Citations

PURPOSE In response to the COVID-19 pandemic, many cancer practices rapidly adopted telehealth services. However, there is a paucity of data regarding ongoing telehealth visit utilization beyond this initial response. The purpose of this study was to assess changes in variables associated with telehealth visit utilization over time. METHODS This is a cross-sectional, year-over-year, retrospective analysis of telehealth visits conducted across a multisite, multiregional cancer practice in the United States. Multivariable models examined the association of patient- and provider-level variables with telehealth utilization across outpatient visits conducted over three 8-week periods from July to August in 2019 (n = 32,537), 2020 (n = 33,399), and 2021 (n = 35,820). RESULTS The rate of telehealth utilization increased from <0.01% (2019) to 11% (2020) to 14% (2021). The most significant patient-level factors associated with increased telehealth utilization included nonrural residence and age ≤65 years. Among patients residing in rural settings, video visit utilization rates were significantly lower and phone visit utilization rates were significantly higher compared with patients from nonrural residences. Regarding provider-level factors, widening differences in telehealth utilization were observed at tertiary versus community-based practice settings. Increased telehealth utilization was not associated with duplicative care as per-patient and per-physician visit volumes in 2021 remained consistent with prepandemic levels. CONCLUSION We observed continuous expansion in telehealth visit utilization from 2020 to 2021. Our experiences suggest that telehealth can be integrated into cancer practices without evidence of duplicative care. Future work should examine sustainable reimbursement structures and policies to ensure accessibility of telehealth as a means to facilitate equitable, patient-centered cancer care.

IMPORTANCE: Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes. OBJECTIVES: The Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN, SETTING, AND PARTICIPANTS: This 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams. RESULTS: Eleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care.

Abstract Background Little is known about the strategies used by critical care leaders to implement new practices in response to the COVID-19 pandemic. Prior studies have identified implementation factors, such as structured communication mechanisms and collaborative leadership styles, that facilitate implementation of new clinical practices. However, the association between differing implementation climates and COVID-19 clinical outcomes has not been examined. The purpose of this mixed methods study was to evaluate the relationship between implementation determinants and COVID-19 mortality rates. Methods We used mixed methods guided by the Consolidated Framework for Implementation Research (CFIR) to assess implementation factors that were associated with COVID-19 mortality rates across diverse critical care settings. Semi-structured qualitative interviews were conducted with critical care leaders and analyzed using the CFIR to rate the influence of constructs on implementation of new care practices. Qualitative and quantitative comparisons of CFIR construct ratings were performed between hospital groups with low versus high mortality rates. Results 31 clinical leaders were interviewed across 17 hospitals. Of the 13 relevant CFIR constructs, three constructs (implementation climate, leadership engagement, and engaging staff) had both qualitative and statistically significant quantitative correlations with mortality outcomes. An implementation climate governed by a trial-and-error approach was correlated with high COVID-19 mortality, while leadership engagement and engaging staff were correlated with low mortality. Another three constructs (needs of patient; organizational incentives and rewards; and engaging implementation leaders) were qualitatively different across mortality outcome groups, but these differences were not statistically significant. Seven constructs did not distinguish between low versus high mortality hospitals based on qualitative or quantitative comparison of CFIR construct ratings. Conclusions Application of the CFIR to identify and quantify constructs across critical care settings enabled us to characterize implementation barriers and facilitators at the practice, interpersonal, and provider level that were associated with COVID-19 mortality rates. Improving clinical outcomes during future public health emergencies will require reducing identified barriers associated with high mortality and harnessing salient facilitators associated with low mortality. Our findings suggest that clinical care implementation efforts should focus on avoiding trial-and-error approaches to adopting new practices, while promoting collaborative and engaged leadership styles.

Diagnostic error or delay (DEOD) is common in the acute care setting and results in poor patient outcomes. Many factors contribute to DEOD, but little is known about how contributors may differ across acute care areas and professional roles. As part of a sequential exploratory mixed methods research study, we surveyed acute care clinical stakeholders about the frequency with which different factors contribute to DEOD. Survey respondents could also propose solutions in open text fields. N = 220 clinical stakeholders completed the survey. Care Team Interactions, Systems and Process, Patient, Provider, and Cognitive factors were perceived to contribute to DEOD with similar frequency. Organization and Infrastructure factors were perceived to contribute to DEOD significantly less often. Responses did not vary across acute care setting. Physicians perceived Cognitive factors to contribute to DEOD more frequently compared to those in other roles. Commonly proposed solutions included: technological solutions, organization level fixes, ensuring staff know and are encouraged to work to the full scope of their role, and cultivating a culture of collaboration and respect. Multiple factors contribute to DEOD with similar frequency across acute care areas, suggesting the need for a multi-pronged approach that can be applied across acute care areas.

