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Biomedical subjects

D D Dankel

Publications and source records attributed to D D Dankel.

3 recordsLinked to original sources

Practical approach to evidence-based management of caries.

This paper discusses evidence-based management of dental caries with regard to: (1) need to adopt new office methods, (2) potential barriers to change, and (3) possible practical solutions to aid change. The need for classifying individual patients into low-, medium-, and high-risk caries groups is justified from a review of the epidemiological characteristics of caries. In addition, a deficiency is identified in traditional caries recording methods since they are unable to grade the severity and activity of individual lesions. The traditional basis of six-monthly recall examinations for all patients is shown from the literature to have no scientific support. It is suggested a three-twelve month recall interval be used, depending on a patient's risk group classification. Some barriers to change are identified as: (1) the collection of more comprehensive history and clinical caries data, (2) the complexity of evidence-based decision-making, and (3) dentists' difficulty in standardizing decision-making. A new pictorial classification for caries severity and activity is described. A demonstration decision-support system is presented in terms of assisting collection of data, automatic identification of risk factors, patient risk classification, and generation of a suggested treatment plan. Evidence-based management may result in change of professional manpower levels.

Dental Caries↗

Can low accuracy disease risk predictor models improve health care using decision support systems?

A prototype decision support system has been designed for managing dental caries using a risk assessment model. Caries is a multifactorial disease with risk prediction models having low sensitivity (65%) and moderate specificity (80%) for 2 or more new lesions. These models are inaccurate for targeting resources at high risk people. However, low risk individuals can be more accurately identified. If the activity of early tooth decay lesions, in low risk people, are monitored over time and only lesions beyond 1/3 of the dentin depth are filled, the number of annual fillings may be reduced by 50%. Currently, most US dental schools do not teach risk assessment for caries and encourage early treatment of lesions leading to a repair destruction cycle. The combination of a decision support system with a moderate accuracy specificity risk model for predicting low risk individuals may produce a significant improvement in caries management.

Decision Support Systems, Clinical↗

Standardizing data collection and decision making with an expert system.

The software for the pilot system has been completed. The appropriateness of the risk factor weights needs to be evaluated by clinical testing. However, this does not prevent the system from being used to teach the philosophy of risk group identification and selection of different management strategies according to disease activity. The current system does demonstrate a dynamic relationship between caries risk assessment/activity and different management strategies. A formal scientific evaluation of the effectiveness of the system as a teaching tool is being developed.

Data Collection↗