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Michael J Maniaci,1 J Colt Cowdell,1 Karla Maita,2 Francisco R Avila,2 Sagar B Dugani,3 Ricardo A Torres-Guzman,2 John P Garcia,2 Antonio J Forte,2 Margaret R Paulson4 1Division of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA; 2Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA; 3Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA; 4Division of Hospital Internal Medicine, Mayo Clinic Health Systems, Eau Claire, WI, USACorrespondence: Michael J Maniaci, Division of Hospital Internal Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA, Tel +1 904-956-0081, Fax +1 904-953-2848, Email Maniaci.Michael@mayo.eduBackground: The diagnosis related group (DRG) is used as an economic patient classification system based on clinical characteristics, hospital stay, and treatment costs. Mayo Clinic’s virtual hybrid hospital-at-home program, advanced care at home (ACH), offers high-acuity home inpatient care for a variety of diagnosis. This study aimed to determine the DRGs admitted to the ACH program at an urban academic center.Methods: A retrospective study was performed on all patients discharged from the ACH program at Mayo Clinic Florida from July 6, 2020, to February 1, 2022. DRG data were extracted from the Electronic Health Record (EHR). Categorization of DRG was done by systems.Results: The ACH program discharged 451 patients with DRGs. Categorization of the DRG demonstrated that the most frequent code assigned corresponded to respiratory infections (20.2%), followed by septicemia (12.9%), heart failure (8.9%), renal failure (4.9%), and cellulitis (4.0%).Conclusion: The ACH program covers a wide range of high-acuity diagnosis across multiple medical specialties at its urban academic medical campus, including respiratory infections, severe sepsis, congestive heart failure, and renal failure, all with major complications or comorbidities. The ACH model of care may be useful in taking care of patients with similar diagnosis at other urban academic medical institutions.Keywords: hospital at home, home care, home acute care, diagnosis related group, inpatient prospective payment system

Michael J Maniaci,1 Karla Maita,2 Ricardo A Torres-Guzman,2 Francisco R Avila,2 John P Garcia,2 Abdullah Eldaly,2 Antonio J Forte,2 Gautam V Matcha,1 Ricardo J Pagan,1 Margaret R Paulson3 1Division of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, USA; 2Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA; 3Division of Hospital Internal Medicine, Mayo Clinic Health Systems, Eau Claire, WI, USACorrespondence: Michael J Maniaci, Division of Hospital Internal Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA, Tel +1 904-956-0081, Fax +1904-953-2848, Email Maniaci.Michael@mayo.eduBackground: Healthcare provider’s experience with new models of care is crucial for long-term success. In July 2020, Mayo Clinic implemented a novel virtual hybrid hospital at home program called Advanced Care at Home (ACH). This model allows virtual providers in a command center to care for high-acuity patients in the home setting through collaboration with a vendor-mediated supply chain. This study aims to describe the outcomes obtained from a survey applied to the ACH providers to determine their acceptance of the quality and safety of the virtual hybrid care model, their perception towards the decision-making and teamwork between the command center and supplier network, and determine if the overall experience with ACH was rewarding.Methods: A 15-question anonymous survey was distributed via email quarterly to all the physicians and nurse practitioners registered in ACH program at Mayo Clinic. The survey encompassed questions related to the overall experience in ACH concerning work environment, quality of care, service reliability, teamwork, decision-making, and satisfaction. All the questions were Likert-like scale choice, and a descriptive analysis using frequency distribution and percentages of the data was performed.Results: Between September 1, 2020 and April 30, 2021, three quarterly surveys were sent to a total of 21 physicians and nurse practitioners caring for patients virtually in ACH. The response rate reported was 72%, 33%, and 66%, respectively, at the first, second, and third quarters. Eighty percent or more of providers consistently gave positive scores to all three areas analyzed throughout the 8-month study.Conclusion: Providers found the ACH virtual hybrid model of home hospital care very rewarding. They were able to deliver high-quality and safe care to their patients through positive teamwork with a vendor-mediated supply chain. This novel model of hospital at home has the potential to be a great provider satisfier moving forward.Keywords: telemedicine, virtual hybrid, hospital home, home healthcare, provider satisfaction

Michael P Boniface,1 Scott A Helgeson,2 Jed C Cowdell,2 Leslie V Simon,1 Brett T Hiroto,2 Monia E Werlang,2 Sarah W Robison,2 Grace G Edwards,3,4 Michele D Lewis,2 Michael J Maniaci2 1Department of Emergency Medicine, Mayo Clinic, Jacksonville, FL, USA; 2Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, USA; 3Department of Education, Mayo Clinic, Jacksonville, FL, USA; 4The Mayo Clinic School of Health Sciences, Mayo Clinic College of Medicine and Science, Rochester, MN, USACorrespondence: Michael J ManiaciDepartment of Internal Medicine, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USAFax +904-953-0007Email maniaci.michael@mayo.eduPurpose: Despite its growing popularity and clinical utility among hospital-based physicians, there are no formal competency requirements nor training standards for United States based Internal Medicine Residencies for learning point-of-care ultrasonography (POCUS). The purpose of this investigation was to study the impact and effectiveness of a novel POCUS curriculum for an Internal Medicine (IM) residency program.Patients and methods: This was a Single-Group Educational Quasi-Experiment involving Categorical and Preliminary Internal Medicine Residents in Post-Graduate Years 1 through 3 at a single United States academic tertiary center. The study period was from January 1, 2017, through June 30, 2017, during which time the residents participated in monthly modules including didactics and hands-on ultrasound scanning skills with live models. Participants completed a comprehensive knowledge examination at the beginning and end of the six-month period. Participants were also tested regarding hands-on image acquisition and interpretation immediately before and after the hands-on skills labs. The primary outcome measure was performance improvement in a comprehensive medical knowledge assessment.Results: In total, 42 residents consented for participation. The residents’ monthly rotations were adjusted in order to accommodate the new educational process. Among 29 participants with complete data sets for analysis, the mean (SD) comprehensive knowledge examination score improved from 60.9% before curriculum to 70.2% after curriculum completion (P

Ali A Alsaad,1 Swetha Davuluri,2 Vandana Y Bhide,3 Amy M Lannen,4 Michael J Maniaci3 1Department of Internal Medicine, Mayo Clinic, 2University of Miami, Coral Gables, 3Division of Hospital Internal Medicine, 4J. Wayne and Delores Barr Weaver Simulation Center, Mayo Clinic, Jacksonville, FL, USA Background: Conducting simulations of rapidly decompensating patients are a key part of internal medicine (IM) residency training. Traditionally, mannequins have been the simulation tool used in these scenarios. Objective: To compare IM residents’ performance and assess realism in specific-simulated decompensating patient scenarios using standardized patients (SPs) as compared to mannequin. Methods: Nineteen IM residents were randomized to undergo simulations using either a mannequin or an SP. Each resident in the two groups underwent four different simulation scenarios (calcium channel blocker overdose, severe sepsis, severe asthma exacerbation, and acute bacterial meningitis). Residents completed pretest and post-test evaluations as well as a questionnaire to assess the reality perception (realism score). Results: Nine residents completed mannequin-based scenarios, whereas 10 completed SP-based scenarios. Improvement in the post-test scores was seen in both groups. However, there were significantly higher post-test scores achieved with SP simulations in three out of the four scenarios (P=0.01). When compared with the mannequin group, the SP simulation group showed a significantly higher average realism score (P=0.002). Conclusions: Applying SP-based specific-simulation scenarios in IM residency training may result in better performance and a higher sense of a realistic experience by medical residents. Keywords: simulation, standardized patient, satisfaction, mannequin, assessment, resident education

