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Center for Dental Informatics, University of Pittsburgh, School of Dental Medicine, 3501 Terrace Street, Pittsburgh, PA 15261; titus{at}pitt.edu
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Abstract |
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 TOP Abstract IntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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KEY WORDS: Dental informatics • dental research/trends • dental practice • dental education • medical information
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Introduction |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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To help answer these questions, this paper is structured into three sections. We first briefly review the growth and size of the dental informatics literature, the individuals who have contributed to it, and the discipline’s achievements. Much of the information in this review is drawn directly from contributions to this conference. Other material is based on our ongoing observation of developments in the discipline during the last 15 years. Second, we discuss a set of research challenges for dental informatics that were postulated more than ten years ago (Lipton, 1992) and assess the progress that has been made toward meeting these challenges. Hindered by the difficulty of quantifying such progress exactly, this assessment is necessarily informal. We then update the list of challenges to reflect contemporary trends, problems, and technologies. Last, we conclude with a set of recommendations intended to help dental informatics grow to its full research potential. In general, this paper is intended to stimulate discussion, not to provide a set of ready-made answers, for the questions posed above.
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History and Background |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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An examination of the dental informatics literature (Schleyer et al., 2003) presents important clues to the development of the field. In April, 2003, approximately 620 papers in dental informatics had been indexed in MEDLINE since 1975. This number underestimates the true total to some degree, but provides at least some estimate for the size of the relevant literature (Schleyer et al., 2003). More important than the size, however, are some other characteristics of this literature. Compared with other dental specialties, the yearly number of publications in dental informatics is quite small (dental informatics—approximately 50 papers per year; endodontics—approximately 300 papers per year; and oral medicine—approximately 2800 papers per year) (Yang et al., 2001). However, with a 10% annual growth rate for the last ten years, the dental informatics literature seems to be growing more than three times faster than that of the seven dental specialties analyzed by Yang et al.(2001), which grew at a combined rate of 3% annually during the same period. While the metric of publication output is necessarily somewhat imprecise, it nevertheless provides a rudimentary basis for comparing dental informatics with the established dental disciplines. Of approximately 1700 unique authors in dental informatics since 1975, 97.5% have published three or fewer papers. This indicates that only a few individuals have made dental informatics their academic career.
Despite these developments in the literature, additional potential for the evolution of the discipline exists. While the early and mid-1990s saw the creation of several dental informatics positions at dental schools, few new positions have become available in the last five years. During the same time, there was no net gain in the number of academic departments exclusively focused on dental informatics. (In the US, between three and five organizational entities devoted to dental informatics exist at dental schools, depending on the definition of "department".) The dental industry is beginning to show interest in informatics expertise, and some larger dental-care settings are looking to applied informaticians to guide and direct the development and implementation of their clinical and administrative information technology (IT) systems. Despite these developments, employment opportunities for recent graduates of dental informatics post-graduate programs have been few and far between. As a result, a growing and well-trained cadre of scientists has little opportunity to contribute to dental practice, research, and education. Nevertheless, significant research challenges in dental informatics exist.
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Research Challenges |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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for a summary of Lipton’s recommendations). Without a doubt, we have made progress addressing many of the challenges Lipton posed. For instance, the contributions of dental and craniofacial research to genetic, proteomic, clinical, and epidemiological databases have been substantial. The NIDCR and the Centers for Disease Control and Prevention have established the Dental, Oral and Craniofacial Data Resource Center (NIDCR, 2003a), which collates survey data, data collection instruments, and references, and provides flexible query capabilities. The public availability of high-quality resources such as MEDLINE and MEDLINEplus has made valid and reliable information more accessible to dental clinicians, educators, researchers, patients, and the public. Many investigators have studied how decision-support systems could assist problem-solving in clinical diagnosis and therapy (White, 1996). The Internet has made possible the establishment of large-scale communities where timely and targeted distribution of relevant information is becoming a distinct possibility, if not a reality. Standardization efforts in dental informatics are beginning to show practical results, as evidenced by the recent publication of several ANSI standards by the ADA Standards Committee for Dental Informatics (ADA, 2003a).
