Pandemic Through the Lens of Black Barbershops: COVID-19's Impact and Barbers' Potential Role as Public Health Extenders.

We examined the impact of COVID-19 on Black barbershops and their potential role as public health extenders. A 30-item survey was distributed to predominantly Black barbershop owners and barbers across 40 different states/territories in the US between June and October 2020. The survey addressed the impact of COVID-19 on Black barbershops, and barbers' interest in engaging in health outreach programs. The majority reported that stay-at-home orders had significant to severe impact on their business; few were prepared for the financial impact and less than half thought they qualified for government assistance. The majority were already providing health education and outreach to the Black community and showed interest in continuing to provide such services, like information on COVID-19. Barbers in Black-serving barbershops, a well-documented effective place for public health outreach to the Black community, show promise as public health extenders in the response to the COVID-19 pandemic.

Excess Mortality Among Patients in the Veterans Affairs Health System Compared With the Overall US Population During the First Year of the COVID-19 Pandemic.

Importance: During the first year of the COVID-19 pandemic, there was a substantial increase in the rate of death in the United States. It is unclear whether those who had access to comprehensive medical care through the Department of Veterans Affairs (VA) health care system had different death rates compared with the overall US population. Objective: To quantify and compare the increase in death rates during the first year of the COVID-19 pandemic between individuals who received comprehensive medical care through the VA health care system and those in the general US population. Design, Setting, and Participants: This cohort study compared 10.9 million enrollees in the VA, including 6.8 million active users of VA health care (those with a visit in the last 2 years), with the general population of the US, with deaths occurring from January 1, 2014, to December 31, 2020. Statistical analysis was conducted from May 17, 2021, to March 15, 2023. Main Outcomes and Measures: Changes in rates of death from any cause during the COVID-19 pandemic in 2020 compared with previous years. Changes in all-cause death rates by quarter were stratified by age, sex, race and ethnicity, and region, based on individual-level data. Multilevel regression models were fit in a bayesian setting. Standardized rates were used for comparison between populations. Results: There were 10.9 million enrollees in the VA health care system and 6.8 million active users. The demographic characteristics of the VA populations were predominantly male (>85% in the VA health care system vs 49% in the general US population), older (mean [SD], 61.0 [18.2] years in the VA health care system vs 39.0 [23.1] years in the US population), and had a larger proportion of patients who were White (73% in the VA health care system vs 61% in the US population) or Black (17% in the VA health care system vs 13% in the US population). Increases in death rates were apparent across all of the adult age groups (≥25 years) in both the VA populations and the general US population. Across all of 2020, the relative increase in death rates compared with expected values was similar for VA enrollees (risk ratio [RR], 1.20 [95% CI, 1.14-1.29]), VA active users (RR, 1.19 [95% CI, 1.14-1.26]), and the general US population (RR, 1.20 [95% CI, 1.17-1.22]). Because the prepandemic standardized mortality rates were higher in the VA populations prior to the pandemic, the absolute rates of excess mortality were higher in the VA populations. Conclusions and Relevance: In this cohort study, a comparison of excess deaths between populations suggests that active users of the VA health system had similar relative increases in mortality compared with the general US population during the first 10 months of the COVID-19 pandemic.

Antecedents to COVID-19 vaccine uptake among patients and employees in the Veterans Health Administration.

The present study sought to understand the antecedents to COVID-19 vaccination among those reporting a change in vaccine intention in order to improve COVID-19 vaccine uptake in the United States. We employed semi-structured interviews and one focus group discussion with vaccinated and unvaccinated Veterans Health Administration (VHA) employees and Veterans at three Veterans' Affairs medical centers between January and June 2021. A subset of these participants (n=21) self-reported a change in COVID-19 vaccine intention and were selected for additional analysis. We combined thematic analysis using the 5C scale (confidence, collective responsibility, complacency, calculation, constraints) as our theoretical framework with a constant comparative method from codes based on the SAGE Working Group on Vaccine Hesitancy. We generated 13 themes distributed across the 5C constructs that appeared to be associated with a change in COVID-19 vaccine intention. Themes included a trusted family member, friend or colleague in a healthcare field, a trusted healthcare professional, distrust of government or politics (confidence); duty to family and protection of others (collective responsibility); perceived health status and normative beliefs (complacency); perceived vaccine safety, perceived risk-benefit, and orientation towards deliberation (calculation); and ease of process (constraints). Key factors in promoting vaccine uptake included a desire to protect family; and conversations with as key factors in promoting vaccine uptake. Constructs from the 5C scale are useful in understanding intrapersonal changes in vaccine intentions over time, which may help public health practitioners improve future vaccine uptake.