1512 Background: In response to the COVID-19 pandemic, many cancer practices adopted telehealth, including telephone and video appointments. Following a period of initial expansion that began in March 2020, sustained telehealth integration has emerged across the Mayo Clinic Cancer Practice (MCCP) in 2021. The primary objective of this study was to identify factors associated with utilization of telehealth appointments. Methods: A cross-sectional, multi-site, retrospective analysis was conducted across MCCP – a multisite, multiregional cancer practice with tertiary referral campuses in Minnesota, Florida, and Arizona, as well as rural, community-based hospitals and clinics throughout the Upper Midwest. Multivariable models were used to examine the association of patient- and provider-level variables with telehealth utilization. Results: Outpatient appointments conducted in July – August 2019 (n = 32,932) were compared with those from 2020 (n = 33,662) and 2021 (n = 35,486). The rate of telehealth appointment utilization increased from <0.01% in 2019 to 11.0% in 2020 and 14.0% in 2021. The strongest provider-level predictor of telehealth utilization was female physician provider type (OR 1.06, 95% CI 1.01 to 1.11; P = 0.0297), a trend consistently observed across career stages, practice locations and settings in 2020 and 2021. Additionally, while the rate of telehealth utilization was not significantly different at referral and community-based campuses in 2020, providers at referral campuses were significantly more likely to utilize telehealth than community-based campuses in 2021 (OR 1.1, 95% CI 1.01 to 1.12; P = 0.0289). Regarding patient-level factors, rural residence (defined by Rural-Urban Commuting Area codes), which accounted for 44.2% of the patient population, was significantly associated with lower telehealth utilization as compared to patients with urban residences, particularly for video appointments (OR 1.04, 95% CI 1.02 to 1.07; P < 0.0001). Notably, the disparity in telehealth utilization between rural and urban populations was found to be less pronounced in 2021 as compared to 2020. Conclusions: Multivariable analysis across a multi-site, multi-regional cancer practice identified several factors associated with increased telehealth utilization. These included female physician provider type, referral-based campuses, and patients residing in urban settings. A detailed understanding of the factors that influence telehealth utilization – a method of care delivery which represents a “new normal” across many cancer practices – will be essential to enable continued equitable access to high-quality, high-impact, patient-centered cancer care.

Abstract Background The COVID-19 pandemic produced unprecedented demands and rapidly changing evidence and practices within critical care settings. The purpose of this study was to identify factors and strategies that hindered and facilitated effective implementation of new critical care practices and policies in response to the pandemic. Methods We used a cross-sectional, qualitative study design to conduct semi-structured in-depth interviews with critical care leaders across the United States. The interviews were audio-taped and professionally transcribed verbatim. Guided by the Consolidated Framework for Implementation Research (CFIR), three qualitative researchers used rapid analysis methods to develop relevant codes and identify salient themes. Results: Among the 17 hospitals that agreed to participate in this study, 31 clinical leaders were interviewed. The CFIR-driven rapid analysis of the interview transcripts generated 12 major themes, which included six implementation facilitators (i.e., factors that promoted the implementation of new critical care practices) and six implementation barriers (i.e., factors that hindered the implementation of new critical care practices). These themes spanned the five CFIR domains (Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process) and 11 distinct CFIR constructs. Salient facilitators to implementation efforts included staff resilience, commitment, and innovation, which were supported through collaborative feedback and decision-making mechanisms between leadership and frontline staff. Major identified barriers included lack of access to reliable and transferable information, available resources, uncollaborative leadership and communication styles. Conclusions: Through applying the CFIR to organize and synthesize our qualitative data, this study revealed important insights into implementation determinants that influenced the uptake of new critical care practices during COVID-19. As the pandemic continues to burden critical care units, clinical leaders should consider emulating the effective change management strategies identified. The cultivation of streamlined, engaging, and collaborative leadership and communication mechanisms not only supported implementation of new care practices across sites, but it also helped reduce salient implementation barriers, particularly resource and staffing shortages. Future critical care implementation studies should seek to capitalize on identified facilitators and reduce barriers.

