Recall and Outlook

The use of relational databases for storage and retrieval of these large patient data is today successfully applied in a variety of medical domains in order to provide statistical analysis and documentation of care.  Several commercial products are available for storing and retrieving patient data including billing software.¹¹²  Effective EOHR data structures are needed to encounter attributes for the management of patient populations as well as for resource management within the practice.  However, the extraction of relevant information to a specific clinical scenario can be tedious and time consuming because sources for clinical data relevant to a particular context may be obscure, or indexing information necessary to locate data may be absent; thus, complicating search and retrieval.  One example of providing rapid access to medical facts, decision models, and commentary of specific use is DecisionNET that represents a unique model of medical knowledge bases.¹¹³  Object-oriented databases are used to represent domain knowledge.¹¹⁴  Unfortunately, similarly structured dental databases are rare to find, since a corresponding representation of thoughts, words, and things using the Unified Medical Language System (UMLS)¹¹⁵ does not exist for dentistry.  Dentistry contains a much larger set of knowledge than described in this paper, which needs to be structured and conceptualized like the Systematized Nomenclature of Medicine (SNOMED).^116-119

Fortunately, the ADA is counting on the belief that a systematized set of diagnostic and descriptive terms and codes will aid individual dentists and dentistry as a whole.  Thus, they initiated a task force on the development of SNODENT.  It includes standardized terms for defining dental disease in an electronic environment.  These terms and codes, developed by the Council on Dental Benefit programs, will allow dentists to electronically document a full range of information about their patients including physical findings, risk factors, and functional status.¹²⁰  The development and implementation of a dental metathesaurus and its domain ontologies are as important for the design and implementation of an image management and communications system termed IMACS.^121,122  Once these concepts become reality, we can automate and go beyond the traditional dental recall system and use, for example, protocol-directed temporal-abstraction systems such as EON.¹²³

As described so far, there are a number of different demands and tasks for dental informatics to solve ongoing and future problems in clinical dentistry.  Figure 2 summarizes the different target values based on data presented in this paper and on relationships between patient requirements and dental characteristics in order to depict the importance to dental informatics.  In addition, this quality matrix demonstrates an importance weighting of the dental characteristics and correlation between these target values and dental characteristics.  Finally, results of competitive site and technical evaluations of dental schools are entered.  They represent the author's subjectivist opinion across European and U.S. sites for the sake of completion of the final charts and, thus, these sites will remain anonymous.

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Citation Number: Vol. 3, No. 1, Page 039