In this study of the Veteran and VA employee population, we aimed to understand what factors led to a decision to receive a COVID-19 vaccine. As part of a quality improvement project, we interviewed individuals at three Veterans' Affairs sites in the first six months of 2021. We then used a smaller sample of 21 participants who reported a change in their intentions to receive a COVID-19 vaccine to analyze for this study. This analysis utilizes constructs from the 5C scale, which was developed to understand the conditions required for an individual to decide to receive a vaccine (confidence, collective responsibility, complacency, calculation, constraints). The coding process revealed a number of recurring themes across the interviews falling under each of the five constructs, but concepts relating to vaccine confidence (i.e., level of trust in those developing and disseminating the vaccine) were most common, and constraints (i.e., psychological and structural barriers that stand in the way of vaccination) appeared least frequently in our interviews. We found that significant motivators to receive the vaccine included a desire to protect family and conversations with trusted clinicians, particularly mental healthcare providers. Our study was unique in using the 5Cs to understand changes in vaccine changes over time. Findings show that change in vaccine attitudes is possible even in the presence of concerns and shed light on approaches that public health providers could use to improve vaccine and booster rates.

Variation in initial and continued use of primary, mental health, and specialty video care among Veterans.

OBJECTIVE: To identify which Veteran populations are routinely accessing video-based care. DATA SOURCES AND STUDY SETTING: National, secondary administrative data from electronic health records at the Veterans Health Administration (VHA), 2019-2021. STUDY DESIGN: This retrospective cohort analysis identified patient characteristics associated with the odds of using any video care; and then, among those with a previous video visit, the annual rate of video care utilization. Video care use was reported overall and stratified into care type (e.g., primary, mental health, and specialty video care) between March 10, 2020 and February 28, 2021. DATA COLLECTION: Veterans active in VA health care (>1 outpatient visit between March 11, 2019 and March 10, 2020) were included in this study. PRINCIPAL FINDINGS: Among 5,389,129 Veterans in this evaluation, approximately 27.4% of Veterans had at least one video visit. We found differences in video care utilization by type of video care: 14.7% of Veterans had at least one primary care video visit, 10.6% a mental health video visit, and 5.9% a specialty care video visit. Veterans with a history of housing instability had a higher overall rate of video care driven by their higher usage of video for mental health care compared with Veterans in stable housing. American Indian/Alaska Native Veterans had reduced odds of video visits, yet similar rates of video care when compared to White Veterans. Low-income Veterans had lower odds of using primary video care yet slightly elevated rates of primary video care among those with at least one video visit when compared to Veterans enrolled at VA without special considerations. CONCLUSIONS: Variation in video care utilization patterns by type of care identified Veteran populations that might require greater resources and support to initiate and sustain video care use. Our data support service specific outreach to homeless and American Indian/Alaska Native Veterans.

Implementation and Effectiveness of a Learning Collaborative to Improve Palliative Care for Seriously Ill Hemodialysis Patients.

BACKGROUND AND OBJECTIVES: Limited implementation of palliative care practices in hemodialysis may contribute to end-of-life care that is intensive and not patient centered. We determined whether a learning collaborative for hemodialysis center providers improved delivery of palliative care best practices. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Ten US hemodialysis centers participated in a pre-post study targeting seriously ill patients between April 2019 and September 2020. Three practices were prioritized: screening for serious illness, goals of care discussions, and use of a palliative dialysis care pathway. The collaborative educational bundle consisted of learning sessions, communication skills training, and implementation support. The primary outcome was change in the probability of complete advance care planning documentation among seriously ill patients. Health care utilization was a secondary outcome, and implementation outcomes of acceptability, adoption, feasibility, and penetration were assessed using mixed methods. RESULTS: One center dropped out due to the coronavirus disease 2019 pandemic. Among the remaining nine centers, 20% (273 of 1395) of patients were identified as seriously ill preimplementation, and 16% (203 of 1254) were identified as seriously ill postimplementation. From the preimplementation to postimplementation period, the adjusted probability of complete advance care planning documentation among seriously ill patients increased by 34.5 percentage points (95% confidence interval, 4.4 to 68.5). There was no difference in mortality or in utilization of palliative hemodialysis, hospice referral, or hemodialysis discontinuation. Screening for serious illness was widely adopted, and goals of care discussions were adopted with incomplete integration. There was limited adoption of a palliative dialysis care pathway. CONCLUSIONS: A learning collaborative for hemodialysis centers spanning the coronavirus disease 2019 pandemic was associated with adoption of serious illness screening and goals of care discussions as well as improved documentation of advance care planning for seriously ill patients. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Pathways Project: Kidney Supportive Care, NCT04125537.

