# Diagnostic Failures in Dentistry > **NIH AHRQ R01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2021 · $400,000 ## Abstract Project Summary/Abstract Despite growing recognition that diagnostic failures are the “new frontier” for patient safety research, there has been no study to systematically examine diagnostic failures (delayed, wrong or missed diagnoses) in dentistry. The primary goal of our proposal is to close this knowledge gap by systematically evaluating dental diagnostic failures (DDFs) associated with periodontal diseases with a goal of moving the profession towards diagnostic excellence. Periodontal (gum) diseases affect 46% of US adults and may often lead to pain, tooth loss, and/or poor quality of life when not properly managed. This work is significant because it is the first attempt to systematically evaluate diagnostic performance in dentistry. It is innovative because it utilizes a new methodology for mining EHR data to identify diagnostic errors, and examines the association between diagnostic errors and clinical/health service outcomes. The approach is grounded in our extensive preliminary work. The investigators are experienced researchers who have pioneered patient safety research in dentistry and laid the foundation for a diagnostic-centered profession through developing and disseminating the dental diagnostic terminology SNODDS that enables dentists to accurately document patients' diagnoses within the EHR in a standardized manner. Our study will be conducted at two academic institutions, which will provide a robust learning environment. In Aim 1, we determine the incidence of dental diagnostic failures (DDFs) associated with periodontal diseases and conditions. This Aim seeks to assess the concordance between clinician-given diagnoses and established diagnostic criteria from the American Academy of Periodontology (AAP) in order to determine the baseline incidence of DDFs associated with periodontal diseases. Specifically, we will deploy automated query scripts to extract critical data elements from the EHR that will be used to generate an EHR-based diagnosis for comparison with the clinician-given diagnosis. All discordant cases will be reviewed independently by trained site clinicians and collectively by the expert panel to confirm the presence or absence of a DDF. In Aim 2 we evaluate clinical and treatment patterns and clinical outcomes following DDFs. In this Aim, we will examine the patterns of treatment received by patients following their periodontal diagnoses and their periodontal health outcomes. We hypothesize that patients with inaccurate diagnoses (DDFs) will be more likely to receive inappropriate treatment (over- or under-treatment) when compared against recommended treatment guidelines. They will also have poorer clinical outcomes (e.g. progression of periodontal disease, tooth loss) compared to those with accurate diagnoses (non-DDFs). We expect that our research will provide the dental profession with a fundamental understanding of DDFs related to periodontal diseases and conditions. It will also provide a solid roadmap fr... ## Key facts - **NIH application ID:** 10365795 - **Project number:** 1R01HS027938-01A1 - **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON - **Principal Investigator:** MUHAMMAD WALJI - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** AHRQ - **Fiscal year:** 2021 - **Award amount:** $400,000 - **Award type:** 1 - **Project period:** 2021-09-30 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10365795 ## Citation > US National Institutes of Health, RePORTER application 10365795, Diagnostic Failures in Dentistry (1R01HS027938-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10365795. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*