The objective of this study was to evaluate patient knowledge of newly prescribed medication after hospital discharge. We reviewed the charts of 172 patients who were discharged from February 1, 2006, through April 25, 2006, from the internal medicine residency service at a community-based teaching hospital with prescriptions for 1 or more new medications. Between 4 and 18 days after discharge, patients were contacted by telephone and asked about the name, number, dosages, schedule, purpose, and adverse effects of the new medication(s) and whether they could name their medical contact person. We recorded the number of correct answers, patient age, and years of education. Of the survey respondents, 86% were aware that they had been prescribed new medications, but fewer could identify the name (64%) or number (74%) of new medications or their dosages (56%), schedule (68%), or purpose (64%). Only 11% could recall being told of any adverse effects, and only 22% could name at least 1 adverse effect. Older patients tended to answer fewer questions correctly (P=.02). We observed no association between the number of correctly answered questions and years of education (P=.57), time between discharge and survey (P=.17), or number of new medications (P=.65). Overall, we found that patients had limited knowledge about their medications after discharge from an internal medicine residency service, with age but not years of education significantly associated with level of knowledge. [ABSTRACT FROM AUTHOR]

Objectives: Mayo Clinic's hospital-at-home program, Advanced Care at Home (ACH), launched in 2020. While hospital-at-home literature reported safe and effective care for the general patient population and those with COVID, comparative outcomes between these two groups were unknown. The aim of this retrospective analysis was to compare the outcomes of COVID and non-COVID patients enrolled in ACH and evaluate if COVID patients can be safely treated in this setting., Methods: Demographics, clinical characteristics, and safety outcomes were retrospectively analyzed to compare COVID and non-COVID patients discharged from ACH between November 2020 and May 2022. Patient characteristics analyzed included severity of illness (SOI) and risk of mortality (ROM), calculated using All Patient Refined Diagnosis Related Groups (APR-DRG). Hospitalization-specific variables included length of stay (LOS), escalation of care, and 30-day readmission rates., Results: Of 1051 patients, 173 (16%) had COVID, and 878 (84%) were non-COVID patients. The average age in the COVID cohort was 66.6 (15.3) years, compared with 72.2 (14.0) in the non-COVID cohort. Extreme SOI was higher in the COVID group (43.3% versus 17.4%), as was extreme ROM (46.2% versus 16.2%), but LOS was shorter (5.7 versus 7 days). Escalation of care (7.5% in COVID cohort versus 8.4%) and 30-day readmission outcomes (9.2% for COVID patients versus 12.9%) were not statistically different between the groups., Conclusions: Despite higher SOI and ROM, COVID patients had shorter LOS with outcomes that were not statistically different from non-COVID patients. COVID patients can be safely and efficiently cared for in ACH., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Digital health tools can improve health care access and outcomes for individuals with limited access to health care, particularly those residing in rural areas. This scoping review examines the existing literature on using digital tools in patients with limited access to health care in rural areas. It assesses their effectiveness in improving health outcomes. The review adopts a comprehensive search strategy to identify relevant studies from electronic databases, and the selected studies are analyzed descriptively. The findings highlight the advantages and barriers of digital health interventions in rural populations. The advantages include increased access to health care practitioners through teleconsultations, improved health care outcomes through remote monitoring, better disease management through mobile health applications and wearable devices, and enhanced access to specialized care and preventive programs. However, limited internet connectivity and a lack of familiarity with digital tools are barriers that must be addressed to ensure equitable access to digital health interventions in rural areas. Overall, digital tools improve health outcomes for individuals with limited health care access in rural areas., Competing Interests: Conflicts of Interest None declared

Background: Hospital-at-home (H@H) models have gained recognition as a safe and potentially cost-effective solution for the current rising global healthcare needs. However, despite these models' potential, their adoption has been limited partly due to patients refusing care at home. This systematic review analyses the reasons behind their refusal., Methods: We searched five databases: Embase, Google Scholar, PubMed, Scopus, and Web of Science, limiting our search to papers from 2005 to 2024. Our search focused on papers reporting patient-provided reasons for declining treatment in a H@H setting without language or country restrictions. In addition to reasons for refusal, we extracted patient demographics and predictors for refusal to ensure a broad understanding of the factors influencing patient decisions. The quality of the studies included was evaluated using the Mixed Methods Appraisal Tool (MMAT) version 2018., Results: From the 1,067 articles identified, seven met our inclusion criteria. The papers reported reasons from 418 patients participating in diverse H@H models from the United States, United Kingdom, Spain, and Singapore, primarily focusing on acute home-based care. The most common reasons for declination included concerns about model effectiveness, safety at home, preference for in-hospital care, physician advice, family burden, and visitor concerns. Additionally, common significant demographic factors associated with decliners were the enrollment site, partnership or marital status, risk of adverse outcomes, and previous healthcare utilization., Conclusions: Understanding patients' motivations for declining H@H is crucial for its successful implementation. Targeted communication strategies and collaboration between healthcare providers are paramount to ensure that patients understand the benefits and safety of H@H models. Future research should explore effective communication and engagement techniques to address patient apprehensions and broaden H@H adoption., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-23/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Background: The association between rurality of patients' residence and hospital experience is incompletely described. The objective of the study was to compare hospital experience by rurality of patients' residence., Methods: From a US Midwest institution's 17 hospitals, we included 56,685 patients who returned a post-hospital Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. We defined rurality using rural-urban commuting area codes (metropolitan, micropolitan, small town, rural). We evaluated the association of patient characteristics with top-box score (favorable response) for 10 HCAHPS items (six composite, two individual, two global). We obtained adjusted odds ratios (aOR [95% CI]) from logistic regression models including patient characteristics. We used key driver analysis to identify associations between HCAHPS items and global rating (combined overall rating of hospital and recommend hospital)., Results: Of all items, overall rating of hospital had lower odds of favorable response for patients from metropolitan (0.88 [0.81-0.94]), micropolitan (0.86 [0.79-0.94]), and small towns (0.90 [0.82-0.98]) compared with rural areas (global test, P = .003). For five items, lower odds of favorable response was observed for select areas compared with rural; for example, recommend hospital for patients from micropolitan (0.88 [0.81-0.97]) but not metropolitan (0.97 [0.89-1.05]) or small towns (0.93 [0.85-1.02]). For four items, rurality showed no association. In metropolitan, micropolitan, and small towns, men vs. women had higher odds of favorable response to most items, whereas in rural areas, sex-based differences were largely absent. Key driver analysis identified care transition, communication about medicines and environment as drivers of global rating, independent of rurality., Conclusions: Rural patients reported similar or modestly more favorable hospital experience. Determinants of favorable experience across rurality categories may inform system-wide and targeted improvement., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Fawad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The primary objective of this study was to develop a risk-based readmission prediction model using the EMR data available at discharge. This model was then validated with the LACE plus score. The study cohort consisted of about 310,000 hospital admissions of patients with cardiovascular and cerebrovascular conditions. The EMR data of the patients consisted of lab results, vitals, medications, comorbidities, and admit/discharge settings. These data served as the input to an XGBoost model v1.7.6, which was then used to predict the number of days until the next readmission. Our model achieved remarkable results, with a precision score of 0.74 (±0.03), a recall score of 0.75 (±0.02), and an overall accuracy of approximately 82% (±5%). Notably, the model demonstrated a high accuracy rate of 78.39% in identifying the patients readmitted within 30 days and 80.81% accuracy for those with readmissions exceeding six months. The model was able to outperform the LACE plus score; of the people who were readmitted within 30 days, only 47.70 percent had a LACE plus score greater than 70, and, for people with greater than 6 months, only 10.09 percent had a LACE plus score less than 30. Furthermore, our analysis revealed that the patients with a higher comorbidity burden and lower-than-normal hemoglobin levels were associated with increased readmission rates. This study opens new doors to the world of differential patient care, helping both clinical decision makers and healthcare providers make more informed and effective decisions. This model is comparatively more robust and can potentially substitute the LACE plus score in cardiovascular and cerebrovascular settings for predicting the readmission risk.