Barriers and Facilitators to the Implementation of Family-Centered Technology in Complex Care: Feasibility Study.

BACKGROUND: Care coordination is challenging but crucial for children with medical complexity (CMC). Technology-based solutions are increasingly prevalent but little is known about how to successfully deploy them in the care of CMC. OBJECTIVE: The aim of this study was to assess the feasibility and acceptability of GoalKeeper (GK), an internet-based system for eliciting and monitoring family-centered goals for CMC, and to identify barriers and facilitators to implementation. METHODS: We used the Consolidated Framework for Implementation Research (CFIR) to explore the barriers and facilitators to the implementation of GK as part of a clinical trial of GK in ambulatory clinics at a children's hospital (NCT03620071). The study was conducted in 3 phases: preimplementation, implementation (trial), and postimplementation. For the trial, we recruited providers at participating clinics and English-speaking parents of CMC<12 years of age with home internet access. All participants used GK during an initial clinic visit and for 3 months after. We conducted preimplementation focus groups and postimplementation semistructured exit interviews using the CFIR interview guide. Participant exit surveys assessed GK feasibility and acceptability on a 5-point Likert scale. For each interview, 3 independent coders used content analysis and serial coding reviews based on the CFIR qualitative analytic plan and assigned quantitative ratings to each CFIR construct (-2 strong barrier to +2 strong facilitator). RESULTS: Preimplementation focus groups included 2 parents (1 male participant and 1 female participant) and 3 providers (1 in complex care, 1 in clinical informatics, and 1 in neurology). From focus groups, we developed 3 implementation strategies: education (parents: 5-minute demo; providers: 30-minute tutorial and 5-minute video on use in a clinic visit; both: instructional manual), tech support (in-person, virtual), and automated email reminders for parents. For implementation (April 1, 2019, to December 21, 2020), we enrolled 11 providers (7 female participants, 5 in complex care) and 35 parents (mean age 38.3, SD 7.8 years; n=28, 80% female; n=17, 49% Caucasian; n=16, 46% Hispanic; and n=30, 86% at least some college). One parent-provider pair did not use GK in the clinic visit, and few used GK after the visit. In 18 parent and 9 provider exit interviews, the key facilitators were shared goal setting, GK's internet accessibility and email reminders (parents), and GK's ability to set long-term goals and use at the end of visits (providers). A key barrier was GK's lack of integration into the electronic health record or patient portal. Most parents (13/19) and providers (6/9) would recommend GK to their peers. CONCLUSIONS: Family-centered technologies like GK are feasible and acceptable for the care of CMC, but sustained use depends on integration into electronic health records. TRIAL REGISTRATION: ClinicalTrials.gov NCT03620071; https://clinicaltrials.gov/ct2/show/NCT03620071.

Evaluating clinician-led quality improvement initiatives: A system-wide embedded research partnership at Stanford Medicine.

