment programs (TTPs) are not consistently offered. In 2017, the U.S. National Cancer Institute, through the Cancer Moonshot, funded the Cancer Center Cessation Initiative (C3I). C3I supports 52 cancer centers to implement and expand evidence-based tobacco treatment in routine oncology care. Integration into routine care involves the use of health information technology (IT), including modifying electronic health records and clinical workflows. Here, we examine C3I cancer centers' IT leadership involvement and experiences in tobacco-dependence treatment implementation., Method: This qualitative study of C3I-funded cancer centers integrated data from online surveys and in-person, semistructured interviews with IT leaders. We calculated descriptive statistics of survey data and applied content analysis to interview transcripts., Results: Themes regarding IT personnel included suggestions to involve IT early, communicate regularly, understand the roles and influence of the IT team, and match program design with IT funding and resources. Themes regarding electronic health record (EHR) modifications included beginning modifications early to account for long lead time to make changes, working with IT to identify and adapt existing EHR tools for TTP or designing tools that will support a desired workflow developed with end-users, and working with IT personnel to make sure TTPs comply with system and state policies (e.g., privacy laws)., Conclusions: The experiences of C3I cancer centers regarding the use of health IT to enhance tobacco-dependence treatment program implementation can guide cancer centers and community oncology practices to potentially enhance TTP implementation and patient outcomes., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics., Methods: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined., Results: 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90)., Conclusions: Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types., Impact: This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3., (©2022 The Authors; Published by the American Association for Cancer Research.)

Background: Health system change can increase the reach of evidence-based smoking cessation treatments. Proactive electronic health record (EHR)-enabled, closed-loop referral ("eReferral") to state tobacco quitlines increases the rates at which patients who smoke accept cessation treatment. Implementing such system change poses many challenges, however, and adaptations to system contexts are often required, but are understudied. This retrospective case study identified adaptations to eReferral EHR tools and implementation strategies in two healthcare systems., Methods: In a large clustered randomized controlled trial (C-RCT; NCT02735382) conducted in 2016-2017, 11 primary care clinics in two healthcare systems implemented quitline eReferral, starting with 1 pilot clinic per system followed by 2 phases of implementation (an experimental phase in 5-6 test clinics per system and then a system-wide dissemination phase in both systems). Adaptations were informed by stakeholder input from live trainings, follow-up calls and meetings in the first month after eReferral launch, emails, direct observation by researchers, and clinic staff survey responses. Retrospective, descriptive analysis characterized implementation strategy modifications and adaptations using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS). A pre- and post-implementation survey assessed staff ratings of eReferral acceptability and implementation barriers and facilitators., Findings: Major modifications to closed-loop eReferral implementation strategies included aligning the eReferral initiative with other high-priority health system objectives, modifying eReferral user interfaces and training in their use, modifying eReferral workflows and associated training, and maintaining and enhancing interoperability and clinician feedback functions. The two health systems both used Epic EHRs but used different approaches to interfacing with the quitline vendor and integrating eReferral into clinician workflows. Both health systems engaged in iterative refinement of the EHR alert prompting eReferral, the eReferral order, trainings, and workflows. Staff survey comments suggested moderate acceptability of eReferral processes and identified possible targets for future modifications in eReferral, including reducing clinician burden related to EHR documentation and addressing clinicians' negative beliefs about patient receptivity to cessation treatment., Conclusions: System-wide implementation of tobacco quitline eReferral in primary care outpatient clinics is feasible but requires extensive coordination across stakeholders, tailoring to local health system EHR configurations, and sensitivity to system- and clinic-specific workflows., Trial Registration: www., Clinicaltrials: gov, NCT02735382 . Registered on 12 August 2016., (© 2022. The Author(s).)

Main Objective: There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic., Study Design and Methods: University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission., Results and Significance: The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months., Conclusions: Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes., Trial Registration: ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528)., Competing Interests: The authors have declared that no competing interests exist.

