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 Table of Contents    
Year : 2013  |  Volume : 3  |  Issue : 1  |  Page : 44-46
Dental informatics

Postgraduate Students, Department of Oral and Maxillofacial Pathology and Microbiology, Meenakshi Ammal Dental College and Hospital, Maduravoyal, Chennai, Tamil Nadu, India

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Date of Web Publication13-Feb-2014

How to cite this article:
Haridass S, Sampath V. Dental informatics. J Educ Ethics Dent 2013;3:44-6

How to cite this URL:
Haridass S, Sampath V. Dental informatics. J Educ Ethics Dent [serial online] 2013 [cited 2020 Mar 30];3:44-6. Available from: http://www.jeed.in/text.asp?2013/3/1/44/126945

Dental informatics is a sub-discipline of biomedical informatics which focuses on the application of computer and information science to improve dental practice, research, education and management. Dental Informatics can improve effectiveness, efficiency diagnosis, treatment, disease prevention and quality of patient care. During the last forty years Dental Informatics has developed into a research discipline of significant scale and scope.

   Dental Informatics: An Emerging Biomedical Informatics Discipline Top

Titus K. L. Schleyer

of Dental Education, November 2003

Since the advent of computer revolution, usage of digital computers in biomedicine has been in use. Informatics is a research discipline that uncovers fundamental principles and methods relating to information and computers and it emerged as a distinct concept in 1960's followed by medical informatics in 1970's and dental informatics made its entry by the 1980's. Currently, it is a small but growing discipline with two formal training programs (since 1997) and one journal dedicated solely to dental informatics (Journal of Computerized Dentistry). Two types of informaticians are present: Those actively involved in research and those actively involved in application development and implementation. A thorough understanding of the psychology and cultural traits of individuals, groups and organizations; the workflow; the organizational and systems infrastructure and available resources are essential to implement computer systems successfully.

Maojo et al. have stated that the complexity of information, environmental issues and cognitive, ethical and emotional aspects contribute to the difficulty of computerizing medicine. Studies state that though more than 85% of dentists use computers in their dental office, the percentage of them using computer based patient records is found to be quite low. The scientific methods in informatics are primarily derived from four research areas: Computer science, information science, cognitive science and telecommunications. Yet, factors such as social sciences, psychology, anthropology, linguistics, engineering etc. also play a significant role. The problems in dental practice, research and education are addressed by combining two or more of the primary methodological foundations mentioned. However, the exact relationship between biomedical informatics and dental informatics is still under debate.

By understanding the goals and methods in a better way and discriminating what constitutes informatics and what does not, individuals will be able to identify how informatics could help them efficiently for their own work.

   Better Informed in Clinical Practice: A Brief Overview of Dental Informatics Top

P. A. Reynolds, J. Harper, S. Dunne

British Dental Journal Volume 204 No. 6 Mar 22 2008

The advent of dental informatics was an age old concept which eventually was raised and faded away with time, due to some technical and financial issues. Dental informatics aims at dealing dental problems using scientific communication by four layered structure namely, model formation, system development, system installation and evaluation and modification. The model formation involves setting up standardized terms and details. Developing the software is a complicated process where information should be formatted and implemented using icons. Using the icons can be confusing as it is difficult to specify them. System installation has its own limitations as the practitioners find it difficult to use these technologies in the middle of the treatment procedure.

Voice recognition is later developed to improve the communication, but it is not widely used as its work is still under progress. Clinical decision support system is one of the important tools of dental informatics where clinicians can take opinion in making diagnoses and planning treatment plans. They comprise groups registered in specific support systems and help each other in specific fields. It helps the practitioner to consult and arrive at better diagnoses. This support system captures knowledge from relative fields of research, clinical practice, literature references etc.

Advancement in the dental informatics is the emergence of electronic patients records (EPR). They avoid the usage of age old paper records and EPR are used in policy makers and for other fund regarding issues. They are even used to produce standard reports of the patient.

Future of dental informatics is based on the three consecutive developments namely computing clinical applications, creation of standard computer coded terms and new computational dentistry.

   Biomedical Informatics and Translational Medicine Top

Indra Neil Sarkar

Journal of Translational Medicine 2010;8:22

Bioinformatics has a new role to bridge in translational medicine helping in better patient care and newer advancements. Translational medicine aims at creating newer treatment modalities for the betterment of the patient by initially identifying what is the exact requirement followed by implementation and its application among people. Translational medicine also comes along with some difficulties and barriers, which can be solved by the use of bioinformatics to a certain extent. It should be clearly emphasized that bioinformatics is used in translational medicine not to improve the informatics whereas its main objective is to improve the patient treatment care.

Various subunits of bioinformatics are used in translational medicine in the identification of pathogenesis, identifying molecular and cellular basis, meeting patient needs etc. Decision support system mainly deals with the maintenance of collected information and viewed under categories such as knowledge acquisition, knowledge representation, interferencing and explanation. These will be made into a design by the translation medicine group and then implemented for research regarding new treatment plans. This is followed by the standardizing the data obtained by exchanging and viewing the data in order to attain to the goal faster. The information gathered should be retrievable at any point to compare and link the users to the required information.

