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Hospital-Level Care at Home for Adults Living in Rural Settings

2025· article· en· W4416867550 on OpenAlexaffabout
David M. Levine, Meghna Desai, Sarah Findeisen, Stephanie Blitzer, Ryan Brewster, Michelle Grinman, Steven C. Amrhein, Mitchell Wicker, Patricia C. Dykes, Stuart R. Lipsitz

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsRural areaMEDLINEHealth carePopulationQualitative research

Abstract

fetched live from OpenAlex

Importance: Home hospital provides hospital-level care at home for patients with acute illness who would traditionally be cared for in a brick-and-mortar (BAM) hospital. While most home hospital programs have been implemented in urban areas, its feasibility in rural areas, where access to care is a major challenge, is unknown. Objective: To compare home hospital care with BAM hospital care for patients residing in rural areas. Design, Setting, and Participants: This randomized clinical trial took place from 2022 to 2023 with a 30-day follow-up in 3 rural areas in the US and Canada. Participants were adults recruited in the emergency department who required hospital-level care for select acute conditions (infections, heart failure, chronic obstructive pulmonary disease or asthma, and other diagnoses). Interventions: Patients in the home hospital group received acute care at home, including in-home nurse and/or paramedic visits, remote physician care, intravenous medications, remote monitoring, video communication, and point-of-care testing. Patients in the BAM group received services at a rural BAM hospital. Main Outcomes and Measures: The primary outcome was the relative change in the acute care episode's direct cost. Secondary outcomes were 30-day readmission, days at home within 30 days of discharge, and physical activity. Exploratory outcomes included the Picker Experience Score and Net Promoter Score. Results: A total of 161 patients (79 home; 82 BAM) with mean (SD) age of 64.4 (17.2) years (home) and 64.9 (14.1) years (control) were included. Most were female (home, 52 [65.8%]; BAM, 50 [61.0%]). The adjusted mean cost of the acute episode was not significantly different (home vs BAM, 14% greater; 95% CI, -6% to 39%; P = .19). There were no significant differences in 30-day readmission (home vs BAM: 8 [10.1%] vs 14 [17.1%]) or mean (SD) days at home within 30 days of discharge (home vs BAM: 28.6 [3.4] vs 28.4 [3.4] days). Patients in the home hospital group were less sedentary, according to accelerometer measurements, than those in the BAM group (mean [SD], 78.0% [10.4%] vs 86.0% [7.2%] of the day sedentary; mean difference, -8.0%; 95% CI, -12.8% to -3.3%; P < .001) and had more mean (SD) steps daily (834.1 [1219.6] vs 120.4 [206.0] steps; mean difference, 713.7 steps; 95% CI, 290.2 to 1137.2 steps; P < .001). Total mean (SD) length of stay (ie, BAM and home hospital days for intervention patients and BAM days for control patients) was not significantly different (home vs BAM: 6.7 [5.0] days vs 5.4 [4.4] days), although patients receiving care at home transferred late in their course (mean [SD] day of transfer, 4.2 [4.3] of 6.7 days). Patients in the home hospital group reported better experiences than those in the BAM hospital group: the mean (SD) Picker experience score was 13.4 (2.6) vs 11.0 (3.8) (mean difference, 2.4; 95% CI, 1.0 to 3.8; P < .001), and the mean (SD) net-promoter score was 88.4 (32.3) vs 45.5 (69.9) (mean difference, 43.0; 95% CI, 17.5 to 68.5; P < .001). Safety events occurred in 11 (14.1%) home patients vs 10 (12.4%) BAM patients (mean difference, 1.8%; 95% CI, -8.1% to 11.6%; P = .74). Conclusions and Relevance: In this randomized clinical trial of home hospital care in rural settings, cost and readmission were unchanged while patient activity and experience improved. Late transfer home likely attenuated the intervention's effect. Trial Registration: ClinicalTrials.gov Identifier: NCT05256303.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.284
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2025
Admission routes2
Has abstractyes

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