ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2026
Quality assurance and improvement in dental oncology.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
12 authors.
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Abstract
Some cancer treatments can irreversibly damage a patient's oral health through complications like post-radiation caries, osteonecrosis, and/or infection. These patients should undergo dental examination before cancer treatment, and dental oncology departments should provide timely and preventive care to minimize delays and prevent adverse outcomes in cancer therapy. While a quality method can be used to systematically monitor success, identify problems, and improve outcomes by collecting and analyzing quality data, to our knowledge, there are no established recommendations for monitoring the quality of care in dental oncology. Therefore, a standardized protocol of Quality Assurance (QA) and Quality Improvement (QI) for dental oncology is proposed. The proposed QA and QI method for dental oncology utilizes the Plan-Do-Study-Act (PDSA) cycle to monitor and implement changes. Clinical and demographic variables are recorded into a database at the initial visit. Data parameters are divided into four categories: Clinic Volume Data represents the total number of clinic visits and referrals; Cancer Demographic Data reports the cancer type and treatment; Clinic Flow Data records dates of referral, consultation, and treatment completion; and Dental Treatment Data documents dental treatments provided to patients. The completion and accuracy of the database are reviewed monthly, and data are extracted biannually and analyzed for further action. Clinic Flow Data identifies delays to care, which are addressed by staff adjustment and care referred to the community. Dental Treatment Data identifies trends and impacts of changes in the treatment paradigm. Clinic Volume and Cancer Demographic Data can suggest modifications to referral triage, allow for department- and institutional-level reporting, and identify areas for research.
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