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Individual- and Community-Level Predictors of Hospital-at-Home Outcomes.
- Source :
- Population Health Management; Jun2024, Vol. 27 Issue 3, p168-173, 6p
- Publication Year :
- 2024
-
Abstract
- 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. The study includes 3 Mayo Clinic centers and community-level data from the Agency for Healthcare Research and Quality. The authors conducted binary logistic regression analyses to examine the relationship among the independent variables (patient- and community-level characteristics) and dependent variables (30-day readmission, mortality, and escalation of care back to the brick-and-mortar hospital). The study examined 1433 patients; 53% were men, 90.58% were White, and 68.2% were married. The mortality rate was 2.8%, 30-day readmission was 11.4%, and escalation back to brick-and-mortar hospitals was 8.7%. At the patient level, older age and male gender were significant predictors of 30-day mortality (P-value <0.05), older age was a significant predictor of 30-day readmission (P-value <0.05), and severity of illness was a significant predictor for readmission, mortality, and escalation back to the brick-and-mortar hospital (P-value <0.01). Patients with COVID-19 were less likely to experience readmission, mortality, or escalations (P-value <0.05). At the community level, the Gini Index and internet access were significant predictors of mortality (P-value <0.05). Race and ethnicity did not significantly predict adverse outcomes (P-value >0.05). This study showed promise in equitable treatment of diverse patient populations. The authors discuss and address health equity issues to approximate the vision of inclusive HaH delivery. [ABSTRACT FROM AUTHOR]
- Subjects :
- MORTALITY risk factors
HOME care services
RISK assessment
INTERNET access
HEALTH services accessibility
SOCIAL determinants of health
LOGISTIC regression analysis
PATIENT readmissions
SEX distribution
TREATMENT effectiveness
RETROSPECTIVE studies
DESCRIPTIVE statistics
AGE distribution
SEVERITY of illness index
TRANSITIONAL care
TELEMEDICINE
DATA analysis software
COVID-19
POVERTY
Subjects
Details
- Language :
- English
- ISSN :
- 19427891
- Volume :
- 27
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Population Health Management
- Publication Type :
- Academic Journal
- Accession number :
- 177992445
- Full Text :
- https://doi.org/10.1089/pop.2023.0297