Introduction: Many healthcare delivery systems have developed clinician-led quality improvement (QI) initiatives but fewer have also developed in-house evaluation units. Engagement between the two entities creates unique opportunities. Stanford Medicine funded a collaboration between their Improvement Capability Development Program (ICDP), which coordinates and incentivizes clinician-led QI efforts, and the Evaluation Sciences Unit (ESU), a multidisciplinary group of embedded researchers with expertise in implementation and evaluation sciences. Aim: To describe the ICDP-ESU partnership and report key learnings from the first 2 y of operation September 2019 to August 2021. Methods: Department-level physician and operational QI leaders were offered an ESU consultation to workshop design, methods, and overall scope of their annual QI projects. A steering committee of high-level stakeholders from operational, clinical, and research perspectives subsequently selected three projects for in-depth partnered evaluation with the ESU based on evaluability, importance to the health system, and broader relevance. Selected project teams met regularly with the ESU to develop mixed methods evaluations informed by relevant implementation science frameworks, while aligning the evaluation approach with the clinical teams' QI goals. Results: Sixty and 62 ICDP projects were initiated during the 2 cycles, respectively, across 18 departments, of which ESU consulted with 15 (83%). Within each annual cycle, evaluators made actionable, summative findings rapidly available to partners to inform ongoing improvement. Other reported benefits of the partnership included rapid adaptation to COVID-19 needs, expanded clinician evaluation skills, external knowledge dissemination through scholarship, and health system-wide knowledge exchange. Ongoing considerations for improving the collaboration included the need for multi-year support to enable nimble response to dynamic health system needs and timely data access. Conclusion: Presence of embedded evaluation partners in the enterprise-wide QI program supported identification of analogous endeavors (eg, telemedicine adoption) and cross-cutting lessons across QI efforts, clinician capacity building, and knowledge dissemination through scholarship.

Teledermatology to Facilitate Patient Care Transitions From Inpatient to Outpatient Dermatology: Mixed Methods Evaluation.

BACKGROUND: Both clinicians and patients have increasingly turned to telemedicine to improve care access, even in physical examination-dependent specialties such as dermatology. However, little is known about whether teledermatology supports effective and timely transitions from inpatient to outpatient care, which is a common care coordination gap. OBJECTIVE: Using mixed methods, this study sought to retrospectively evaluate how teledermatology affected clinic capacity, scheduling efficiency, and timeliness of follow-up care for patients transitioning from inpatient to outpatient dermatology care. METHODS: Patient-level encounter scheduling data were used to compare the number and proportion of patients who were scheduled and received in-clinic or video dermatology follow-ups within 14 and 90 days after discharge across 3 phases: June to September 2019 (before teledermatology), June to September 2020 (early teledermatology), and February to May 2021 (sustained teledermatology). The time from discharge to scheduling and completion of patient follow-up visits for each care modality was also compared. Dermatology clinicians and schedulers were also interviewed between April and May 2021 to assess their perceptions of teledermatology for postdischarge patients. RESULTS: More patients completed follow-up within 90 days after discharge during early (n=101) and sustained (n=100) teledermatology use than at baseline (n=74). Thus, the clinic's capacity to provide follow-up to patients transitioning from inpatient increased from baseline by 36% in the early (101 from 74) and sustained (100 from 74) teledermatology periods. During early teledermatology use, 61.4% (62/101) of the follow-ups were conducted via video. This decreased significantly to 47% (47/100) in the following year, when COVID-19-related restrictions started to lift (P=.04), indicating more targeted but still substantial use. The proportion of patients who were followed up within the recommended 14 days after discharge did not differ significantly between video and in-clinic visits during the early (33/62, 53% vs 15/39, 38%; P=.15) or sustained (26/53, 60% vs 28/47, 49%; P=.29) teledermatology periods. Interviewees agreed that teledermatology would continue to be offered. Most considered postdischarge follow-up patients to be ideal candidates for teledermatology as they had undergone a recent in-person assessment and might have difficulty attending in-clinic visits because of competing health priorities. Some reported patients needing technological support. Ultimately, most agreed that the choice of follow-up care modality should be the patient's own. CONCLUSIONS: Teledermatology could be an important tool for maintaining accessible, flexible, and convenient care for recently discharged patients needing follow-up care. Teledermatology increased clinic capacity, even during the pandemic, although the timeliness of care transitions did not improve. Ultimately, the care modality should be determined through communication with patients to incorporate their and their caregivers' preferences.

Patient and Clinician Perspectives of New and Return Ambulatory Teleneurology Visits.