Patient data is collected in electronic health records and then used when needed in translational medicine. The bioinformatics play a very important role in collection of data, organizing, implementing and testing trans-disciplinary hypothesis. Thus success of translational medicine is greatly influenced and helped by the role of bioinformatics thus taking the treatment modality to a newer range.

   Educating Future Clinicians about Clinical Informatics: A Review of Implementation and Evaluation Cases Top

Kathleen Gray, Ambica Dattakumar, Anthony Maeder, Helen Chenery

European Journal for Biomedical Informatics 2011;Volume 7 Issue 2:En48-en57

There is a need for the future healthcare individuals to learn about clinical informatics to develop a sophisticated update in their respective fields and to improve the overall practice. It could be implemented by introducing training curriculum during their respective study periods. The curriculum has to be built upon consistency and efficiency. Reference to the literature of clinical informatics should be done in order to develop skills and teaching materials.

The future health care professionals should know the value of clinical informatics, its outcomes, contents undertaken and correlation with standard, tracking and delivery modes. The curriculum should be evaluated and implemented efficiently. The methods such as collection of literature, databases and references are done to run the program correctly.

Among all the health care professionals such as, medicine, nursing, dental, allied sciences and complementary medicine, only very few are actually accounted in the curriculum. Many remain unaccounted whereas with the others are completely ignorant. This show the poor reach of clinical informatics, which could be due to lack proper curriculum or gaps in teaching programs. Thus efforts should be made to establish proper learning curriculums during their respective courses and to improve on the teaching facilities.

   Modern Dentistry @ Computerization Dot Com: An Epigrammatic Sketch of the Present Scenario Top

Puneet Kumar, Prince Kumar

J Adv Med Dent Scie Res 2013;1:17-28

Before 1946, the desk calculators and punch card systems were the only data processing machines and the first electronic computer, electronic numerical integrator and calculator was developed in 1946. This was followed by the development of the various generations of the computers, the personal computers, portable computers and the microcomputer. In the mid 1960's, computers were used only for specific and limited tasks in dental schools and practices but due to its significant progression the role of computers and its relationship with dentists improved by the 1980's. Computer systems can be practically applied in office management, digital imaging and radiography. It can also be used for administrative applications such as billing, accounting; clinical applications like computerized cephalometrics, computer-aided design and computer-aided manufacturing (CAD-CAM); other applications like literature review, case presentation and for entertainment and family use. It is seen that almost every report published on dental epidemiology has used computer technology for analytic purposes.

The qualitative information collected for a survey is coded in numerical or alphabetical characters. The data preparation includes three phases namely collection, coding and punching. The collected dental data is analyzed by abstracting the data according to the epidemiological indices and analyzing the results of the groups using indices. For the past 15 years, CAD/CAM system, CEREC system and computer-driven milling devices for inlays, on lays, crowns etc. have contributed significantly to the field of dentistry. Digital photography, digital radiography, intraoral television, computerized approximation of orthodontic tooth movement and computerized shade selection are the advancing applications that are efficiently incorporated by most dentists nowadays. A relatively new field called teledentistry combines dental care with telecommunication technology to increase access to dental care and aids in advancements in dental education. At reasonable costs, it extends care to patients in rural areas. Hence, dental informatics should be aimed at improving diagnosis, treatment and disease prevention, pain relief and improvement of oral health.

   Using Electronic Dental Record Data for Research: A Data-mapping Study Top

K. Liu, A. Acharya, S. Alai and T. K. Schleyer

Journal of Dental Research May, 2013

Gilbert et al. in 2011 stated that capturing research data is important as anecdotal evidence suggests that dental practices record some data that are also collected in practice based research network studies. Most records are collected manually on case report forms which are submitted to the Data Coordinating Center directly or after local entry and they are finally merged into the study database. The disadvantage of this method includes delayed data transmission, possible inaccuracies and increased cost factor and time consumption. It was inferred that if appropriate electronic data had been available for the CONDOR-case control study of osteonecrosis of the jaws, 2009 the total time taken for acquiring the data would have been reduced by about 40 min per participant. Using electronic data can have multiple benefits such as increased efficiency, reducing burden for the data entry staff, reducing costs, conducting faster studies, decreasing errors etc.

The authors carried out a study to determine which type of practice-based studies are most feasible based on the currently available data on Electronic dental record (EDRs). Preliminary and final mapping was done on the Cancer Data Standard Registry and Repository as well as the dental information model (DIM). Results concluded that 33% of the DIM data elements matched at least one common data element (CDE) completely and 9%partially, translating to about 9% and 2% respectively of all data elements used in practice-based research network studies. Data about dental anatomy, medications and items such as oral biopsy and caries were found to be the most common CDEs. The study concluded that a significant number of data elements in general dental records can be either mapped completely or partially to data field in research studies yet further studies are necessary to determine the feasibility of electronic clinical data for research purposes.

Correspondence Address:
Sruthi Haridass
Postgraduate Students, Department of Oral and Maxillofacial Pathology and Microbiology, Meenakshi Ammal Dental College and Hospital, Maduravoyal, Chennai, Tamil Nadu
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Source of Support: None, Conflict of Interest: None

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