This study aims to explore how artificial intelligence can help ease the burden on caregivers, filling a gap in current research and healthcare practices due to the growing challenge of an aging population and increased reliance on informal caregivers. We conducted a search with Google Scholar, PubMed, Scopus, IEEE Xplore, and Web of Science, focusing on AI and caregiving. Our inclusion criteria were studies where AI supports informal caregivers, excluding those solely for data collection. Adhering to PRISMA 2020 guidelines, we eliminated duplicates and screened for relevance. From 947 initially identified articles, 10 met our criteria, focusing on AI's role in aiding informal caregivers. These studies, conducted between 2012 and 2023, were globally distributed, with 80% employing machine learning. Validation methods varied, with Hold-Out being the most frequent. Metrics across studies revealed accuracies ranging from 71.60% to 99.33%. Specific methods, like SCUT in conjunction with NNs and LibSVM, showcased accuracy between 93.42% and 95.36% as well as F-measures spanning 93.30% to 95.41%. AUC values indicated model performance variability, ranging from 0.50 to 0.85 in select models. Our review highlights AI's role in aiding informal caregivers, showing promising results despite different approaches. AI tools provide smart, adaptive support, improving caregivers' effectiveness and well-being.

Home hospital programs continue to grow across the United States. There are limited studies around the process of patient selection and successful acquisition from the emergency department. The article describes how an interdisciplinary team used quality improvement methodology to significantly increase the number of admissions directly from the emergency department to the Advanced Care at Home program., (Copyright © 2024 the American College of Medical Quality.)

Background: Hospital-at-home (HaH) is a growing model of care that has been shown to improve patient outcomes, satisfaction, and cost-effectiveness. However, selecting appropriate patients for HaH is challenging, often requiring burdensome manual screening by clinicians. To facilitate HaH enrollment, electronic health record (EHR) tools such as best practice advisories (BPAs) can be used to alert providers of potential HaH candidates., Objective: To describe the development and implementation of a BPA for identifying HaH eligible patients in Mayo Clinic's Advanced Care at Home (ACH) program, and to evaluate the provider response and the patient characteristics that triggered the BPA., Design, Setting, and Participants: We conducted a retrospective multicenter study of hospitalized patients who triggered the BPA notification for ACH eligibility between March and December 2021 at Mayo Clinic in Jacksonville, FL and Mayo Clinic Health System in Eau Claire, WI. We extracted demographic and diagnosis data from the patients as well as characteristics of the providers who received the BPA notification., Intervention: The BPA was developed based on the ACH inclusion and exclusion criteria, which were derived from clinical guidelines, literature review, and expert consensus. The BPA was integrated into the EHR and displayed a pop-up message to the provider when a patient met the criteria for ACH eligibility. The provider could choose to refer the patient to ACH, dismiss the notification, or defer the decision., Main Outcomes and Measures: The main outcomes were the number and proportion of BPA notifications that resulted in a referral to ACH, and the number and proportion of referrals that were accepted by the ACH clinical team and transferred to ACH. We also analyzed the factors associated with the provider's decision to refer or not refer the patient to ACH, such as the provider's role, location, and specialty., Results: During the study period, 8962 notifications were triggered for 2847 patients. Providers opted to refer 711 (11.4%) of the total notifications linked to 324 unique patients. After review by the ACH clinical team, 31 of the 324 referrals (9.6%) met clinical and social criteria and were transferred to ACH. In multivariable analysis, Wisconsin nurses, physician assistants, and in-training personnel had lower odds of referring the patients to ACH when compared to attending physicians., (© 2024 Society of Hospital Medicine.)

Background: Remote patient monitoring (RPM), or telemonitoring, offers ways for health care practitioners to gather real-time information on the physiological conditions of patients. As telemedicine, and thus telemonitoring, is becoming increasingly relevant in today's society, understanding the practitioners' opinions is crucial. This systematic review evaluates the perspectives and experiences of health care practitioners with telemonitoring technologies., Methods: A database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the selection of articles measuring health care practitioners' perspectives and experiences with RPM technologies published between 2017 and 2021. Only articles written in English were included. No statistical analysis was performed and thus this is a qualitative review., Results: A total of 1605 studies were identified after the initial search. After applying the inclusion and exclusion criteria of this review's authors, 13 articles were included in this review. In all, 2351 practitioners' perspectives and experience utilizing RPM technology in a variety of medical specialties were evaluated through close- and open-ended surveys. Recurring themes emerged for both the benefits and challenges. Common benefits included continuous monitoring of patients to provide prompt care, improvement of patient self-care, efficient communication, increased patient confidence, visualization of health trends, and greater patient education. Challenges comprised increased workload, higher patient anxiety, data inaccuracy, disorienting technology, financial issues, and privacy concerns., Conclusion: Health care practitioners generally believe that RPM is feasible for application. Additionally, there is a consensus that telemonitoring strategies will become increasingly relevant. However, there are still drawbacks to the technology that need to be considered., Competing Interests: Conflicts of Interest None declared

Introduction: The Care Hotel is a virtual hybrid care model for postoperative patients after low-risk procedures which allow recovery in an outpatient environment. This study aimed to analyze if the American Society of Anesthesiologists Physical Status (ASA PS) Classification System can be used as a predictive factor for staying at Mayo Clinic's Care Hotel., Methods: This retrospective cohort study was conducted between July 23, 2020, and June 4, 2021, at Mayo Clinic in Florida, a 306-bed community academic hospital. ASA PS Class and post-procedure care setting (Care Hotel vs inpatient ward) were collected. Patients were classified into two ASA PS groups (ASA PS Classes 1-2 and 3-4). Pearson's Chi-square test was used to determine if the ASA PS Class and having stayed or not at the Care Hotel were independent and an Odds Ratio (OR) calculated., Results: Out of 392 surgical and procedural patients, 272 (69.39%) chose the Care Hotel and 120 (30.61%) chose the inpatient ward. There was a statistically significant association between ASA PS Class and staying at the Care Hotel, P < .01. The OR of preferring to stay at the Care Hotel in patients with ASA PS Class 1-2 vs ASA PC Class 3-4 was 1.91 ( P = .0041, 95% CI: 1.229-2.982)., Conclusion: Patients with ASA PS Classes 1-2 are almost twice as likely to elect to stay at the Care Hotel compared to those with ASA PS Classes 3-4. This finding may help care teams focus their Care hotel recruitment efforts., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objective: The Coronavirus Disease-19 (COVID-19) pandemic caused a decline in hospitalist wellness. The COVID-19 pandemic has evolved, and new outbreaks (i.e. Mpox) have challenged healthcare systems. The objective of the study was to assess changes in hospitalist wellness and guide interventions., Methods: We surveyed hospitalists (physicians and advanced practice providers [APPs]), in May 2021 and September 2022, at a healthcare system's 16 hospitals in four US states using PROMIS® measures for global well-being, anxiety, social isolation, and emotional support. We compared wellness score between survey periods; in the September 2022 survey, we compared wellness scores between APPs and physicians and evaluated the associations of demographic and hospital characteristics with wellness using logistic (global well-being) and linear (anxiety, social isolation, emotional support) regression models., Results: In May 2021 vs. September 2022, respondents showed no statistical difference in top global well-being for mental health (68.4% vs. 57.4%) and social activities and relationships (43.8% vs. 44.3%), anxiety (mean difference: +0.8), social isolation (mean difference: +0.5), and emotional support (mean difference: -1.0) (all, p  ≥ 0.05). In September 2022, in logistic regression models, APPs, compared with physicians, had lower odds for top (excellent or very good) global well-being mental health (odds ratio [95% CI], 0.31 [0.13-0.76]; p  < 0.05). In linear regression models, age <40 vs. ≥40 years was associated with higher anxiety (estimate ± standard error, 2.43 ± 1.05; p  < 0.05), and concern about contracting COVID-19 at work was associated with higher anxiety (3.74 ± 1.10; p  < 0.01) and social isolation (3.82 ± 1.21; p  < 0.01). None of the characteristics showed association with change in emotional support. In September 2022, there was low concern for contracting Mpox in the community (4.6%) or at work (10.0%)., Conclusion: In hospitalists, concern about contracting COVID-19 at work was associated with higher anxiety and social isolation. The unchanged wellness scores between survey periods identified opportunities for intervention. Mpox had apparently minor impact on wellness.

