The quality of hospital EHR data is vital to the delivery of safe and effective patient care, and for the reuse of the data across the Learning Health System.
The vision of i~HD is to improve health care and to accelerate research through more trustworthy learning from health data. We engage with all stakeholders in order to co-create high- quality and secure environments for data sharing and data use. We aim to maximise efficiency and effectiveness, have better data quality, improve connectivity between practitioners and keep the patient centre stage.
To enable engagement with all stakeholders, i~HD is a neutral, not-for-profit institute.
Many European hospitals have expressed to us a wish to be better Learning Health Systems:
In response to this, i~HD has developed assessment methods to guide data quality improvement, and is actively promoting the importance of data quality across Europe.
The i~HD DQS4H can assess and help improve the quality of EHR data for hospitals wishing to:
The i~HD Data Quality Task Force members bring over a decade of expertise in electronic health records, health data quality, assessment methodologies and certification programmes.
Based on extensive literature reviews the Task Force defined nine Data Quality Dimensions. As a result of original research projects (including PhD publications) algorithms were developed to generate validated and reproducible quantitative assessments of these data quality dimensions. The data quality assessments are conducted using both quantitative and qualitative analyses.
Hospitals choose which data to focus on for the assessment, depending on their main objectives.
In collaboration with:
After providing feedback on the report, we can provide advice on improvement strategies, and run workshops for your teams.
Pragmatic: minimally invasive to hospital operations
Evidence based: well researched, published, assessment methodology
Flexible: can be tailored to your data quality drivers
Focussed: we can help you choose the most suitable dimensions and EHR data variables
Staged: clear sequence of steps with regular interactions and feedback loops
Holistic: we consider quality in the context of your user workflows and your EHR system
Extendable: data sets can be added incrementally, to chart out a data quality improvement journey
For further information please contact via DQS4H@i-hd.eu