ClinicalTrials.gov
public full text
Public Domain
Continuous Monitoring of Patients in and After the Acute Admission Ward to Optimize Clinical Pathways
Hospitals aim to hospitalize patients when necessary and discharge patients when possible. However, the triage process and discharge management of patients in e.g. the Acute Admission Ward, is not a trivial task. The upcoming technology of wearable monitoring devices, whereby patients can be continuously monitored with an unobtrusive vital signs device, might help getting more insight into patients' health condition and thus help facilitate efficient and effective triaging. Therefore, the primary objective is to assess the effects of continuous monitoring of patients in the acute admission ward (AAW) on the percentage of patients who can be discharged home. Secondary objectives are to assess the length of stay in the acute admission ward and in the in-hospital wards, as well as the effect on admission to the intensive care unit, rapid response team calls and hospital readmission. The predictive value of algorithms applied to the monitoring data combined with other parameters to detect timely deterioration and predict discharge will be assessed. Facilitators and barriers for implementing such a system will be investigated.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Noncontact, Handheld Device for Measurement of Respiratory Rate#1127296
- Clinical acuity and National Early Warning Scores (NEWS2) of remotely monitored patients on virtual wards: A retrospective cohort study.#143353
- Smart Discharges for Older Children#873014
- Interactive Digital Health Tools to Improve Patient Safety in Acute Care#833970
- SmartWatch-driven AF Detection in Stroke Patients#1198313
Record · ID 1260277
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive