Research and quality improvement in dental data is very difficult because standardization of terms is still in its infancy. Whether in paper or electronic records, data differ across practices. One dentist might call a tooth “fractured” while another would label it “broken.” Automated analysis won’t detect the semantic similarity; instead, the system will record two different patient problems. This makes health information exchange extremely difficult except on a single record level, because a dentist must interpret the semantic information of every record.
This video brings to the fore the need for a three-pronged approach: terminology modeling, information modeling and inference (decision support) modeling. The robust information model developed by these researchers has great promise for design of usable, powerful EHRs.
If you would like to be part of this project and contribute to spreading standardization throughout dental data, contact Dr. Schleyer at firstname.lastname@example.org.
- There is a need for more standardization in clinical terminology used in Dental EHRs based on an information model
- Health information exchange, quality research and analytics need normalization and mapping of clinical data between systems in order to accomplish their goals and objectives.
- A three-pronged approach of information modeling, terminology standardization and inference/evidence data is critical for useful, exceptional EHRs.