Key result
A novel 12-dimension taxonomy classified 34 Hospital at Home care models into three distinct archetypes: models for clinically complex patients, technology-enabled generalizable care, and complex interventions involving informal caregivers.
Why the study?
The lack of a standardized classification system for Hospital at home care models has hindered their systematic evaluation and comparison.
This study provides a validated 12-dimension taxonomy and identifies three main clusters of Hospital at Home care models, offering a framework to standardize reporting and tailor care delivery.
Answers are grounded in this paper and cite their sources.
May guide HaH model selection for complex patients; leaves open prospective validation to standardize reporting.
BACKGROUND: Hospital at home (HaH) care models have gained significant attention due to their potential to reduce healthcare costs, improve patient satisfaction, and lower readmission rates. However, the lack of a standardized classification system has hindered systematic evaluation and comparison of these models. Taxonomies serve as classification systems that simplify complexity and enhance understanding within a specific domain. OBJECTIVE: This paper introduces a comprehensive taxonomy of HaH care models, aiming to categorize and compare the various ways HaH services are delivered as an alternative to traditional hospital care. METHODS: We developed a taxonomy of characteristics for HaH care models based on scientific literature and by applying a taxonomy development framework. To validate the taxonomy, and to analyze the current landscape of HaH models we matched the taxonomy to HaH care models described in literature. Finally, to identify types of HaH care implementations, we applied the k-means clustering method to care models represented using the taxonomy. RESULTS: Our taxonomy consists of 12 unique dimensions structured into 5 perspectives following the progression from triaging, through care delivery, operational processes, and metrics for success: Persons and roles (2 dimensions), Target population (1 dimension), Service delivery and care model (6 dimensions), outcomes and quality metrics (2 dimensions), and training and education (1 dimension). Cluster analysis of 34 HaH care models revealed three distinct types: One cluster (50%, 17/34) focuses on patient eligibility and home environment suitability, a care model to be chosen for clinically complex patients. A second cluster (29.4%, 10/34) aggregates technology-enabled models using telemedicine and remote monitoring that are adaptable across settings. This type could be chosen for generalizable care. The third cluster (20.6%, 7/34) includes complex interventions involving informal caregivers and advanced medical devices, requiring caregiver training, supportive policies, and user-friendly technology to reduce caregiver burden and improve safety. CONCLUSIONS: The clusters identified highlight practical considerations for adapting HaH care approaches to patient and contextual needs. These findings can guide policymakers in developing guidelines and assist practitioners in tailoring HaH care models to specific patient populations. The challenges encountered in collecting information on different characteristics of the taxonomy underscore the urgent need for more comprehensive and standardized reporting in scientific papers on HaH interventions.
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Kerstin Denecke (2025) conducted a review in Hospital at Home (HaH) care models (n=34). Hospital at Home (HaH) care models was evaluated on Taxonomy dimensions and clusters of HaH care models. A novel 12-dimension taxonomy classified 34 Hospital at Home care models into three distinct archetypes: models for clinically complex patients, technology-enabled generalizable care, and complex interventions involving informal caregivers.
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