Electronic health record (EHR) systems collate patient data, and the integration and standardization of documents through Health Information Exchange (HIE) play a pivotal role in refining patient management. Although the clinical implications of AI in EHR systems have been extensively analyzed, its application in HIE as a crucial source of patient data is less explored. Addressing this gap, our systematic review delves into utilizing AI models in HIE, gauging their predictive prowess and potential limitations. Employing databases such as Scopus, CINAHL, Google Scholar, PubMed/Medline, and Web of Science and adhering to the PRISMA guidelines, we unearthed 1021 publications. Of these, 11 were shortlisted for the final analysis. A noticeable preference for machine learning models in prognosticating clinical results, notably in oncology and cardiac failures, was evident. The metrics displayed AUC values ranging between 61% and 99.91%. Sensitivity metrics spanned from 12% to 96.50%, specificity from 76.30% to 98.80%, positive predictive values varied from 83.70% to 94.10%, and negative predictive values between 94.10% and 99.10%. Despite variations in specific metrics, AI models drawing on HIE data unfailingly showcased commendable predictive proficiency in clinical verdicts, emphasizing the transformative potential of melding AI with HIE. However, variations in sensitivity highlight underlying challenges. As healthcare's path becomes more enmeshed with AI, a well-rounded, enlightened approach is pivotal to guarantee the delivery of trustworthy and effective AI-augmented healthcare solutions.

To understand why US patients refused participation in hospital-at-home (H@H) during the coronavirus disease 2019 Public Health Emergency, eligible adult patients seen at 2 Mayo Clinic sites, Mayo Clinic Health System-Northwest Wisconsin region (NWWI) and Mayo Clinic Florida (MCF), from August 2021 through March 2022, were invited to participate in a convergent-parallel study. Quantitative associations between H@H participation status and patient baseline data at hospital admission were investigated. H@H patients were more likely to have a Mayo Clinic patient portal at baseline ( P -value: .014), indicating a familiarity with telehealth. Patients who refused were more likely to be from NWWI ( P -value < .001) and have a higher Epic Deterioration Index score ( P -value: .004). The groups also had different quarters (in terms of fiscal calendar) of admission ( P -value: .040). Analyzing qualitative interviews (n = 13) about refusal reasons, 2 themes portraying the quantitative associations emerged: lack of clarity about H@H and perceived domestic challenges. To improve access to H@H and increase patient recruitment, improved education about the dynamics of H@H, for both hospital staff and patients, and inclusive strategies for navigating domestic barriers and diagnostic challenges are needed., (© The Author(s) 2023.)

Background: Remote patient monitoring (RPM) is an option for continuously managing the care of patients in the comfort of their homes or locations outside hospitals and clinics. Patient engagement with RPM programs is essential for achieving successful outcomes and high quality of care. When relying on technology to facilitate monitoring and shifting disease management to the home environment, it is important to understand the patients' experiences to enable quality improvement., Objective: This study aimed to describe patients' experiences and overall satisfaction with an RPM program for acute and chronic conditions in a multisite, multiregional health care system., Methods: Between January 1, 2021, and August 31, 2022, a patient experience survey was delivered via email to all patients enrolled in the RPM program. The survey encompassed 19 questions across 4 categories regarding comfort, equipment, communication, and overall experience, as well as 2 open-ended questions. Descriptive analysis of the survey response data was performed using frequency distribution and percentages., Results: Surveys were sent to 8535 patients. The survey response rate was 37.16% (3172/8535) and the completion rate was 95.23% (3172/3331). Survey results indicated that 88.97% (2783/3128) of participants agreed or strongly agreed that the program helped them feel comfortable managing their health from home. Furthermore, 93.58% (2873/3070) were satisfied with the RPM program and ready to graduate when meeting the program goals. In addition, patient confidence in this model of care was confirmed by 92.76% (2846/3068) of the participants who would recommend RPM to people with similar conditions. There were no differences in ease of technology use according to age. Those with high school or less education were more likely to agree that the equipment and educational materials helped them feel more informed about their care plans than those with higher education levels., Conclusions: This multisite, multiregional RPM program has become a reliable health care delivery model for the management of acute and chronic conditions outside hospitals and clinics. Program participants reported an excellent overall experience and a high level of satisfaction in managing their health from the comfort of their home environment., (©Tufia C Haddad, Karla C Maita, Jonathan W Inselman, Francisco R Avila, Ricardo A Torres-Guzman, Jordan D Coffey, Laura A Christopherson, Angela M Leuenberger, Sarah J Bell, Dominick F Pahl, John P Garcia, Lukas Manka, Antonio J Forte, Michael J Maniaci. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.07.2023.)

Background: Patients with mild to severe chronic systemic disease undergoing low-risk procedures are often hospitalized for observation. The Care Hotel is a novel virtual medicine hybrid model of care that offers patients a comfortable, out of hospital environment where they can receive both in-person and virtual care after a surgery or procedure. This study aimed to analyze if virtual hybrid post-procedure care in a hotel could be both conducted on and accepted by patients, even those with moderate to severe chronic diseases., Methods: This retrospective cohort study was conducted between July 23, 2020 and June 4, 2021 at Mayo Clinic in Florida, a 306-bed community academic hospital. We collected the sex, age, race, ethnicity, acceptance rate, ASA score, and primary procedure of patients using the Care Hotel., Results: Out of 392 patients, 272 (69.4%) opted for care in the program. Median patient age was 61.5 years, 59.56% were males, and 86.40% were white. We found that 50.37% had an ASA score of 2 and 43.4% had an ASA score of 3. Ten different surgical specialties were able to utilize the Care Hotel for care in 47 different procedure types. Urology had the most patients (n=70, 25.7%). Post-electrophysiologic procedures were the most common procedures (n=39, 14.3%)., Conclusion: Our virtual hybrid Care Hotel program was widely accepted by patients and could care for a multitude of post-operative procedures. Additionally, this novel program can care for patients with both mild and severe systemic diseases.

Hospital at home is designed to offer patients hospital level care in the comfort of their own home. The process by which clinicians select eligible patients that are clinically and socially appropriate for this model of care requires labor-intensive manual chart reviews. We addressed this problem by providing a predictive model, web application, and data pipeline that produces an eligibility score based on a set of clinical and social factors that influence patients' success in the program. Providers used this predictive model to prioritize the order in which they perform chart reviews and patient screenings. Training performance area under the curve (AUC) was 0.77. Testing 'in production' had an AUC of 0.75. Admission criteria in training rapidly changed over the course of the study due to the novelty of the clinical model. The current algorithm successfully identified many inconsistencies in enrollment and has streamlined the process of patient identification., (©2022 AMIA - All rights reserved.)

Technology-enhanced hospital-at-home (H@H), commonly referred to as hybrid H@H, became more widely adopted during the COVID-19 pandemic. We conducted focus group interviews with Mayo Clinic staff members (n = 14) delivering hybrid H@H in three separate locations-a rural community health system (Northwest Wisconsin), the nation's largest city by area (Jacksonville, FL), and a desert metropolitan area (Scottsdale, AZ)-to understand staff experiences with implementing a new care delivery model and using new technology to monitor patients at home during the pandemic. Using a grounded theory lens, transcripts were analyzed to identify themes. Staff reported that hybrid H@H is a complex care coordination and communication initiative, that hybrid H@H faces site-specific challenges modulated by population density and state policies, and that many patients are receiving uniquely high-quality care through hybrid H@H, partly enabled by advances in technology. Participant responses amplify the need for additional qualitative research with hybrid H@H staff to identify areas for improvement in the deployment of new models of care enabled by modern technology.