Abstract Background The COVID-19 pandemic produced unprecedented demands and rapidly changing evidence and practices within critical care settings. The purpose of this study was to identify factors and strategies that hindered and facilitated effective implementation of new critical care practices and policies in response to the pandemic. Methods We used a cross-sectional, qualitative study design to conduct semi-structured in-depth interviews with critical care leaders across the United States. The interviews were audio-taped and professionally transcribed verbatim. Guided by the Consolidated Framework for Implementation Research (CFIR), three qualitative researchers used rapid analysis methods to develop relevant codes and identify salient themes. Results Among the 17 hospitals that agreed to participate in this study, 31 clinical leaders were interviewed. The CFIR-driven rapid analysis of the interview transcripts generated 12 major themes, which included six implementation facilitators (i.e., factors that promoted the implementation of new critical care practices) and six implementation barriers (i.e., factors that hindered the implementation of new critical care practices). These themes spanned the five CFIR domains (Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Process) and 11 distinct CFIR constructs. Salient facilitators to implementation efforts included staff resilience, commitment, and innovation, which were supported through collaborative feedback and decision-making mechanisms between leadership and frontline staff. Major identified barriers included lack of access to reliable and transferable information, available resources, uncollaborative leadership and communication styles. Conclusions Through applying the CFIR to organize and synthesize our qualitative data, this study revealed important insights into implementation determinants that influenced the uptake of new critical care practices during COVID-19. As the pandemic continues to burden critical care units, clinical leaders should consider emulating the effective change management strategies identified. The cultivation of streamlined, engaging, and collaborative leadership and communication mechanisms not only supported implementation of new care practices across sites, but it also helped reduce salient implementation barriers, particularly resource and staffing shortages. Future critical care implementation studies should seek to capitalize on identified facilitators and reduce barriers.

Abstract Background The symptom burden associated with cancer and its treatment can negatively affect patients’ quality of life and survival. Symptom-focused collaborative care model (CCM) interventions can improve outcomes, but only if patients engage with them. We assessed the receptivity of severely symptomatic oncology patients to a remote nurse-led CCM intervention. Methods In a pragmatic, cluster-randomized, stepped-wedge trial conducted as part of the National Cancer Institute IMPACT Consortium (E2C2, NCT03892967), patients receiving cancer care were asked to rate their sleep disturbance, pain, anxiety, emotional distress, fatigue, and limitations in physical function. Patients reporting at least 1 severe symptom (≥7/10) were offered phone consultation with a nurse symptom care manager (RN SCM). Initially, patients had to “opt-in” to receive a call, but the protocol was later modified so they had to “opt-out” if they did not want a call. We assessed the impact of opt-in vs opt-out framing and patient characteristics on receptiveness to RN SCM calls. All statistical tests were 2-sided. Results Of the 1204 symptom assessments (from 864 patients) on which at least 1 severe symptom was documented, 469 (39.0%) indicated receptivity to an RN SCM phone call. The opt-out period (odds ratio [OR] = 1.61, 95% confidence interval [CI] = 1.12 to 2.32, P = .01), receiving care at a tertiary care center (OR = 3.59, 95% CI = 2.18 to 5.91, P &lt; .001), and having severe pain (OR = 1.80, 95% CI = 1.24 to 2.62, P = .002) were associated with statistically significantly greater willingness to receive a call. Conclusions Many severely symptomatic patients were not receptive to an RN SCM phone call. Better understanding of reasons for refusal and strategies for improving patient receptivity are needed.

Objectives Diagnostic error and delay is a prevalent and impactful problem. This study was part of a mixed-methods approach to understand the organizational, clinician, and patient factors contributing to diagnostic error and delay among acutely ill patients within a health system, as well as recommendations for the development of tailored, targeted, feasible, and effective interventions. Methods We did a multisite qualitative study using focus group methodology to explore the perspectives of key clinician stakeholders. We used a conceptual framework that characterized diagnostic error and delay as occurring within 1 of 3 stages of the patient’s diagnostic journey—critical information gathering, synthesis of key information, and decision making and communication. We developed our moderator guide based on the sociotechnical frameworks previously described by Holden and Singh for understanding noncognitive factors that lead to diagnostic error and delay. Deidentified focus group transcripts were coded in triplicate and to consensus over a series of meetings. A final coded data set was then uploaded into NVivo software. The data were then analyzed to generate overarching themes and categories. Results We recruited a total of 64 participants across 4 sites from emergency departments, hospital floor, and intensive care unit settings into 11 focus groups. Clinicians perceive that diverse organizational, communication and coordination, individual clinician, and patient factors interact to impede the process of making timely and accurate diagnoses. Conclusions This study highlights the complex sociotechnical system within which individual clinicians operate and the contributions of systems, processes, and institutional factors to diagnostic error and delay.