Miguel Humberto Torres-Urquidy

Clinical Computing in General Dentistry

OBJECTIVE Measure the adoption and utilization of, opinions about, and attitudes toward clinical computing among general dentists in the United States. DESIGN Telephone survey of a random sample of 256 general dentists in active practice in the United States. MEASUREMENTS A 39-item telephone interview measuring practice characteristics and information technology infrastructure; clinical information storage; data entry and access; attitudes toward and opinions about clinical computing (features of practice management systems, barriers, advantages, disadvantages, and potential improvements); clinical Internet use; and attitudes toward the National Health Information Infrastructure. RESULTS The authors successfully screened 1,039 of 1,159 randomly sampled U.S. general dentists in active practice (89.6% response rate). Two hundred fifty-six (24.6%) respondents had computers at chairside and thus were eligible for this study. The authors successfully interviewed 102 respondents (39.8%). Clinical information associated with administration and billing, such as appointments and treatment plans, was stored predominantly on the computer; other information, such as the medical history and progress notes, primarily resided on paper. Nineteen respondents, or 1.8% of all general dentists, were completely paperless. Auxiliary personnel, such as dental assistants and hygienists, entered most data. Respondents adopted clinical computing to improve office efficiency and operations, support diagnosis and treatment, and enhance patient communication and perception. Barriers included insufficient operational reliability, program limitations, a steep learning curve, cost, and infection control issues. CONCLUSION Clinical computing is being increasingly adopted in general dentistry. However, future research must address usefulness and ease of use, workflow support, infection control, integration, and implementation issues.

Detection of disease outbreaks by the use of oral manifestations.

Oral manifestations of diseases caused by bioterrorist agents could be a potential data source for biosurveillance. This study had the objectives of determining the oral manifestations of diseases caused by bioterrorist agents, measuring the prevalence of these manifestations in emergency department reports, and constructing and evaluating a detection algorithm based on them. We developed a software application to detect oral manifestations in free text and identified positive reports over three years of data. The normal frequency in reports for oral manifestations related to anthrax (including buccal ulcers-sore throat) was 7.46%. The frequency for tularemia was 6.91%. For botulism and smallpox, the frequencies were 0.55% and 0.23%. We simulated outbreaks for these bioterrorism diseases and evaluated the performance of our system. The detection algorithm performed better for smallpox and botulism than for anthrax and tularemia. We found that oral manifestations can be a valuable tool for biosurveillance.

Designing Clinical Data Presentation in Electronic Dental Records Using Cognitive Task Analysis Methods

Despite the many decades of research on the effective development of clinical systems in medicine, the adoption of health information technology to improve patient care continues to be slow, especially in ambulatory settings. This applies to dentistry as well, a primary care discipline with approximately 137,000 practitioners in the United States. A critical reason for slow adoption is the poor usability of clinical systems, which makes it difficult for providers to navigate through the information and obtain an integrated view of patient data. Cognitive science methods have shown significant promise to meaningfully inform the design, development and assessment of clinical information systems. In most cases, these methods have been applied to evaluate the design of systems after they have been developed. Very few studies, on the other hand, have used cognitive engineering methods to support the design process for a system itself. It is this gap in knowledge how cognitive engineering methods can be optimally applied to inform the system design process that our research seeks to address. This project studied the cognitive processes and in-formation management strategies used by dentists during a typical patient exam and applied the results to inform the design of an electronic dental record interface. The results of this study will contribute to designing clinical systems that improve cognitive support for clinicians during patient care. Such a system has the potential to enhance the quality and safety of patient care, as well as reduce healthcare costs.

HIT Considerations: Informatics and Technology Needs and Considerations

In this chapter, we explore and consider many of the technical, data and knowledge issues that impact electronic health records. These issues include healthcare standards and semantic interoperability, security of applications and data, privacy of information, the ability to identify uniquely a participant across all healthcare domains, usability and context based information retrieval, and clinical decision support. These generally applicable informatics issues are then examined with a specific focus on the overall goal of integrating medical and dental health information. Thus, we also examine standards specific to dentistry, the data needs of dentists, and clinical dental decision support efforts.

Broader Considerations of Medical and Dental Data Integration

Dental health insurance coverage in the United States is either nonexistent (Medicare and the uninsured), spotty (Medicaid) and limited (most employer-based private benefit plans). Perhaps as a result, dental health in the United States is not good. What public policy makers may not appreciate is that this may well be impacting medical care costs in a way that improved dental benefits would produce a substantial return to investment in expanded dental insurance coverage.

Evaluating the effectiveness of modeling principles for data models.

We evaluated the effectiveness of modeling principles intended to harmonize the information representation between terminology-ontology models and information models. Our study utilized dental clinical statements and sample dental record questions. We asked experts to define the equivalency (mapping) of these elements and measured their agreement. We modified the data elements and asked the experts to conduct subsequent mappings. We measured the agreement and compared the levels of agreement before and after changes, expecting that agreement would increase. The level of agreement (Kappa) before modeling was 0.3 to 0.4 and after was 0.5 (p<0.05). The difference was small but statistically significant. Our results suggest that the modeling principles improve information representation since agreement increased.