HOW EHR systems augmenting Doctors at CDSS (Clinical decision support systems)
NEED
In the era of Industry 4.0, the amount and quality of clinical data are growing rapidly due to electronic health records (EHRs), and significant advancements in technical capabilities for handling and processing data (Big data) and utilizing various NLP and computer vision algorithms (AI). Any product developed in this context should provide high-quality clinical decision support to fully leverage the benefits of electronic health records data.
There are four major clinical decision support system (CDSS) functionalities that every EHR tool should provide to assist doctors with data and insights:
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System Function: The system should provide two basic functions - determining what is true and what to do. This applies to CDSS, where advice on fixed set data should be readily available, and recommendations on which test to order for further differential diagnosis or which drug to prescribe for the patient’s current condition should be advised based on trained models and data from the EHR system.
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Advice: The system should be able to provide advice on passive or active nature. Passive advice is under the user’s control, whereas active systems automatically provide advice based on models and data relationships. However, active advice may cause alert fatigue with the user, so the system should be cautious about what advice is provided in passive or active nature.
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Communication: The system should have better interoperable capabilities and be able to communicate information easily between various departments.
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Human-Computer Interaction: The product design should be easy to use and apply and should align closely with real-time workflow in terms of design and architecture.
The decision process should incorporate additional statistical models, mathematical techniques, and increasing computing power. Complex models such as Bayesian models, artificial neural networks, and machine learning algorithms should be utilized to provide improved outcome predictions, prioritize treatment, and help choose the best course of action. The system should also have better interpretability capabilities.
Our platform, Medeva.io, offers all these functionalities to assist doctors at the point of care.