Mayo Clinic's Care Hotel is a virtual hybrid care model which allows postoperative patients to recover in a comfortable environment after a low-risk procedure. Hospitals need to understand the key patient factors that promote acceptance of the Care Hotel if they are to benefit from this innovative care model. This study aims to identify factors that can predict whether a patient will stay at Care Hotel., Materials and Methods: This retrospective chart review of 1065 patients was conducted between 23 July 2020, and 31 December 2021. Variables examined included patient age, sex, race, ethnicity, Charlson comorbidity index, distance patient travelled to hospital, length of surgery, day of the week of surgery, and surgical service. Associations of patient and surgery characteristics with the primary outcome of staying at the Care Hotel were assessed using unadjusted and multivariable logistic regression models., Results: Of the 1065 patients who met criteria for admission to the Care Hotel during the study period, 717 (67.3%) chose to stay at the Care Hotel while 328 (32.7%) choose to be admitted to the hospital. In multivariable analysis, there was a significant association between surgical service and staying at the Care Hotel ( P <0.001). Specifically, there was a higher likelihood of staying at the Care Hotel for patients from Neurosurgery [odds rato (OR)=1.86, P =0.004], Otorhinolaryngology (OR=2.70, P <0.001), and General Surgery (OR=2.75, P =0.002). Additionally, there was a higher likelihood of staying at the Care Hotel with distance travelled over 110 miles [OR (per each doubling)=1.10, P =0.007]., Conclusion: When developing a post-surgical care model for patients following outpatient procedures, the referring surgical service is a primary factor to consider in order to ensure patient acceptance, along with patient distance. This study can assist other healthcare organizations considering this model, as it provides guidance on which factors are most indicative of acceptance., Competing Interests: None of the authors report any conflicts of interest., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Mayo Clinic's virtual hybrid hospital-at-home program, Advanced Care at Home (ACH) monitors acute and post-acute patients for signs of deterioration and institutes a rapid response (RR) system if detected., Objective: This study aimed to describe Mayo Clinic's ACH RR team and its effect on emergency department (ED) use and readmission rates., Methods: This was a retrospective review of all post-inpatient (restorative phase) ACH patients admitted from July 6, 2020 through June 30, 2021. If the restorative patient had a clinical decompensation, an RR was activated. All RR activations were analyzed for patient demographic characteristics, admitting and escalation diagnosis, time spent by virtual team on the RR, and whether the RR resulted in transport to the ED or hospital readmission., Results: Three hundred and twenty patients were admitted to ACH during the study interval; 230 received restorative care. Seventy-two patients (31.3%) had events that triggered an RR. Fifty (69.4%) of the RR events were related to the admission diagnosis (p < 0.001; 95% CI 0.59-0.80). Twelve patients (16.7%) required transport to an ED for further treatment and were readmitted and 60 patients (83.3%) were able to be treated successfully in the home by the RR team (p < 0.001; 95% CI 0.08-0.25)., Conclusions: The use of an ACH RR team was effective at limiting both escalations back to an ED and hospital readmissions, as 83% of deteriorating patients were successfully stabilized and managed in their homes. Implementing a hospital-at-home RR team can reduce the need for ED use by providing critical resources and carrying out required interventions to stabilize the patient's condition., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: In July 2020, Mayo Clinic launched Advanced Care at Home (ACH), a high-acuity virtual hybrid hospital-at-home model (HaH) of care at Mayo Clinic Florida and Northwest Wisconsin, an urban destination medical center and a rural community practice respectively. This study aims to describe demographic characteristics of ACH patients as well as their acuity of illness using severity of illness (SOI) and risk of mortality (ROM), to illustrate the complexity of patients in the program, taking into account the different diagnostic related groups., Methods: Mayo Clinic uses All Patient Refined-Diagnosis Related Groups (APR-DRG) to calculate SOI and ROM on hospitalized patients. APR-DRG data, including SOI and ROM, were gathered from individual chart reviews from July 6, 2020, to March 31, 2022., Results:  Out of 923 patients discharged from ACH, the average APR-DRG SOI was 2.89 (SD 0.81) and ROM was 2.73. (SD 0.92). Mean age was 70.88 (SD 14.46) years, 54.6% were male patients and the average length of stay was 4.10 days. The most frequent diagnosis was COVID-19 infection with 162 patients (17.6%), followed by heart failure exacerbation (12.7%) and septicemia (10.9%). The 30-day readmission rate after discharge from ACH was 11.2% (n = 103) and the 30-day mortality rate was 1.8% (n = 17). There were no in-program patient deaths., Conclusions: SOI and ROM from patients at the ACH program have been shown to be in the range of "moderate/major" according to the APR-DRG classification. The ACH program is capable of accepting and managing highly complex patients that require advanced therapeutic means. Furthermore, the ACH program has an in-program mortality rate of 0 to date. Therefore, ACH is rising as a capable alternative to the brick-and-mortar hospital., (© 2023. The Author(s).)

Background: As providers look to scale high-acuity care in the patient home setting, hospital-at-home is becoming more prevalent. The traditional model of hospital-at-home usually relies on care delivery by in-home providers, caring for patients in urban communities through academic medical centers. Our objective is to describe the process and outcomes of Mayo Clinic's Advanced Care at Home (ACH) program, a hybrid virtual and in-person hospital-at-home model combining a single, virtual provider-staffed command center with a vendor-mediated in-person medical supply chain to simultaneously deliver care to patients living near an urban hospital-at-home command center and patients living in a rural region in a different US state and time zone., Methods: A descriptive, retrospective medical records review of all patients admitted to ACH between July 6, 2020, and December 31, 2021. Patients were admitted to ACH from an urban academic medical center in Florida and a rural community hospital in Wisconsin. We collected patient volumes, age, sex, race, ethnicity, insurance type, primary hospital diagnosis, 30-day mortality rate, in-program mortality, 30-day readmission rate, rate of return to hospital during acute phase, All Patient Refined-Diagnosis Related Groups (APR-DRG) Severity of Illness (SOI), and length of stay (LOS) in both the inpatient-equivalent acute phase and post-acute equivalent restorative phase., Results: Six hundred and eighty-six patients were admitted to the ACH program, 408 in Florida and 278 in Wisconsin. The most common diagnosis seen were infectious pneumonia (27.0%), septicemia / bacteremia (11.5%), congestive heart failure exacerbation (11.5%), and skin and soft tissue infections (6.3%). Median LOS in the acute phase was 3 days (IQR 2-5) and median stay in the restorative phase was 22 days (IQR 11-26). In-program mortality rate was 0% and 30-day mortality was 0.6%. The mean APR-DRG SOI was 2.9 (SD 0.79) and the 30-day readmission rate was 9.7%., Conclusions: The ACH hospital-at-home model was able to provide both high-acuity inpatient-level care and post-acute care to patients in their homes through a single command center to patients in urban and rural settings in two different geographical locations with favorable outcomes of low mortality and hospital readmissions., (© 2023. The Author(s).)

In the US, at least one fall occurs in at least 28.7% of community-dwelling seniors 65 and older each year. Falls had medical costs of USD 51 billion in 2015 and are projected to reach USD 100 billion by 2030. This review aims to discuss the extent of smartphone (SP) usage in fall detection and prevention across a range of care settings. A computerized search was conducted on six electronic databases to investigate the use of remote sensing technology, wireless technology, and other related MeSH terms for detecting and preventing falls. After applying inclusion and exclusion criteria, 44 studies were included. Most of the studies targeted detecting falls, two focused on detecting and preventing falls, and one only looked at preventing falls. Accelerometers were employed in all the experiments for the detection and/or prevention of falls. The most frequent course of action following a fall event was an alarm to the guardian. Numerous studies investigated in this research used accelerometer data analysis, machine learning, and data from previous falls to devise a boundary and increase detection accuracy. SP was found to have potential as a fall detection system but is not widely implemented. Technology-based applications are being developed to protect at-risk individuals from falls, with the objective of providing more effective and efficient interventions than traditional means. Successful healthcare technology implementation requires cooperation between engineers, clinicians, and administrators.