BACKGROUND AND OBJECTIVES: To evaluate the adoption and perceived utility of video visits for new and return patient encounters in ambulatory neurology subspecialties. METHODS: Video visits were launched in an academic, multi-subspecialty, ambulatory neurology clinic in March 2020. Adoption of video visits for new and return patient visits was assessed using clinician-level scheduling data from March 22 to May 16, 2020. Perceived utility of video visits was explored via a clinician survey and semistructured interviews with clinicians and patients/caregivers. Findings were compared across 5 subspecialties and 2 visit types (new vs return). RESULTS: Video visits were adopted rapidly; all clinicians (n = 65) integrated video visits into their workflow within the first 6 weeks, and 92% of visits were conducted via video, although this varied by subspecialty. Utility of video visits was higher for return than new patient visits, as indicated by surveyed (n = 48) and interviewed clinicians (n = 30), aligning with adoption patterns. Compared with in-person visits, clinicians believed that it was easier to achieve a similar physical examination, patient-clinician rapport, and perceived quality of care over video for return rather than new patient visits. Of the 25 patients/caregivers interviewed, most were satisfied with the care provided via video, regardless of visit type, with the main limitation being the physical examination. DISCUSSION: Teleneurology was robustly adopted for both new and return ambulatory neurology patients during the COVID-19 pandemic. Return patient visits were preferred over new patient visits, but both were feasible. These results provide a foundation for developing targeted guidelines for sustaining teleneurology in ambulatory care.

Attitudes and Intentions of US Veterans Regarding COVID-19 Vaccination.

Importance: Compared with the general population, veterans are at high risk for COVID-19 and have a complex relationship with the government. This potentially affects their attitudes toward receiving COVID-19 vaccines. Objective: To assess veterans' attitudes toward and intentions to receive COVID-19 vaccines. Design, Setting, and Participants: This cross-sectional web-based survey study used data from the Department of Veterans Affairs (VA) Survey of Healthcare Experiences of Patients' Veterans Insight Panel, fielded between March 12 and 28, 2021. Of 3420 veterans who were sent a link to complete a 58-item web-based survey, 1178 veterans (34%) completed the survey. Data were analyzed from April 1 to August 25, 2021. Exposures: Veterans eligible for COVID-19 vaccines. Main Outcomes and Measures: The outcomes of interest were veterans' experiences with COVID-19, vaccination status and intention groups, reasons for receiving or not receiving a vaccine, self-reported health status, and trusted and preferred sources of information about COVID-19 vaccines. Reasons for not getting vaccinated were classified into categories of vaccine deliberation, dissent, distrust, indifference, skepticism, and policy and processes. Results: Among 1178 respondents, 974 (83%) were men, 130 (11%) were women, and 141 (12%) were transgender or nonbinary; 58 respondents (5%) were Black, 54 veterans (5%) were Hispanic or Latino, and 987 veterans (84%) were non-Hispanic White. The mean (SD) age of respondents was 66.7 (10.1) years. A total of 817 respondents (71%) self-reported being vaccinated against COVID-19. Of 339 respondents (29%) who were not vaccinated, those unsure of getting vaccinated were more likely to report fair or poor overall health (32 respondents [43%]) and mental health (33 respondents [44%]) than other nonvaccinated groups (overall health: range, 20%-32%; mental health: range, 18%-40%). Top reasons for not being vaccinated were skepticism (120 respondents [36%] were concerned about side effects; 65 respondents [20%] preferred using few medications; 63 respondents [19%] preferred gaining natural immunity), deliberation (74 respondents [22%] preferred to wait because vaccine is new), and distrust (61 respondents [18%] did not trust the health care system). Among respondents who were vaccinated, preventing oneself from getting sick (462 respondents [57%]) and contributing to the end of the COVID-19 pandemic (453 respondents [56%]) were top reasons for getting vaccinated. All veterans reported the VA as 1 of their top trusted sources of information. The proportion of respondents trusting their VA health care practitioner as a source of vaccine information was higher among those unsure about vaccination compared with those who indicated they would definitely not or probably not get vaccinated (18 respondents [26%] vs 15 respondents [15%]). There were no significant associations between vaccine intention groups and age (χ24 = 5.90; P = .21) or gender (χ22 = 3.99; P = .14). Conclusions and Relevance: These findings provide information needed to develop trusted messages used in conversations between VA health care practitioners and veterans addressing specific vaccine hesitancy reasons, as well as those in worse health. Conversations need to emphasize societal reasons for getting vaccinated and benefits to one's own health.

Developing best practices for PPE Portraits across 25 sites: a systematic assessment of implementation and spread of adaptations using FRAME.

