Implementation of a virtual and in-person hybrid hospital-at-home model in two geographically separate regions utilizing a single command center: a descriptive cohort study.

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.

Advanced care at home at scale in an integrated health care system.

OBJECTIVES: To assess the feasibility of scaling advanced care at home (ACAH) (otherwise known as hospital at home) within an integrated health care delivery system. STUDY DESIGN: Retrospective cohort study of patients qualified for hospital-level care who were admitted to either ACAH or a traditional hospital. METHODS: From April 29, 2020, to November 14, 2021, patients requiring hospital-level care received Kaiser Permanente at Home or traditional hospital care. In a subgroup of patients, we compared outcomes for Kaiser Permanente at Home vs traditional hospital care using regression models. RESULTS: A total of 1005 patients were admitted to Kaiser Permanente at Home. Average daily census (ADC) was intentionally increased over time in stages, from 7.2 to 8.8, then to 12.7. The maximum daily census was 22, with a peak ADC of 16, representing 9% of the total hospital inpatient medicine service census. During this time, there were numeric decreases in Kaiser Permanente at Home escalation rates (17.5% to 10.8%), median length of stay (7.43 days to 5.46 days), and readmission rates (9.79% to 9.24%). A subgroup of Kaiser Permanente at Home patients contributed to the comparative analyses, which showed that patients admitted to Kaiser Permanente at Home were 64% less likely to experience delirium than patients admitted for traditional hospital care (OR, 0.36; 95% CI, 0.15-0.88; P = .026). Comparisons of quality metrics across stages of implementation (readmissions, escalations, length of stay) were inconclusive. CONCLUSION: In an integrated delivery system, ACAH care can be scaled and can create hospital capacity. However, our data were inconclusive regarding quality throughout scaling due to the small effective sample size, necessitating replication in a larger prospective study with adequate power/precision.

Supportive Oncology Care at Home Intervention for Patients With Pancreatic Cancer.

PURPOSE: We sought to determine the feasibility of delivering a Supportive Oncology Care at Home intervention among patients with pancreatic cancer. METHODS: We prospectively enrolled patients with pancreatic cancer from a parent trial of neoadjuvant fluorouracil, leucovorin, oxaliplatin, and irinotecan (FOLFIRINOX). The intervention entailed (1) remote monitoring of patient-reported symptoms, vital signs, and body weight; (2) a hospital-at-home care model; and (3) structured communication with the oncology team. We defined the intervention as feasible if ≥ 60% of patients enrolled in the study and ≥ 60% completed the daily assessments within the first 2-weeks of enrollment. We determined rates of treatment delays, urgent clinic visits, emergency department visits, and hospitalizations among those who did (n = 20) and did not (n = 24) receive Supportive Oncology Care at Home from the parent trial. RESULTS: From January 2019 to September 2020, we enrolled 80.8% (21/26) of potentially eligible patients. One patient became ineligible following consent because of moving out of state, resulting in 20 participants (median age = 67 years). In the first 2 weeks of enrollment, 65.0% of participants completed all daily assessments. Overall, patients reported 96.1% of daily symptoms, 96.1% of daily vital signs, and 92.5% of weekly body weights. Patients receiving the intervention had lower rates of treatment delays (55.0% v 75.0%), urgent clinic visits (10.0% v 25.0%), and emergency department visits/hospitalizations (45.0% v 62.5%) compared with those not receiving the intervention from the same parent trial. CONCLUSION: Findings demonstrate the feasibility and acceptability of a Supportive Oncology Care at Home intervention. Future work will investigate the efficacy of this intervention for decreasing health care use and improving patient outcomes.

Supportive oncology care at home interventions: protocols for clinical trials to shift the paradigm of care for patients with cancer.

BACKGROUND: Patients with cancer often endure substantial symptoms and treatment toxicities leading to high healthcare utilization, including hospitalizations and emergency department visits, throughout the continuum of their illness. Innovative oncology care models are needed to improve patient outcomes and reduce their healthcare utilization. Using a novel hospital at home care platform, we developed a Supportive Oncology Care at Home intervention to address the needs of patients with cancer. METHODS: We are conducting three trials to delineate the role of Supportive Oncology Care at Home for patients with cancer. The Supportive Oncology Care at Home intervention includes: (1) a hospital at home care model for symptom assessment and management; (2) remote monitoring of daily patient-reported symptoms, vital signs, and body weight; and (3) structured communication with the oncology team. Our first study is a randomized controlled trial to test the efficacy of Supportive Oncology Care at Home versus standard oncology care for improving healthcare utilization, cancer treatment interruptions, and patient-reported outcomes in patients with cancer receiving definitive treatment of their cancer. Participants include adult patients with gastrointestinal and head and neck cancer, as well as lymphoma, receiving definitive treatment (e.g., treatment with curative intent). The second study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention for hospitalized patients with advanced cancer. Eligible participants include adult patients with incurable cancer who are admitted with an unplanned hospitalization. The third study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention to enhance the end-of-life care for patients with advanced hematologic malignancies. Eligible participants include adult patients with relapsed or refractory hematologic malignancy receiving palliative therapy or supportive care alone. DISCUSSION: These studies are approved by the Dana-Farber/Harvard Cancer Center Institutional Review Board and are being conducted in accordance with the Consolidated Standards of Reporting Trials statement for non-pharmacological trials. This work has the potential to transform the paradigm of care for patients with cancer by providing them with the necessary support at home to improve their health outcomes and care delivery. TRIAL REGISTRATIONS: NCT04544046, NCT04637035, NCT04690205.

Preventing ethics conflicts and improving healthcare quality through system redesign.

BACKGROUND: Ethics and quality care are common drivers for healthcare organisations. Both are based on ethics principles that are the foundation for quality, and are synergistic with the Institute of Medicine's six quality aims. This paper describes the relationship between ethics principles and the goals of improving quality, safety and value. It demonstrates how healthcare staff, quality improvement professionals and ethics committee members could apply a quality improvement framework to address and prevent ethics issues. DISCUSSION: Recurring ethics issues can have a detrimental impact on both the quality of patient care and the culture of a healthcare organisation. Clinical staff and ethics committee members traditionally respond to ethics issues using a reactive approach. Despite nascent interest in a system-oriented preventive approach to ethics issues, there is limited practical advice for ethics committee members regarding how to specifically implement a system redesign strategy. Using an illustrative case study, the authors demonstrate how to apply a recognised quality improvement framework, which focuses on clinical microsystems, to manage and decrease ethics issues--therefore enhancing the organisation's quality of care. CONCLUSION: An important step in enhancing quality and ethics aims would be for the organisation's staff, including quality improvement professionals and ethics committee members, to collaborate in fostering system redesign. The authors' aim is not to examine in detail a specific quality improvement approach or method; rather, they wish to highlight the synergy they believe exists between quality improvement efforts and organisational ethics issues.