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Progress in information collection and dissemination has been mixed. The Internet has made information distribution and access technically trivial. While tardy modem connections, copyright issues, and slow-moving content providers are ongoing problems, we can foresee the day when almost all information and computer resources required by biomedical professionals are available electronically, on demand, and independent of location. The more thorny questions to address include when, how, and in what form information should be presented, especially in an information economy where attention is quickly becoming the limited resource (Coiera, 2000). Lipton (1992) suggested DENTLINE, a literature database similar to MEDLINE, focused exclusively on dental issues, as one measure to make information delivery more targeted and relevant for dental professionals. While a system such as DENTLINE has not come into being, it is possible to search only the dental journals in MEDLINE with search interfaces such as PubMed, the Web interface to MEDLINE provided by the NLM. Generally, however, MEDLINE, the Unified Medical Language System, GenBank, and many other major databases continue to serve all biomedical professionals rather than a defined subset. Special information-filtering mechanisms (Bartling, 2003) could achieve the intent of DENTLINE while preserving the advantages of large, homogeneous collections of information in biomedicine. A major portion of Lipton’s proposed goals deal with effective knowledge management, despite the fact that they are not labeled as such. Knowledge management systems maintain data, information, and problem-solving methodologies in an organized, comprehensive, flexible, and accessible fashion. Yet, dentistry has not succeeded in building such systems. We continually create and maintain many separate and independent stores of individual and aggregate data and information. The overwhelming majority of problem-solving methods exist in formats that are inaccessible to computers (such as in research papers, systematic reviews, textbooks, and the heads of scientists, educators, and practitioners). Thus, the absence of effective knowledge management hampers progress in all fields of dentistry and retards the transition of useful innovations to direct patient care.
The need to acquire more aggregate data about patients, their diagnoses, their treatment, and the associated outcomes remains as relevant now as it was ten years ago (NIDCR, 2003b). Systematic and large-scale data-gathering on patients remains the exception rather than the rule. While some large and integrated dental care delivery systems are beginning to amass sizable collections of patient data, health services researchers, for the most part, must still make do with the billing databases of insurers as their raw material, inadequate as they may be. The NIDCR recently cleared practice-based research networks (PBRNs) as a new concept for dental research (NIDCR, 2003c), and perhaps this will mark the beginning of a connection between the patient information locked up in dental practices and the researchers who can answer pressing questions using it. However, without some standardization, data from PBRNs will not be as useful as they could be.
Standardized vocabularies and information models, a key component in the representation of biomedical data, have shown little progress in dentistry in the last ten years. The ADA’s Current Dental Terminology (CDT) has been updated and augmented regularly, but is limited to treatment procedures. The ADA’s Systematized Nomenclature of Dentistry (SNODENT) project, an effort to create a comprehensive diagnostic vocabulary, has resulted in a terminology that has been neither formally evaluated nor used on a grand scale. Many other areas of dental practice, research, and education would benefit significantly from the availability of standardized vocabularies, and their continued absence is a significant impediment to progress.
One can make three key observations from Lipton’s challenges formulated more than a decade ago. First, most of them truly are grand challenges (Sittig et al., 2003), or we would have solved them already. Knowledge management, computer-based oral health records, and dental decision support systems are examples of very difficult and complex research issues for dental informatics. Such challenges can be met only by a large number of scientists exploring many different potential solutions over a long period of time. As the discussion earlier in the paper suggests, this extensive and continual collaboration is what dental informatics currently does not have. Until now, most dental informaticians have been working alone or in very small research groups, and in relative geographic isolation. Qualified researchers in dental informatics are the exception rather than the rule. For most dental schools and research centers, dental informatics has had either low or no priority and thus has received few resources. It is hardly a surprise that we have not been able to address many of these research challenges with more success.
A second observation is that while dental informatics is an integral and growing part of the biomedical informatics community, informaticians working in fields other than dentistry will rarely provide ready-made solutions for dental problems, especially in applied informatics (Schleyer, 2003a). For example, much progress has been made toward electronic patient records in medicine, especially in larger care settings, such as academic health centers and hospitals. However, these advances have translated into little or no progress for dental practice. On the other hand, results from theoretical informatics research (Schleyer, 2003a) are often much easier to apply across disciplines, especially when analogous problems are identified. For instance, the image-processing algorithms that make up the core of the OralCDX system (Sciubba, 1999) drew on the rich set of imaging methods that were pioneered in other disciplines. Promising advances from biomedical informatics in general should be applied in dentistry when appropriate; however, when they fail to solve the problem, solutions specific to dentistry should be developed.
