Clinical Characteristics and Outcomes of Patients With COVID-19 Treated in Mayo Clinic's Advanced Care at Home Program.

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.

Initial Experience With Inpatient Hospital Care at Home for Urologic Disease.

Introduction: In 2020, Mayo Clinic launched Advanced Care at Home (ACH), a hospital-at-home program that cares for high-acuity inpatients via remote monitoring and in-person care. Herein, we describe our initial experience utilizing ACH for patients with urologic problems.

Methods: We identified ACH patients treated at Mayo Clinic Florida from July 2020 to August 2022.

The Impact of Digital Health Solutions on Bridging the Health Care Gap in Rural Areas: A Scoping Review.

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.

Machine Learning-Based Prediction of Readmission Risk in Cardiovascular and Cerebrovascular Conditions Using Patient EMR Data.

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.

Rurality and patients' hospital experience: A multisite analysis from a US healthcare system.

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.

Risk factors associated with escalation of care in a quaternary academic hospital at home program.

Background: Hospital-at-home has become a more recognized way to care for patients requiring inpatient hospitalization. At times, these patients may require escalation of care (transfer from home back to the brick-and-mortar (BAM) hospital for ongoing hospitalization care needs), a process that has not been extensively studied.

Objective: To evaluate what patient factors contribute to escalations of care in the hospital-at-home delivery model.

Artificial Intelligence Support for Informal Patient Caregivers: A Systematic Review.

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.

Bypassing the Brick-and-Mortar Hospital: Increasing Direct Admissions from the Emergency Department to Inpatient Hospital-at-Home.

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.

Individual- and Community-Level Predictors of Hospital-at-Home Outcomes.

Advanced Care at Home is a Mayo Clinic hospital-at-home (HaH) program that provides hospital-level care for patients. The study examines patient- and community-level factors that influence health outcomes. The authors performed a retrospective study using patient data from July 2020 to December 2022.

Development and evaluation of best practice advisory alert for patient eligibility in a hospital-at-home program: A multicenter retrospective study.

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.

Acute postoperative and rehabilitation care managed in a virtual hybrid hospital-at-home after a total knee arthroplasty: A case report.

Key Clinical Messages: This case report demonstrates a virtual hybrid hospital-at-home program can provide inpatient-level postoperative and rehabilitative care after total knee arthroplasty to a medically complex patient in the comfort of their own home.

Abstract: Advanced Care at Home combines virtual providers with in-home care delivery. We report a case of virtual postoperative and rehabilitative care in a medically complex patient who underwent a total knee arthroplasty.

Benefits and Challenges of Remote Patient Monitoring as Perceived by Health Care Practitioners: A Systematic Review.

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.

Why U.S. Patients Declined Hospital-at-Home during the COVID-19 Public Health Emergency: An Exploratory Mixed Methods Study.

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 (-value: .

Global well-being, anxiety, social isolation, and emotional support among hospitalists during COVID-19 and Mpox outbreaks.

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.

Post-Autologous Hematopoietic Cell Transplant Care in the "Home Sweet Home" Setting: A Treatment Paradigm Shift.

Background: Multiple myeloma (MM) is the second most common hematologic malignancy, with 34,470 estimated new cases in 2022. High-dose therapy followed by autologous hematopoietic cell transplantation (auto-HCT) remains a standard treatment for MM even in the era of novel therapies. This is usually performed in hospital-based settings, either in the inpatient or outpatient units.

Patient Satisfaction With a Multisite, Multiregional Remote Patient Monitoring Program for Acute and Chronic Condition Management: Survey-Based Analysis.

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.

Half Empty Half Full? Biased Perceptions of Compassionate Love and Effects of Dyadic Complementarity.

The prevailing theory on relationship judgments for interaction attributes suggests individuals tend to underestimate a romantic partner's expressions of compassionate love and that such underestimation is beneficial for the relationship. Yet, limited research has incorporated dyadic perspectives to assess how biased perceptions are associated with both partners' outcomes. In two daily studies of couples, we used distinct analytical approaches (Truth and Bias Model; Dyadic Response Surface Analysis) to inform perspectives on how biased perceptions are interrelated and predict relationship satisfaction.

Surgical service and distance traveled drive patient preference for Care Hotel: a retrospective cohort study.

Unlabelled: 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.

Staff Successes and Challenges with Telecommunications-Facilitated Patient Care in Hybrid Hospital-at-Home during the COVID-19 Pandemic.

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.