Observational studyFrontiers in public health2022
One-Bed-One-Team-Does an Integrated General Hospital Inpatient Model Improve Care Outcomes and Productivity: An Observational Study.
Observational study in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Evolving practice of general internal medicine in the current medical landscape.Internal medicine journal · 2026Review
- Expanding the role of community hospitals to promote population health in Singapore.The Lancet regional health. Western Pacific · 2025Review
- The Impact of Pandemic-Driven Care Redesign on Hospital Efficiency.Risk management and healthcare policy · 2024Review
- Community hospitals of the future: the role of community hospitals to mitigate health system burden in Singapore.Frontiers in health services · 2024Article
- Community hospitals of the future-challenges and opportunities.Frontiers in health services · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: With the increasing complexity of healthcare problems worldwide, the demand for better-coordinated care delivery is on the rise. However, current hospital-based practices remain largely disease-centric and specialist-driven, resulting in fragmented care. This study aimed to evaluate the effectiveness and feasibility of an integrated general hospital (IGH) inpatient care model. Methods: Retrospective analysis of medical records between June 2018 and August 2019 compared patients admitted under the IGH model and patients receiving usual care in public hospitals. The IGH model managed patients from one location with a multidisciplinary team, performing needs-based care transition utilizing acuity tagging to match the intensity of care to illness acuity. Results: 5,000 episodes of IGH care entered analysis. In the absence of care transition in intervention and control, IGH average length of stay (ALOS) was 0.7 days shorter than control. In the group with care transition in intervention but not in control, IGH acute ALOS was 2 days shorter, whereas subacute ALOS was 4.8 days longer. In the presence of care transition in intervention and control, IGH acute ALOS was 6.4 and 10.2 days shorter and subacute ALOS was 15.8 and 26.9 days shorter compared with patients under usual care at acute hospitals with and without co-located community hospitals, respectively. The 30- and 60-days readmission rates of IGH patients were marginally higher than usual care, though not clinically significant. Discussions: The IGH care model maybe associated with shorter ALOS of inpatients and optimize resource allocation and service utilization. Patients with dynamic acuity transition benefited from a seamless care transition process.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.