Last, it is obvious that technology has developed with more speed and in more different directions than could have been foreseen in the early 1990s. These developments make it easier to meet some of the listed research challenges. For instance, before the widespread diffusion of the Internet throughout society, a concept such as the National Health Information Infrastructure (US Department of Health and Human Services, 2003) was truly a dream. Now, with more than 40% of all dental practices being connected to the Internet, that dream has at least a technological platform on which it can be built. However, many issues can be resolved only by the concerted effort of the dental informatics research community, not by relying on the beneficial effects of external trends.
Research challenges: an updated view
It is logical and useful to extend the discussion to research challenges in dental informatics for the future. Sittig et al.(2003) have already articulated a few grand challenges for dental informatics elsewhere in these proceedings. Based on Lipton’s work (1992), we present an updated, global, and comprehensive view of research challenges in dental informatics that encompasses the grand challenges described by Sittig et al. The Fig. shows a map of those research challenges. Due to space constraints in this manuscript, we highlight only a few key research areas and a few common themes connecting them.
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Dental Practice |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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Parallel to this research focus on dental care delivery in the operatory, we have to propel the development of computer-based oral health records forward. Such records must be designed for the local, regional, national, and international context. Several companies provide systems for dental practices that capture and manage a rich set of data about patients, and these systems can serve as useful precursors for computer-based oral health records. In all implementations of computer-based oral health records, research must address issues regarding information architecture, forms of data and information representation, security, privacy, controlled vocabularies, interfaces to other systems, and many other considerations.
Local, regional, national, and international networks for communicating patient information will bring us closer to the vision of comprehensive and longitudinal electronic patient records (Dick and Steen, 1991). This vision requires resolving a whole host of research questions, including but not limited to authentication and authorization, communication, storage and retrieval, and ownership. Concepts such as practice-based research networks can be built on much of the same infrastructure, even if they have a different purpose and are implemented differently. For instance, data from PBRNs will probably have to be merged into centralized databases, while ad hoc patient record queries could be executed in a distributed manner.
Involving patients more in their own care can have a variety of benefits (Agency for Health Care Policy and Research, 1997), such as greater knowledge about treatment options, increased satisfaction with the decision-making process, and improved health outcomes. Some entities, such as the Department of Veterans Affairs, allow their patients to access their health records through the Internet (Veterans Health Administration, 2003). However, in general, the growing area of consumer health informatics has received scant attention in dentistry, and many opportunities remain to be explored formally. Possible research areas include patient access to all or part of their own dental records, improved communication between dentists and patients, health-related educational software, and patient-specific health and wellness information.
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Dental Research |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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Informatics and IT have already contributed substantially to the progress of dental research, ranging from computer programs that assist researchers in the acquisition, storage, management, and retrieval of research information to computer-based analysis tools that permit many research projects to be performed faster and better than ever before. However, in none of these areas has an endpoint been reached. For example, as the scale and scope of dental research change, more attention must be focused on helping increasingly large, multi-disciplinary and distant research teams collaborate using electronic tools. Computer-based tools for dental research must be developed in accordance with state-of-the-art software engineering principles, so that they can evolve and be re-used by as many researchers as possible. As discussed above, knowledge management and dissemination are crucial if we are to enhance the efficiency and efficacy of dental research. Decision support systems for research can help researchers make optimal decisions in research design and experimentation. Policies and guidelines from funding agencies, such as the NIDCR, can ensure that informatics and IT serve dental research in the best possible manner.
In part, this vision also requires a change in our current model of dental research. Top researchers typically maintain, in their heads, a large database of data, information, problem-solving methods, troubleshooting approaches, and creative insights. This knowledge must be made explicit and accessible so that other researchers and software applications can use it. In light of the need to address many research problems using increasingly multidisciplinary approaches, we must ensure that knowledge integration does not become the next bottleneck in the pursuit of research. Researchers, tools, software applications, and databases must be considered part of a system whose performance we strive to optimize. Traditionally, research has benefited significantly from intense competition between and among individuals, research groups, and institutions. However, this may not continue to be the best model. Cooperation, rather than competition, may hold the promise of greater efficiency in addressing important research questions.
