The Value of Remote Vital Signs Monitoring in Detecting Clinical Deterioration in Patients in Hospital at Home Programs or Postacute Medical Patients in the Community: Systematic Review
Bibliographic record
Abstract
Background Vital signs monitoring (VSM) is used in clinical acuity scoring systems (APACHE [Acute Physiology and Chronic Health Evaluation], NEWS2 [National Early Warning Score 2], and SOFA [Sequential Organ Failure Assessment]) to predict patient outcomes for early intervention. Current technological advances enable convenient remote VSM. While the role of VSM for ill, hospital ward–treated patients is clear, its role in the community for acutely ill patients in the hospital at home (HAH) or postacute setting (patients who have just been discharged from an acute hospital stay and at increased risk of deterioration) is less well defined. Objective We assessed the efficacy of remote VSM for patients in the HAH or postacute setting. Methods This systematic review adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched studies in PubMed (MEDLINE), Embase, and Scopus. Studies focused on the postacute phase were included, as only 2 case series addressed the HAH setting. Risk of bias (ROB) was evaluated using the Cochrane Risk of Bias Tool for randomized controlled trials (RCTs), the Newcastle-Ottawa scale for observational studies, and the case methods outlined by Murad et al for case reports. The GRADE (Grading Recommendations Assessment, Development, and Evaluation) framework was used to assess the certainty of evidence. Outcomes of interest included hospital readmissions, mortality, patient satisfaction, and compliance. Risk ratios (RR) were used to measure effect sizes for readmission and mortality, with patient satisfaction and compliance reported descriptively. Results The search yielded 5851 records, with 28 studies meeting eligibility criteria (8 RCTs, 7 cohort studies, and 13 case series). Two focused on HAH, while 26 studies addressed the postacute phase. Nineteen studies looked at heart failure, 3 studied respiratory conditions, and 6 studies studied other conditions. Meta-analysis was conducted with 6 studies looking at hospital readmission within 60 days and 4 studies at mortality within 30 days. Readmissions did not significantly decrease (RR 0.81, 95% CI 0.61-1.09; P=.16). Significant heterogeneity was observed for readmissions (I2=58%). Conversely, mortality reduced significantly (RR 0.65, 95% CI 0.42-0.99; P=.04). There was no significant heterogeneity in mortality (I2=0%). There was high heterogeneity in the study populations, interventions, and outcomes measured. Many studies were of poor quality, with 50% (4/8) of RCTs exhibiting a high ROB. The certainty of evidence for both readmission and mortality was very low. Conclusions Published data on the effects of remote VSM in acutely ill patients at home remains scarce. Future studies evaluating all common vital signs (heart rate, blood pressure, oxygen saturation, and temperature) with consistent monitoring frequencies and clear intervention protocols to better understand how to integrate remote VSM into HAH programs are needed. Trial Registration PROSPERO CRD42023388827; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023388827
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".