Document Type : Original Article
Authors
- . Hamideh Ehtesham 1
- . Reza Safdari 2
- . Arash Mansourian 3
- . Shahram Tahmasebian 4
- . Niloofar Mohammadzadeh 2
- . Sara Pourshahidi 5
1 Department of Health Information Technology, Ferdows School of Paramedical and Health, Birjand University of Medical Sciences, Birjand, Iran, Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
3 Department of Oral Medicine, Dental Research Center, Faculty of Dentistry, Tehran University of Medical Sciences, Tehran, Iran
4 Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran
5 Department of Oral and Maxillofacial Medicine, Tehran University of Medical Sciences, Tehran, Iran
Abstract
BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patient
data elements need to be processed in their diagnosis. One of the biggest and most basic challenges
is the analysis of this huge amount of complex patient data in an increasing number of complicated
clinical decisions. This study seeks to identify the necessary steps for collecting and management
of these data elements through establishing a consensus‑based framework.
METHODS: This research was conducted as a descriptive, cross‑sectional study from April 2016 to
January 2017, which has been performed in several steps: literature review, developing the initial
draft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinions
and 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 23
data elements were utilized in recording data elements in the diagnosis of all of the different oral
diseases. In the paraclinical indicator and clinical indicator categories, the necessary data elements
were considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket’s
Oral 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 and
oropharyngeal cancer; and salivary gland diseases.
CONCLUSIONS: The study achieved a consensus‑based framework for the essential data element
in the differential diagnosis of oral medicine using a comprehensive search with rich keywords in
databases and reference texts, providing an environment for discussion and exchange of ideas
among experts and the careful use of the Delphi decision technique.
Keywords
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