Clinical Decissions Support Systems
Clinical Decissions Support Systems(Cdss)
What are clinical decision support systems (CDSS)?
According to the definition on ‘Search health IT’, ‘a clinical decision support system (CDSS) is an application that analyzes data to help healthcare providers make decisions and improve patient care.’ The CDSS assists in making decisions by the necessary information but the final one is made by the user.
Types of Cdss- List 5 Components of Cdss
There are 3 components that make up the CDSS, they are:
- Data repository
- Rules engine
- Interface
Data Repository (DR)
This is a very large and complex system; it can even be called the ‘Brain’. The DR is where all the information needed for analyzing a situation is stored, hence it needs to be capable of handling terabytes of data at a time. The data can either be structured or unstructured taken from different medical institutions such as the British Medical Journal (BMJ). The data can also be acquired from previous diagnosis from the EPR. The information framework works by storing previous patient records that can later be retrieved if/when a similar situation is encountered and can be a lot more valuable when in use as helps provides more accurate data. As with every other system, the CDSS comes with its own set of challenges.
Solution
Growth rate of the data repositories that is created from various sources is too high and it is ever-challenging for any system to keep pace with it. Big data, with its capability to handle 4 Vs (Volume, Velocity, Variety and Value), is the solution to keep pace with the growth of the data repository and provide high-performing response times. Big data also handles a variety of data types in an integrated framework to provide a single view of information that can be used by the CDSS to provide decision support. Maintaining such huge data to provide zero down time and zero data loss with high performance response times is always a challenge from the infrastructure perspective.
Data repositories don’t always come in a standard format – this varies from structured tables to highly unstructured text material to charts and diagrams. It is quite challenging to handle all such different data types in a single framework.
Rules Engine (RE)
The rules engine is the central element that analyzes and interpret data from the data repository. Generally, it offers the foundation on decision making that can help the user make the most accurate and proper diagnosis for a patient.
Challenges
The creation and maintenance of rules is a complex process requiring both clinical and IT expertise.
Go for open source like Open CDSS from HL7, where the quality and dependency of the rules engine evolve continuously with contributions and validations from the world’s leading standards-related organizations and healthcare IT competency groups.
The performance of the rules engine is always in question given the range of complex rules that the CDSS has to process against such a voluminous knowledge data.
The quality, relevancy and dependency of the rules engine is not proven yet, as there are no healthcare domain certifications available for rules engines.
