. Hamideh Ehtesham; . Reza Safdari; . Arash Mansourian; . Shahram Tahmasebian; . Niloofar Mohammadzadeh; . Sara Pourshahidi
Volume 10, Issue 9 , September 2020, , Pages 1-10
Abstract
BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patientdata elements need to be processed in their diagnosis. One of the biggest and most basic ...
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BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patientdata elements need to be processed in their diagnosis. One of the biggest and most basic challengesis the analysis of this huge amount of complex patient data in an increasing number of complicatedclinical decisions. This study seeks to identify the necessary steps for collecting and managementof these data elements through establishing a consensus‑based framework.METHODS: This research was conducted as a descriptive, cross‑sectional study from April 2016 toJanuary 2017, which has been performed in several steps: literature review, developing the initialdraft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinionsand creating version v.i, performing Delphi rounds, and creating the final framework.RESULTS: The administrative data category with 17 and the historical data category with 23data elements were utilized in recording data elements in the diagnosis of all of the different oraldiseases. In the paraclinical indicator and clinical indicator categories, the necessary data elementswere considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket’sOral Medicine: ulcerative, vesicular, and bullous lesions; red and white lesions of the oral mucosa;pigmented lesions of the oral mucosa; benign lesions of the oral cavity and the jaws; oral andoropharyngeal cancer; and salivary gland diseases.CONCLUSIONS: The study achieved a consensus‑based framework for the essential data elementin the differential diagnosis of oral medicine using a comprehensive search with rich keywords indatabases and reference texts, providing an environment for discussion and exchange of ideasamong experts and the careful use of the Delphi decision technique.