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Dental Education |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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Cross-cutting Issues |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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Security, privacy, confidentiality, and data access also cross-cut most research issues. In the last few years, new regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) and other Federal regulations, have significantly strengthened the framework in which health information is managed. While many consider compliance with these regulations a necessary evil, the HIPAA actually facilitates the development of systems such as the National Health Information Infrastructure (US Department of Health and Human Services, 2003) because it provides strict guidelines for security, privacy, and confidentiality. However, regulations such as HIPAA do not answer all research questions related to security and confidentiality, and therefore further research on these issues is needed (Masys and Baker, 1997).
A last cross-cutting issue is evaluation research. Evaluation of innovations in informatics and IT has often taken a backseat to other, more pressing aspects of research and development (Friedman and Wyatt, 1996). However, without formal evaluation it is difficult to know whether an innovation conveys any benefits, and if so, which ones. As health professionals, we would never accept a drug that did not undergo a clinical trial. Yet we do not have the same scruples regarding the computer programs we use in clinical practice, research, and education. Evaluation in informatics is a complex subject (Friedman and Wyatt, 1996), and continual effort at developing new evaluation approaches is needed (Schleyer and Johnson, 2003).
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Dental Informatics: Evolution or Revolution? |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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(1) Create a more focused, worldwide community of dental informaticians.
As a discipline, dental informatics is larger than the numbers cited above indicate. Many researchers engage in dental informatics research, but they would never consider themselves informaticians. They may label themselves engineers, information scientists, computer scientists, computational biologists, human-computer interaction specialists, and cognitive scientists. The challenge is to create a sense of community in all individuals who are researching informatics issues in dentistry, regardless of their position, provenance, or location. The goal should not be to label as many people as possible "dental informaticians", but rather to link the field’s scarce intellectual resources better. In short, we should strive to create a close-knit, active, and global community of researchers pursuing research questions in dental informatics. Options to accomplish this include focused meetings, collaborative research projects, and the establishment of a virtual, worldwide community.
(2) Get more biomedical informaticians interested in dental problems.
Additional resources will be focused on dental research problems if we manage to stimulate the interest of the biomedical informatics community at large, rather than just its dental subset. Meetings that bring together biomedical informaticians and dental researchers are one method, as this conference has demonstrated. Requests for Applications and Program Announcements issued by funding agencies for dental research questions that speak to the expertise of biomedical informaticians are certain to elicit responses. Strengthening working relationships between dental and other biomedical informaticians—for instance, through joint training programs, collaborative research projects, and cross-disciplinary working groups—are a third possibility.
(3) Provide career opportunities and career paths for dental informatics researchers.
This recommendation is realistic only if dental informatics provides and demonstrates tangible and sustainable value to the dental community at large. Dental informatics must make a difference, rather than talk about one. Certain steps will help dental informatics achieve this:
(4) Address grand challenges together as a community.
No single research team, no matter how qualified and talented, will make much progress on even one or two of the grand challenges listed in this and the paper by Sittig et al.(2003). The major dental organizations worldwide must address these issues with energy and a sense of mission, and must provide the leadership and vision to make the grand challenges a priority. Once they do that, it is very likely that the dental informatics community will respond enthusiastically.
(5) Recruit subsequent generations of dental informaticians.
Today’s students in dentistry, computer science, information science, and other fields will be tomorrow’s informaticians. The same is true for dentists in clinical practice who have an interest in dental informatics and would like to make it their career. If those individuals are to be made aware of and excited about this possibility, they must be exposed to the field and its active researchers. The relative dearth of informatics researchers at dental schools presents a special challenge in the development of a bigger "pipeline" of future dental informaticians.
These recommendations are far from complete, but some of them may help dental informatics advance in its evolution as a research discipline.
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Conclusion |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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Acknowledgments |
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The development of this manuscript was supported in part by award 1R13DE014611-01 from the National Institute of Dental and Craniofacial Research/National Library of Medicine.
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Footnotes |
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References |
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TOPAbstractIntroductionHistory and BackgroundResearch ChallengesDental PracticeDental ResearchDental EducationCross-cutting IssuesDental Informatics: Evolution or...ConclusionReferences |
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