In July 2020, Mayo Clinic introduced a hospital-at-home program, known as Advanced Care at Home (ACH) as an alternate option for clinically stable medical patients requiring hospital-level care. This retrospective cohort study evaluates the impact of the addition of a dedicated ACH patient acquisition Advanced Practice Provider (APP) on average length of stay (ALOS) and the number of patients admitted into the program between in Florida and Wisconsin between 6 July 2020 and 31 January 2022. Patient volumes and ALOS of 755 patients were analyzed between the two sites both before and after a dedicated acquisition APP was added to the Florida site on 1 June 2021. The addition of a dedicated acquisition APP did not affect the length of time a patient was in the emergency department or hospital ward prior to ACH transition (2.91 days [Florida] vs. 2.59 days [Wisconsin], p = 0.22), the transition time between initiation of the ACH consult to patient transfer home (0.85 days [Florida] vs. 1.16 days [Wisconsin], p = 0.28), or the total ALOS (6.63 days [Florida] vs. 6.34 days [Wisconsin], p = 0.47). The average number of patients acquired monthly was significantly increased in Florida (38.3 patients per month) compared with Wisconsin (21.6 patients per month) ( p < 0.01). The addition of a dedicated patient acquisition APP resulted in significantly higher patient volumes but did not affect transition time or ALOS. Other hospital-at-home programs may consider the addition of an acquisition APP to maximize patient volumes.

Introduction: Numerous factors are intersecting in healthcare resulting in an increased focus on new tools and methods for managing care in patients' homes. Remote patient monitoring (RPM) is an option to provide care at home and maintain a connection between patients and providers to address ongoing medical issues., Methods: Mayo Clinic developed a nurse-led RPM program for disease and post-procedural management to improve patient experience, clinical outcomes, and reduce health care utilization by more directly engaging patients in their health care. Enrolled patients are sent a technology package that includes a digital tablet and peripheral devices for the collection of symptoms and vital signs. The data are transmitted from to a hub integrated within the electronic health record. Care team members coordinate patient needs, respond to vital sign alerts, and utilize the data to inform and provide individualized patient assessment, patient education, medication management, goal setting, and clinical care planning., Results: Since its inception, the RPM program has supported nearly 22,000 patients across 17 programs. Patients who engaged in the COVID-19 RPM program experienced a significantly lower rate of 30-day, all-cause hospitalization (13.7% vs. 18.0%, P  = 0.01), prolonged hospitalization >7 days (3.5% vs. 6.7%, P  = 0.001), intensive care unit (ICU) admission (2.3% vs. 4.2%, P  = 0.01), and mortality (0.5% vs. 1.7%, P  = 0.01) when compared with those enrolled and unengaged with the technology. Patients with chronic conditions who were monitored with RPM upon hospital discharge were significantly less likely to experience 30-day readmissions (18.2% vs. 23.7%, P  = 0.03) compared with those unmonitored. Ninety-five percent of patients strongly agreed or agreed they were likely to recommend RPM to a friend or family member., Conclusions: The Mayo Clinic RPM program has generated positive clinical outcomes and is satisfying for patients. As technology advances, there are greater opportunities to enhance this clinical care model and it should be extended and expanded to support patients across a broader spectrum of needs. This report can serve as a framework for health care organizations to implement and enhance their RPM programs in addition to identifying areas for further evolution and exploration in developing RPM programs of the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Coffey, Christopherson, Williams, Gathje, Bell, Pahl, Manka, Blegen, Maniaci, Ommen and Haddad.)

Objective: To evaluate care utilization, cost, and mortality among high-risk patients enrolled in a coronavirus disease 2019 (COVID-19) remote patient monitoring (RPM) program., Methods: This retrospective analysis included patients diagnosed with COVID-19 at risk for severe disease who enrolled in the RPM program between March 2020 and October 2021. The program included in-home technology for symptom and physiologic data monitoring with centralized care management. Propensity score matching established matched cohorts of RPM-engaged (defined as ≥1 RPM technology interactions) and non-engaged patients using a logistic regression model of 59 baseline characteristics. Billing codes and the electronic death certificate system were used for data abstraction from the electronic health record and reporting of care utilization and mortality endpoints., Results: Among 5796 RPM-enrolled patients, 80.0% engaged with the technology. Following matching, 1128 pairs of RPM-engaged and non-engaged patients comprised the analysis cohorts. Mean patient age was 63.3 years, 50.9% of patients were female, and 81.9% were non-Hispanic White. Patients who were RPM-engaged experienced significantly lower rates of 30-day, all-cause hospitalization (13.7% vs 18.0%, P=.01), prolonged hospitalization (3.5% vs 6.7%, P=.001), intensive care unit admission (2.3% vs 4.2%, P=.01), and mortality (0.5% vs 1.7%; odds ratio, 0.31; 95% CI, 0.12 to 0.78; P=.01), as well as cost of care ($2306.33 USD vs $3565.97 USD, P=0.04), than those enrolled in RPM but non-engaged., Conclusion: High-risk COVID-19 patients enrolled and engaged in an RPM program experienced lower rates of hospitalization, intensive care unit admission, mortality, and cost than those enrolled and non-engaged. These findings translate to improved hospital bed access and patient outcomes., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Telemedicine has revolutionized health-care services with its unprecedented abilities to connect patients with health-care professional across the distances. Patient satisfaction is an important measure of the quality and effectiveness of health-care services., Aim: The goal of this systematic review is to investigate patient satisfaction with telemedicine in acute care setting., Methods and Results: Four sources of data were searched PubMed, Cumulative Index of Nursing and Allied Health Literature, Scopus, and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. Our analysis has showed that acute telemedicine was effective in managing a broad spectrum of acute medical conditions while achieving high levels of patient satisfaction., Conclusion: Patient satisfaction is a complex product of expectations and experiences. Furthermore, it is an important indicator of the quality of the service. Despite the challenging nature of acute medicine, telemedicine services were successful in improving the quality of the service and achieving high levels of patient satisfaction., Relevance for Patients: Telemedicine is rapidly evolving as an essential component of our healthcare system. Implementing telemedicine in acute care is a relatively new concept and patient satisfaction in these settings needs to be evaluated., Competing Interests: The authors declare no conflicts of interest., (Copyright: © 2022 Author(s).)

Background: Delivering acute hospital care to patients at home might reduce costs and improve patient experience. Mayo Clinic's Advanced Care at Home (ACH) program is a novel virtual hybrid model of "Hospital at Home." This pragmatic randomized controlled non-inferiority trial aims to compare two acute care delivery models: ACH vs. traditional brick-and-mortar hospital care in acutely ill patients., Methods: We aim to enroll 360 acutely ill adult patients (≥18 years) who are admitted to three hospitals in Arizona, Florida, and Wisconsin, two of which are academic medical centers and one is a community-based practice. The eligibility criteria will follow what is used in routine practice determined by local clinical teams, including clinical stability, social stability, health insurance plans, and zip codes. Patients will be randomized 1:1 to ACH or traditional inpatient care, stratified by site. The primary outcome is a composite outcome of all-cause mortality and 30-day readmission. Secondary outcomes include individual outcomes in the composite endpoint, fall with injury, medication errors, emergency room visit, transfer to intensive care unit (ICU), cost, the number of days alive out of hospital, and patient-reported quality of life. A mixed-methods study will be conducted with patients, clinicians, and other staff to investigate their experience., Discussion: The pragmatic trial will examine a novel virtual hybrid model for delivering high-acuity medical care at home. The findings will inform patient selection and future large-scale implementation., Trial Registration: ClinicalTrials.gov NCT05212077. Registered on 27 January 2022., (© 2022. The Author(s).)