BACKGROUND: Adaptation, a form of modification that aims to improve an intervention's acceptability and sustainability in each context, is essential to successful implementation in some settings. Due to the COVID-19 pandemic, clinicians have rapidly adapted how they deliver patient care. PPE Portraits are a form of adaptation, whereby health workers affix a postcard size portrait of themselves to the front of their personal protective equipment (PPE) to foster human connection during COVID-19. METHODS: We used the expanded framework for reporting adaptations and modifications to evidence-based interventions (FRAME) method to better understand the reasoning behind and results of each adaptation. We hypothesized that using the FRAME in conjunction with design-thinking would lead to emerging best practices and that we would find adaptation similarities across sites. Throughout multiple implementations across 25 institutions, we piloted, tracked, and analyzed adaptations using FRAME and design thinking. For each adaptation, we assessed the stage of implementation, whether the change was planned, decision makers involved, level of delivery impacted, fidelity to original intervention, and the goal and reasoning for adaptation. We added three crucial components to the FRAME: original purpose of the adaptation, unintended consequences, and alternative adaptations. RESULTS: When implementing PPE Portraits across settings, from a local assisted living center's memory unit to a pediatric emergency department, several requests for adaptations arose during early development stages before implementation. Adaptations primarily related to (1) provider convenience and comfort, (2) patient populations, and (3) scale. Providers preferred smaller portraits and rounded (rather than square) laminated edges that could potentially injure a patient. Affixing the portrait with a magnet was rejected given the potential choking hazard the magnetic strip presented for children. Other adaptations, related to ease of dissemination, included slowing the process down during early development and providing buttons, which could be produced easily at scale. CONCLUSIONS: The FRAME was used to curate the reasoning for each adaptation and to inform future dissemination. We look forward to utilizing FRAME including our additions and design thinking, to build out a range of PPE Portrait best practices with accompanying costs and benefits.

Vaccine hesitancy as an opportunity for engagement: A rapid qualitative study of patients and employees in the U.S. Veterans Affairs healthcare system.

Although COVID-19 vaccines have been available to many U.S. Veterans Affairs (VA) healthcare system employees and Veteran patients since early 2021, vaccine receipt data indicates some groups are not receiving them. Our objective was to conduct a rapid qualitative assessment of Veterans' and VA employees' views on COVID-19 vaccination to inform clinical leaders' ongoing efforts to increase vaccine uptake across the VA. We employed semi-structured interviews and a focus group involving employees and Veterans as part of a quality improvement project between January and June 2021 at three VA medical centers. Thirty-one employees and 27 Veterans participated in semi-structured interviews; 5 Veterans from a national stakeholder organization participated in a focus group. Data were analyzed using directed content analysis, involving an a priori coding framework comprised of four domains with subcodes under each: contextual influences, barriers and facilitators, vaccine-specific issues, and VA/military experiences. We then classified initial codes into five categories of hesitancy: vaccine deliberation, dissent, distrust, indifference and skepticism. A subset of Veterans (n = 14) and employees (n = 8) identified as vaccine hesitant. Vaccine hesitancy categories were represented by subcodes of religion, culture, gender or socio-economic factors, perceptions of politics and policies, role of healthcare providers, and historical influences; (contextual influences); knowledge or awareness of vaccines, perceived susceptibility to COVID-19, and beliefs and attitudes about health and illness (barriers and facilitators); vaccine development process (vaccine-specific issues) and military experiences (VA/military factors). Facilitators involved talking with trusted others, ease of vaccine access, and perceptions of family and societal benefits of vaccines. Vaccine hesitancy is multi-faceted and likely requires multiple strategies for engaging in conversations to address Veteran and VA employee concerns. Messages should involve patient-centered communication strategies delivered by trusted healthcare providers and peers and should focus on addressing expected benefits for family, friends, and society.

Technology-Enabled and Artificial Intelligence Support for Pre-Visit Planning in Ambulatory Care: Findings From an Environmental Scan.

PURPOSE: Pre-visit planning (PVP) is believed to improve effectiveness, efficiency, and experience of care, yet numerous implementation barriers exist. There are opportunities for technology-enabled and artificial intelligence (AI) support to augment existing human-driven PVP processes-from appointment reminders and pre-visit questionnaires to pre-visit order sets and care gap closures. This study aimed to explore the current state of PVP, barriers to implementation, evidence of impact, and potential use of non-AI and AI tools to support PVP. METHODS: We used an environmental scan approach involving: (1) literature review; (2) key informant interviews with PVP experts in ambulatory care; and (3) a search of the public domain for technology-enabled and AI solutions that support PVP. We then synthesized the findings using a qualitative matrix analysis. RESULTS: We found 26 unique PVP implementations in the literature and conducted 16 key informant interviews. Demonstration of impact is typically limited to process outcomes, with improved patient outcomes remaining elusive. Our key informants reported that many PVP barriers are human effort-related and see potential for non-AI and AI technologies to support certain aspects of PVP. We identified 8 examples of commercially available technology-enabled tools that support PVP, some with AI capabilities; however, few of these have been independently evaluated. CONCLUSIONS: As health systems transition toward value-based payment models in a world where the coronavirus disease 2019 pandemic has shifted patient care into the virtual space, PVP activities-driven by humans and supported by technology-may become more important and powerful and should be rigorously evaluated.

