JMIR Publications

ABSTRACT

Background:

Displeasure with Clinical Decision Support Systems (CDSS) functionality is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to desired and actual clinical workflow. Computer-Interpretable guidelines (CIG) are used to formalize medical knowledge in clinical practice guidelines (CPG) in a computable language, however, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability.

Objective:

This has led the authors to propose a different approach in terms of how clinical knowledge and data are represented. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both Web and mobile applications. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines, with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow.

Methods:

We designed and implemented an architecture design for our CDSS, which uses the Model View Controller (MVC) architecture and a knowledge engine in the MVC architecture based on eXtensible Markup Language (XML). The knowledge engine design also integrated the requirements of matching clinical care workflow that was desired in the CDSS. For this component of the design task we used a work ontology analysis [1] of the Clinical Practice Guidelines (CPGs) for antenatal care in our particular target clinical settings.

Results:

Computer-Interpretable guidelines (CIGs) are used to formalize medical knowledge in a computable form that is contained in CPGs. In comparison to some other common CIGs used for CDSS, our XML approach can be used to take advantages of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly we can take advantages of its flexibility to standardize CIG structure design in a low-level specification language that is quite ubiquitous, universal, computationally efficient integrable with Web technologies and still human readable.

Conclusions:

Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal healthcare CPGs and their associated clinical workflows. The framework appears general enough to be useful with other CPGs in medicine. XML proved to be a language expressive enough to describe such planning problems in a computable form, both restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile applications where intermittent communication requires a small footprint and an autonomous application. It can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.