Objectives: Hospitalists, comprising PAs, NPs, and physicians, manage patients hospitalized with COVID-19. To guide the development of support programs, this study compared the psychologic wellness of hospitalist PAs, NPs, and physicians during the COVID-19 pandemic., Methods: We surveyed hospitalists in 16 hospitals at Mayo Clinic, from May 4 to 25, 2020. We used PROMIS surveys for self-reported global well-being (two single-item measures), anxiety, social isolation, and emotional support, before and during the pandemic. Linear and logistic regression models were adjusted for personal and professional factors., Results: The response rate was 52.2% (N = 154/295). In adjusted linear regression models, the change in scores (before minus during pandemic) for anxiety, social isolation, and emotional support was similar for PAs and NPs compared with physicians. In adjusted logistic regression models, physicians, compared with PAs and NPs, had a higher odds of top global well-being for mental health (adjusted odds ratio [95% confidence interval]: 2.82 [1.12, 7.13]; P = .03) and top global well-being for social activities and relationships (adjusted odds ratio 4.08 [1.38, 12.08]; P = .01)., Conclusions: During the COVID-19 pandemic, global well-being was lower for PAs and NPs compared with physician hospitalists. These results can guide support programs for hospitalists., (Copyright © 2022 American Academy of Physician Associates.)

Objectives: Traditional hospital at home models often have high patient experience scores. The purpose of this study is to look at the patient experience of a new virtual hybrid model of hospital at home called Advanced Care at Home., Methods: Patients in Mayo Clinic's Advanced Care at Home program received a survey via email from 1 January-31 May 2021. Each survey consisted of 20 questions divided into 18 multiple-choice and two open-ended questions., Results: Ninety-nine surveys were sent and 41 partially or completely finished surveys were returned for a response rate of 41.4%. Patients responded positively, denoted by answering "strongly agree or somewhat agree," with regard to the ability to reach the team right away 100% of the time, being kept informed 92% of the time, the command center responding promptly to their needs 95% of the time, the team providing comfort and support 98% of the time, feeling comfortable with interacting with their provider by phone or tablet 95% of the time, the ease of use from the equipment 97% of the time, the virtual and in-person staff working well together 98% of the time, the staff treating patients with courtesy and respect 100% of the time, and the ease of understanding the discharge process and feeling ready to leave the program 100% of the time. All providers received positive responses on listening ⩾88% of the time. Patients gave a top rating in likelihood to recommend the program 100% of the time., Conclusion: Overall, the Advanced Care at Home model of hospital at home was highly recommended by patients. Patients scored the program high on responsiveness, staff engagement and communication, ease of equipment use, and readiness for discharge, strengthening the overall confidence in this novel program., 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) 2022.)

Background: The early phase of the coronavirus disease 2019 (COVID-19) pandemic had a negative impact on the wellness of hospitalists and hospital medicine advanced practice providers (APPs). However, the burden of the pandemic has evolved and the change in hospitalist and hospital medicine APP wellness is unknown., Objective: To evaluate the longitudinal trend in wellness of hospitalists and hospital medicine APPs during the COVID-19 pandemic and guide wellness interventions., Design, Setting and Participants: Between May 4, 2020, and June 6, 2021, we administered three surveys to Internal Medicine hospitalists (physicians) and hospital medicine APPs (nurse practitioners and physician assistants) at 16 Mayo Clinic hospitals in four U.S. states., Measurements: We evaluated the association of hospitalist and hospital medicine APP characteristics with PROMIS® measures of global wellbeing-mental health, global wellbeing-social activities and relationships, anxiety, social isolation, and emotional support, using logistic and linear regression models., Results: The response rates were 52.2% (n=154/295; May 2020), 37.1% (n=111/299; October 2020) and 35.5% (n=114/321; May 2021). In mixed models that included hospitalist and hospital medicine APP characteristics and survey period, APPs, compared with physicians, had lower odds of top global wellbeing-social activities and relationships (adjusted odds ratio 0.42 [0.22-0.82]; p = .01), whereas survey period showed no association. The survey period showed an independent association with higher anxiety (May 2020 vs. others) and higher social isolation (October 2020 vs. others), whereas profession showed no association. Concern about contracting COVID-19 at work was significantly associated with lower odds of top global wellbeing-mental health and global wellbeing-social activities and relationships, and with higher anxiety and social isolation. Hospitalist and hospital medicine APP characteristics showed no association with levels of emotional support., Conclusions: In this longitudinal assessment of hospitalists and hospital medicine APPs, concern about contracting COVID-19 at work remained a determinant of wellness. The trend for global wellbeing, anxiety, and social isolation may guide wellness interventions., (© 2022 Society of Hospital Medicine.)

Introduction: The Care Hotel is a virtual medicine hybrid model of care that was implemented at Mayo Clinic in Florida in July of 2020. This temporal accommodation offers patients a comfortable out of hospital environment where they can receive both in-person and virtual care after a surgery or procedure. This study aims to report patient feedback regarding their Care Hotel experience., Materials and Methods: Between July 23, 2020 and June 4, 2021, a satisfaction survey was sent to patients via email after their discharge from the Care Hotel. The survey consisted of 8 Likert questions rating their experience in the model as well as 2 questions where patients describe the positive and negative aspects of their stay. Patient demographics including age, sex, procedure performed, and the surgical/procedural service under which they were admitted to the hotel were also collected., Results: Out of 182 patients admitted to Care Hotel, 102 answered the survey. Nine surveys were excluded due to missing patient information, and 93 surveys were analyzed. Eighty-seven percent of patients had a positive experience in the Care Hotel model and 94% of patients were likely to recommend the program to others. Positive comments highlighted the ease of use of the technology setups, the low cost of the hotel, the seamless transition of care, and the relief of the burden of care for family members., Conclusion: The Mayo Clinic hybrid Care Hotel, combining both in-person and virtual modes of medical care, provides a good overall experience for patients following low-risk surgeries and procedures., Competing Interests: None of the authors have any conflicts of interest to declare., (© 2022 The Authors.)

Background: Home telemonitoring has been used with discharged patients in an attempt to reduce 30-day readmissions with mixed results., Objective: To assess whether home 30-day telemonitoring after discharge for patients at high risk of readmission would reduce readmissions or mortality., Design: Prospective, randomized controlled trial., Patients: We compared 30-day readmission rates and mortality for patients at high risk for readmission who received home telemonitoring versus standard care between November 1, 2014, and November 30, 2018, in 2 tertiary care hospitals., Interventions: The intervention group received home-installed equipment to measure blood pressure, heart rate, pulse oximetry, weight if heart failure was present, and glucose if diabetes was present. Results were transmitted daily and reviewed by a nurse. Both groups received standard care., Main Measures: The primary outcome was a composite end point of hospital readmission or death within 30 days after discharge. The secondary outcome was an emergency department visit within 30 days after discharge., Key Results: A total of 1380 participants (mean [SD] age, 66 [14] years; 722 [52.3%] men and 658 [47.7%] women) participated in this study. Using a modified intention-to-treat analysis, the risk of readmission or death within 30 days among patients at high readmission risk was 23.7% (137/578) in the control group and 18.2% (87/477) in the telemonitoring group (absolute risk difference, - 5.5% [95% CI, - 10.4 to - 0.6%]; relative risk, 0.77 [95% CI, 0.61 to 0.98]; P = .03). Emergency department visits occurred within 30 days after discharge in 14.2% (81/570) of patients in the control group and 8.6% (40/464) of patients in the telemonitoring group (absolute risk difference, - 5.6% [95% CI, - 9.4 to - 1.8%]; relative risk, 0.61 [95% CI, 0.42 to 0.87]; P = .005)., Conclusions: Thirty days of postdischarge telemonitoring may reduce readmissions of high-risk patients., Trial Registration: ClinicalTrials.gov identifier: NCT02136186., (© 2021. Society of General Internal Medicine.)

