ArticleHealthcare (Basel, Switzerland)2024
User Experience Study of the Patient Monitoring Systems Based on Usability Testing and Eye Tracking.
Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Psychometric evaluation of the Spanish-language version of the health information technology usability evaluation scale (Health-ITUES).International journal of medical informatics · 2026Article
- Characterizing Human Visual Performance in Dim Industrial Environments: An Eye-Tracking Sensor-Based Study on Mine Monitoring Interface Layouts.Sensors (Basel, Switzerland) · 2026Article
- Usability of a Patch-Type Ultrasound System for Non-Invasive Hemodynamic Monitoring: A Simulation Study in Anesthesiologists.Healthcare (Basel, Switzerland) · 2026Article
- The Patient Monitoring Roundtable as Catalyst for Health Care Innovation: Case Study.Journal of participatory medicine · 2026Article
- Usability Validation of an Integrated Hemodynamic and Pulmonary Monitoring System Using Eye-Tracking Analysis.Journal of clinical medicine · 2026Article
- Usability Evaluation of a Central Monitoring System with AI-Based Cardiac Arrest Prediction in the ICU.Journal of clinical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
BACKGROUND/
objectivesThe patient monitoring system is a critical tool commonly used in hospitals, making it essential to assess caregivers' user requirements and satisfaction with its usability. In intensive care units (ICUs), the usability of these systems is closely linked to the work efficiency of key users, such as nurses, and directly impacts patient safety and treatment outcomes. This study evaluates the usability of patient monitoring systems in intensive care units (ICUs), focusing on user requirements and satisfaction among nurses, the primary users. Usability is directly linked to work efficiency and patient safety, with post-marketing surveillance (PMS) data from overseas, highlighting issues such as unrecognized alarms, leading to worsened patient conditions.
methodsThis study involved 22 ICU nurses who had used the system for over a year, assessing usability through testing, satisfaction surveys, the Health-ITUES, and eye-tracking analysis.
resultsThe results showed a high success rate (94%) and positive satisfaction scores (4.15, SD = 0.88), with a Health-ITUES score of 4.13 (SD = 0.78). Eye tracking revealed that some functions, including alarms, were overlooked or not recognized.
conclusionsRecommendations include improving the interface for alarm messages and recording deletion functions to enhance user satisfaction and patient safety.
Indexed as
Identifiers
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.