A Specialized Acute COVID-19 Outpatient Clinic at an Academic Medical Center.

Health systems are challenged to provide equitable access to coronavirus disease 2019 (COVID-19) outpatient care during the pandemic. Infected patients may have difficulties accessing regular care and rely on emergency rooms. With the goal to improve system efficiencies and access to care, Stanford launched a designated outpatient COVID-19 "Care and Respiratory Observation of Patients With Novel Coronavirus" clinic in April 2020 in which all adult Stanford patients with newly diagnosed severe acute respiratory syndrome coronavirus 2 were offered follow-up for 2-3 weeks through video, telephone, and in-person encounters. Patients were triaged into risk categories and received home pulse oximeters based on a standardized protocol. Between April 15, 2020, and March 26, 2021, the Care and Respiratory Observation of Patients With Novel Coronavirus clinic enrolled 1317 patients. The clinic provided evaluation of Patients under Investigation, management of acute COVID-19 symptoms, care for COVID-19 patients after hospital discharge, clinical advice, and opportunities for research. The authors share crucial implementation lessons related to team agility, care personalization, and resource optimization.

Inpatient Telemedicine Implementation as an Infection Control Response to COVID-19: Qualitative Process Evaluation Study.

BACKGROUND: The COVID-19 pandemic created new challenges to delivering safe and effective health care while minimizing virus exposure among staff and patients without COVID-19. Health systems worldwide have moved quickly to implement telemedicine in diverse settings to reduce infection, but little is understood about how best to connect patients who are acutely ill with nearby clinical team members, even in the next room. OBJECTIVE: To inform these efforts, this paper aims to provide an early example of inpatient telemedicine implementation and its perceived acceptability and effectiveness. METHODS: Using purposive sampling, this study conducted 15 semistructured interviews with nurses (5/15, 33%), attending physicians (5/15, 33%), and resident physicians (5/15, 33%) on a single COVID-19 unit within Stanford Health Care to evaluate implementation outcomes and perceived effectiveness of inpatient telemedicine. Semistructured interview protocols and qualitative analysis were framed around the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework, and key themes were identified using a rapid analytic process and consensus approach. RESULTS: All clinical team members reported wide reach of inpatient telemedicine, with some use for almost all patients with COVID-19. Inpatient telemedicine was perceived to be effective in reducing COVID-19 exposure and use of personal protective equipment (PPE) without significantly compromising quality of care. Physician workflows remained relatively stable, as most standard clinical activities were conducted via telemedicine following the initial intake examination, though resident physicians reported reduced educational opportunities given limited opportunities to conduct physical exams. Nurse workflows required significant adaptations to cover nonnursing duties, such as food delivery and facilitating technology connections for patients and physicians alike. Perceived patient impact included consistent care quality, with some considerations around privacy. Reported challenges included patient-clinical team communication and personal connection with the patient, perceptions of patient isolation, ongoing technical challenges, and certain aspects of the physical exam. CONCLUSIONS: Clinical team members reported inpatient telemedicine encounters to be acceptable and effective in reducing COVID-19 exposure and PPE use. Nurses adapted their workflows more than physicians in order to implement the new technology and bore a higher burden of in-person care and technical support. Recommendations for improved inpatient telemedicine use include information technology support and training, increased technical functionality, and remote access for the clinical team.

An App-Based Intervention to Support First Responders and Essential Workers During the COVID-19 Pandemic: Needs Assessment and Mixed Methods Implementation Study.