Background : Hospitalists, comprised of nurse practitioners and physician assistants (collectively, advanced practice providers [APPs]) and physicians, have opportunities to counsel patients and reduce SARS-CoV-2 related coronavirus disease 2019 (COVID-19) vaccine hesitancy. However, hospitalist perspectives on the COVID-19 vaccine and potential differences between APPs and physicians are unknown. Understanding hospitalist perspectives could help to address vaccine hesitancy among patients. Methods : We conducted an online survey of hospitalists at Mayo Clinic sites in Arizona, Florida, Minnesota, and Wisconsin from 14 December 2020 through 4 January 2021. We collected demographic information and assessed perspectives on the COVID-19 vaccine and, for comparison, on the influenza vaccine. Descriptive statistics were used to compare responses between APPs and physicians. Results : The overall response rate was 42.7% (n = 128/300) and comprised of 53.9% women (n = 69/128) and 41.4% APPs (n = 53/128). Most hospitalists reported receiving or planning to receive vaccination against COVID-19 (93.7%; n = 119/128) and influenza (97.7%; n = 125/128). Most hospitalists reported they would advise 100% of patients to receive the COVID-19 vaccine (66% for APPs; 74.7% for physicians) and influenza vaccine (83% for APPs; 80% for physicians). Barriers to recommending the COVID-19 vaccine included patient health status and vaccine safety profile. Hospitalists reported that patients and coworkers receiving the COVID-19 vaccine would reduce their anxiety (~80% of hospitalists), social isolation (~64% of hospitalists), and improve their emotional support (~40% of hospitalists). APP and physician responses were similar. The possible reduction in social isolation was associated with higher odds of hospitalists advising all patients to receive the COVID-19 vaccine (adjusted odds ratio 2.95 [95% confidence interval, 1.32-6.59]; P < .008), whereas hospitalist age, gender, and profession showed no association. Conclusion : Most hospitalists would reportedly advise patients to receive the COVID-19 vaccine. Barriers to this recommendation included patient health status and vaccine safety. Hospitalists are an important resource to provide patient education and reduce COVID-19 vaccine hesitancy.

Background: As the United States' population ages, the health care system will experience overall change. This study aims to identify factors in the older adult that may contribute to involuntary hold status in the ED., Methods: This study is a retrospective review conducted at a suburban acute-care hospital ED of adult patients evaluated while on involuntary hold from January 1, 2014, through November 30, 2015. Older adults (patients born on or before 06/31/1964) were compared to younger adults (born on or after 07/01/1964) according to demographic and clinical variables including medical comorbidity, ED length of stay, reason for involuntary hold, psychiatric disorder, suicide attempt, substance use disorder, serum alcohol level, urine drug testing, medical comorbidity, violence in the ED, 30-day ED readmission, and 30-day mortality., Results: Of 251 patients, 90 (35.9%) were older adults. The most common reason for involuntary hold in both cohorts was suicidal ideation. Medical comorbidities were more prevalent in older adults [60 (66.7%) vs. 64 (39.8%), P ≤.0001]. Older adults were less likely to report current drug abuse [31 (34.4%) vs. 77 (47.8%), P = .04]. The most commonly misused substance in both groups was alcohol; however, despite similar rates, blood alcohol levels (BAC) and urine drug screen (UDS) were performed less often in older adults. Cohorts were not significantly different with respect to sex, race, violence in the ED, psychiatric diagnosis, and ED LOS., Conclusions: Involuntary older adult patients present with medical comorbidities that impact mental health. In the ED, they are less likely report substance use, and drug screening may be underutilized. Medical needs make their care unique and may present challenges in transfer of care to inpatient psychiatric facilities., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Patients with COVID-19 infection requiring in-hospital care are frequently managed by Internal Medicine hospitalists, comprised of physicians, nurse practitioners and physician assistants. There is sparse information on the psychological impact of the COVID-19 pandemic on Internal Medicine hospitalists., Methods: We surveyed Internal Medicine hospitalists at Mayo Clinic sites in four states (Arizona, Florida, Minnesota, and Wisconsin). We collected demographic information, and used Patient-Reported Outcomes Measurement Information System (PROMIS®) measures to assess global well-being, anxiety, social isolation, and emotional support. Descriptive statistics were used to compare responses between two periods: prior to the pandemic (before March 15 th , 2020), and during the pandemic (March 15 through 30 April 2020). The survey was conducted from May 4-25, 2020., Results: Of 295 Internal Medicine hospitalists, 154 (52%) responded. Fifty-six percent were women (n = 85/154) and 54% were physicians (n = 84/154). Most hospitalists (75%; n = 115/154) reported concerns about contracting COVID-19 infection at work, and 5% (n = 8/154) reported changing where they lived during the pandemic. Most hospitalists (73%; n = 112/154) reported relying primarily on institutional resources for COVID-19 information. During the pandemic, the percentage of participants with excellent or very good global well-being decreased (90% prior to pandemic vs. 53% during pandemic), with increases in mean anxiety (-4.88 [95% confidence interval, - 5.61 to - 4.16]; P <.001) and social isolation (-3.91[95% confidence interval, - 4.68 to - 3.13]; P <.001). During the same period, there was a small decrease in mean emotional support (1.46 [95% confidence interval, 0.83 to 2.09]; P <.001)., Conclusion: During the COVID-19 pandemic, Internal Medicine hospitalists reported lower global well-being, higher anxiety and social isolation, and a small decrease in emotional support. These results provide a framework to develop programs to support hospitalists and potentially mitigate long-term psychological sequelae including burnout.

Background: Physician hospitalists may participate in research and generate knowledge for evidence-based hospital practice. Despite this, physician hospitalists are primarily involved in patient care, and there is sparse information on barriers for their participation in research and if these barriers differ by career stage., Methods: We conducted a survey of physician hospitalists at Mayo Clinic sites based in four states (Arizona, Florida, Minnesota, and Wisconsin). We surveyed physician hospitalists on demographics, academic rank, current research skills, barriers for participation in research, and research skills they aspire to acquire. Responses were summarized using descriptive statistics and categorized by early-career (<10 years), mid-career (10-20 years), and later-career (≥20 years) stages at Mayo Clinic. The survey was conducted from March to April 2019., Results: Of 188 physician hospitalists, there was a 52% response rate with 71% in early career, 21% mid-career, and 7% late career, with 39% female. Physician hospitalists at early-career (90%), mid-career (76%), and later-career (71%) stages were interested in participating in research. Among physician hospitalists with ≤3 peer-reviewed publications, barriers for participation in research included lack of mentorship, time, research skills, and funding. Among physician hospitalists with ≥4 peer-reviewed publications, factors for research success included mentorship (89% early-career, 38% mid-career, 75% later-career; p = 0.002) and membership in a research team. Compared to mid- and later-career physician hospitalists, a higher proportion of early-career hospitalists was interested in acquiring skills to both critically review the literature (70% early-career, 43% mid-career, 0% later-career; p = 0.006) and write manuscripts (86% early-career, 57% mid-career, 50% later-career; p = 0.02); there was generally similar interest across career stages to acquire skills to conduct literature searches and write grants., Conclusion: The generally similar responses from physician hospitalists across career stages highlight system-level opportunities to increase research mentorship, promote the acquisition of research skills, and reduce barriers for participation in research.

Advanced practice providers and physicians at an academic healthcare system comprising more than 15 hospitals across four US states were surveyed to identify barriers to participation in research. Overall, barriers reported by advanced practice providers and physicians were more similar than different, highlighting system-level opportunities to build research skills and accelerate academic productivity.