Medical device integration
Data dashboards
Scientific research
Manual collection of data is both a time consuming, limiting, and comprehensive task. Often, only a fraction of the measured healthcare data is registered and recorded, which means that a lot of knowledge and large volumes of measured data are lost. There is also the potential risk of incorrect readings or recordings in the patient’s electronic medical record.
Studies show that automated data-collection from medical devices can reduce documentation errors from 18% to 0%. Furthermore, the time from data is registered to it is available in the patient’s electronic medical record is significantly reduced.
In addition, care providers will benefit from spending less time on registration procedures, having access to high quality data, and accessing data faster in the patient’s electronic medical record.
Medical Device Integration
To collect, store and distribute data the medical devices are wirelessly or manually connected to Columna VitalShare. As soon as data is collected, it is stored in Columna VitalShare and can be distributed to any patient data application like the electronic medical record.
Easy-to-read data visualisations
Clinical staff have easy access to data through the Viewer app which provides overview of the accumulated medical device data for clinical verification. The overview is both easy to read and interactive, promoting quick overview and enabling staff to deep dive into data for further analysis. The solution supports and optimises the utilisation, visualisation, and validation of healthcare data from medical devices, which provides a better foundation for deciding on the right course of action.
Data-based research and analysis
All data from Columna VitalShare is registered and logged in a Vender Neutral Archive. From here the high-quality data is easily accessed through open standardised interfaces. Having access to more and accurate data, which up until now has been difficult or impossible to obtain, paves the way for new research areas and additional analysis.