BACKGROUND: The COVID-19 pandemic has created unprecedented challenges for first responders (eg, police, fire, and emergency medical services) and nonmedical essential workers (eg, workers in food, transportation, and other industries). Health systems may be uniquely suited to support these workers given their medical expertise, and mobile apps can reach local communities despite social distancing requirements. Formal evaluation of real-world mobile app-based interventions is lacking. OBJECTIVE: We aimed to evaluate the adoption, acceptability, and appropriateness of an academic medical center-sponsored app-based intervention (COVID-19 Guide App) designed to support access of first responders and essential workers to COVID-19 information and testing services. We also sought to better understand the COVID-19-related needs of these workers early in the pandemic. METHODS: To understand overall community adoption, views and download data of the COVID-19 Guide App were described. To understand the adoption, appropriateness, and acceptability of the app and the unmet needs of workers, semistructured qualitative interviews were conducted by telephone, by video, and in person with first responders and essential workers in the San Francisco Bay Area who were recruited through purposive, convenience, and snowball sampling. Interview transcripts and field notes were qualitatively analyzed and presented using an implementation outcomes framework. RESULTS: From its launch in April 2020 to September 2020, the app received 8262 views from unique devices and 6640 downloads (80.4% conversion rate, 0.61% adoption rate across the Bay Area). App acceptability was mixed among the 17 first responders interviewed and high among the 10 essential workers interviewed. Select themes included the need for personalized and accurate information, access to testing, and securing personal safety. First responders faced additional challenges related to interprofessional coordination and a "culture of heroism" that could both protect against and exacerbate health vulnerability. CONCLUSIONS: First responders and essential workers both reported challenges related to obtaining accurate information, testing services, and other resources. A mobile app intervention has the potential to combat these challenges through the provision of disease-specific information and access to testing services but may be most effective if delivered as part of a larger ecosystem of support. Differentiated interventions that acknowledge and address the divergent needs between first responders and non-first responder essential workers may optimize acceptance and adoption.

Learning from past respiratory failure patients to triage COVID-19 patient ventilator needs: A multi-institutional study.

BACKGROUND: Unlike well-established diseases that base clinical care on randomized trials, past experiences, and training, prognosis in COVID19 relies on a weaker foundation. Knowledge from other respiratory failure diseases may inform clinical decisions in this novel disease. The objective was to predict 48-hour invasive mechanical ventilation (IMV) within 48 h in patients hospitalized with COVID-19 using COVID-like diseases (CLD). METHODS: This retrospective multicenter study trained machine learning (ML) models on patients hospitalized with CLD to predict IMV within 48 h in COVID-19 patients. CLD patients were identified using diagnosis codes for bacterial pneumonia, viral pneumonia, influenza, unspecified pneumonia and acute respiratory distress syndrome (ARDS), 2008-2019. A total of 16 cohorts were constructed, including any combinations of the four diseases plus an exploratory ARDS cohort, to determine the most appropriate cohort to use. Candidate predictors included demographic and clinical parameters that were previously associated with poor COVID-19 outcomes. Model development included the implementation of logistic regression and three ensemble tree-based algorithms: decision tree, AdaBoost, and XGBoost. Models were validated in hospitalized COVID-19 patients at two healthcare systems, March 2020-July 2020. ML models were trained on CLD patients at Stanford Hospital Alliance (SHA). Models were validated on hospitalized COVID-19 patients at both SHA and Intermountain Healthcare. RESULTS: CLD training data were obtained from SHA (n = 14,030), and validation data included 444 adult COVID-19 hospitalized patients from SHA (n = 185) and Intermountain (n = 259). XGBoost was the top-performing ML model, and among the 16 CLD training cohorts, the best model achieved an area under curve (AUC) of 0.883 in the validation set. In COVID-19 patients, the prediction models exhibited moderate discrimination performance, with the best models achieving an AUC of 0.77 at SHA and 0.65 at Intermountain. The model trained on all pneumonia and influenza cohorts had the best overall performance (SHA: positive predictive value (PPV) 0.29, negative predictive value (NPV) 0.97, positive likelihood ratio (PLR) 10.7; Intermountain: PPV, 0.23, NPV 0.97, PLR 10.3). We identified important factors associated with IMV that are not traditionally considered for respiratory diseases. CONCLUSIONS: The performance of prediction models derived from CLD for 48-hour IMV in patients hospitalized with COVID-19 demonstrate high specificity and can be used as a triage tool at point of care. Novel predictors of IMV identified in COVID-19 are often overlooked in clinical practice. Lessons learned from our approach may assist other research institutes seeking to build artificial intelligence technologies for novel or rare diseases with limited data for training and validation.