Utilizing Dental Electronic Health Records Data to Predict Risk for Periodontal Disease
Periodontal disease can lead to loss of affected teeth and is seen in persons 30 years and older in the United States. The major risks attributed to developing periodontal disease are systemic diseases like diabetes, cardiovascular diseases, and habits such as smoking.
The authors in this article explored the risk factors associated with periodontal disease which they gathered from the patient’s electronic health record (EHR).
The intention of the authors in this article were to make a risk prediction model for the disease so they extracted known risk factors for periodontal disease from 200 randomly selected patients from a data set of 2370 patients who came in for a comprehensive oral examination for 1 year at Indiana University School of Dentistry, Indiana. The used the risk prediction and visualization tool to assess the risk factors of a patient to periodontal disease.
The authors found that bone loss and patient demography played a role in the population at high risk for the disease. The risk prediction and utilization method showed 1076 patients at high risk for periodontal disease in this study.
The tools used in this study were the risk prediction and utilization method, which had the potential to detect risk factors for periodontal disease. These tools would definitely be efficient to address the treatment needs at the point of care.
The above critical review of the article showed the use of a tool that could be used in public health as a disease management tool to educate the patient regarding their risk factors and how it relates to their oral health. Thus, this is useful to the patient and the dental care provider for preventing and treating periodontal disease.
- Utilizing Dental Electronic Health Records Data to Predict Risk for Periodontal Disease. http://www-ncbi-nlm-nih-gov.ezproxyhost.library.tmc.edu/pubmed/26262380