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Research Studies is a compilation of published research articles funded by 大象视频or authored by 大象视频researchers.

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1 to 3 of 3 Research Studies Displayed
Tokede B, Yansane A, Brandon R
The burden of diagnostic error in dentistry: a study on periodontal disease misclassification.
This study provided epidemiological estimates on the rate of diagnostic misclassification in dentistry based on electronic health record-based data. The results revealed that approximately one third of periodontal cases are misclassified. The authors concluded their findings highlighted the potential role of technology in aiding diagnostic decision-making at the point of care.
AHRQ-funded; HS027938.
Citation: Tokede B, Yansane A, Brandon R . The burden of diagnostic error in dentistry: a study on periodontal disease misclassification. J Dent 2024 Sep; 148:105221. doi: 10.1016/j.jdent.2024.105221..
Keywords: Diagnostic Safety and Quality, Dental and Oral Health, Medical Errors, Adverse Events, Patient Safety, Electronic Health Records (EHRs), Health Information Technology (HIT), Clinical Decision Support (CDS)
Tokede B, Brandon R, Lee CT
Development and validation of a rule-based algorithm to identify periodontal diagnosis using structured electronic health record data.
This article describes the development and validation of an automated electronic health record (EHR) based algorithm to suggest a periodontal diagnosis. It was based on materials from the 2017 World Workshop on the Classification of Periodontal Diseases and Conditions. Findings suggested that a rule-based algorithm using EHR data can be implemented with moderate accuracy in support of chairside clinical diagnostic decision making, and may be particularly useful for inexperienced clinicians. The authors noted that grey-zone cases where clinical judgement will be required still exist and that future applications of similar algorithms will depend upon the quality of EHR data.
AHRQ-funded; HS027938.
Citation: Tokede B, Brandon R, Lee CT . Development and validation of a rule-based algorithm to identify periodontal diagnosis using structured electronic health record data. J Clin Periodontol 2024 May; 51(5):547-57. doi: 10.1111/jcpe.13938..
Keywords: Dental and Oral Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
Kalenderian E, Bangar S, Yansane A
Identifying contributing factors associated with dental adverse events through a pragmatic electronic health record-based root cause analysis.
This study鈥檚 objective was to analyze harmful dental adverse events (AEs) to assess potential contributing factors. Harmful AEs were defined as those that resulted in temporary moderate to severe harm, required hospitalization, or resulted in permanent moderate to severe harm. The authors classified potential contributing factors according to (1) who was involved (person), (2) what were they doing (tasks), (3) what tools/technologies were they using (tools/technologies), (4) where did the event take place (environment), (5) what organizational conditions contributed to the event? (organization), (6) patient (including parents), and (7) professional-professional collaboration. A second review was conducted by a blinded panel of dental experts to confirm the presence of an AE. A total of 59 cases at 2 dental institutions had 1 or more harmful AEs. The most common harmful AE was pain (27.1%) followed by nerve injury (16.9%), hard tissue injury (15.2%), and soft tissue injury (15.2%). The most common contribution factor was the care provider (training, supervision, and fatigue at 31.5%) followed by patient ((noncompliance, unsafe practices at home, low health literacy, 17.1%), and professional-professional collaboration (15.3%).
AHRQ-funded; HS027268.
Citation: Kalenderian E, Bangar S, Yansane A . Identifying contributing factors associated with dental adverse events through a pragmatic electronic health record-based root cause analysis. J Patient Saf 2023 Aug 1; 19(5):305-12. doi: 10.1097/pts.0000000000001122..
Keywords: Dental and Oral Health, Adverse Events, Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Patient Safety

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