Background: Delivering evidence-based tobacco dependence treatment in oncology settings improves smoking abstinence and cancer outcomes. Leadership engagement/buy-in is critical for implementation success, but few studies have defined buy-in or described how to secure buy-in for tobacco treatment programs (TTPs) in cancer care. This study examines buy-in during the establishment of tobacco treatment programs at National Cancer Institute (NCI)-designated cancer centers., Methods: We utilized a sequential, explanatory mixed-methods approach to analyze quantitative data and qualitative interviews with program leads in the U.S.-based NCI Moonshot-supported Cancer Center Cessation Initiative ( n = 20 Centers). We calculated descriptive statistics and applied structural coding and content analysis to qualitative data., Results: At least 75% of participating centers secured health care system administrative, clinical, and IT leadership buy-in and support. Six themes emerged from interviews: engaging leadership, access to resources, leveraging federal funding support to build leadership interest, designating champions, identifying training needs, and ensuring staff roles and IT systems support workflows., Conclusions: Buy-in among staff and clinicians is defined by the belief that the TTP is necessary, valuable, and evidence based. Recognizing and securing these dimensions of buy-in can facilitate implementation success, leading to improved cancer outcomes.

Background: Although people who smoke cigarettes are overrepresented among hospital inpatients, few are connected with smoking cessation treatment during their hospitalization. Training, accountability for medication use, and monitoring of all patients position pharmacists well to deliver cessation interventions to all hospitalized patients who smoke. Methods: A large Midwestern University hospital implemented a pharmacist-led smoking cessation intervention. A delegation protocol for hospital pharmacy inpatients who smoked cigarettes gave hospital pharmacists the authority to order nicotine replacement therapy (NRT) during hospitalization and upon discharge, and for referral to the Wisconsin Tobacco Quit Line (WTQL) at discharge. Eligible patients received the smoking cessation intervention unless they actively refused (ie, "opt-out"). The program was pilot tested in phases, with pharmacist feedback between phases, and then implemented hospital-wide. Interviews, surveys, and informal mechanisms identified ways to improve implementation and workflows. Results: Feedback from pharmacists led to changes that improved workflow, training and patient education materials, and enhanced adoption and reach. Refining implementation strategies across pilot phases increased the percentage of eligible smokers offered pharmacist-delivered cessation support from 37% to 76%, prescribed NRT from 2% to 44%, and referred to the WTQL from 3% to 32%. Conclusion: Hospitalizations provide an ideal opportunity for patients to make a tobacco quit attempt, and pharmacists can capitalize on this opportunity by integrating smoking cessation treatment into existing inpatient medication reconciliation workflows. Pharmacist-led implementation strategies developed in this study may be applicable in other inpatient settings., Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2021.)

Introduction: Patients who use tobacco are too rarely connected with tobacco use treatment during healthcare visits. Electronic health record enhancements may increase such referrals in primary care settings. This project used the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to assess the implementation of a healthcare system change carried out in an externally valid manner (executed by the healthcare system)., Methods: The healthcare system used their standard, computer-based training approach to implement the electronic health record and clinic workflow changes for electronic referral in 30 primary care clinics that previously used faxed quitline referral. Electronic health record data captured rates of assessment of readiness to quit and quitline referral 4 months before implementation and 8 months (May-December 2017) after implementation. Data, analyzed from October 2018 to June 2019, also reflected intervention reach, adoption, and maintenance., Results: For reach and effectiveness, from before to after implementation for electronic referral, among adult patients who smoked, assessment of readiness to quit increased from 24.8% (2,126 of 8,569) to 93.2% (11,163 of 11,977), quitline referrals increased from 1.7% (143 of 8,569) to 11.3% (1,351 of 11,977), and 3.6% were connected with the quitline after implementation. For representativeness of reach, electronic referral rates were especially high for women, African Americans, and Medicaid patients. For adoption, 52.6% of staff who roomed at least 1 patient who smoked referred to the quitline. For maintenance, electronic referral rates fell by approximately 60% over 8 months but remained higher than pre-implementation rates., Conclusions: Real-world implementation of an electronic health record-based electronic referral system markedly increased readiness to quit assessment and quitline referral rates in primary care patients. Future research should focus on implementation methods that produce more consistent implementation and better maintenance of electronic referral., (Copyright © 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)