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The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2026

Visualizing the Timeline of Care: Development of a Graphical Approach to Better Understanding Complex, Longitudinal Surgical Care of Cleft Lip/Palate.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Lin Elaine, Yi Victoria N, Dunworth Kristina, Cox Meredith, Patel Kamlesh, Allori Alexander C

Аннотация

ObjectiveDevelop and apply novel data visualization techniques to analyze longitudinal cleft surgical care and to identify patterns in treatment timing and procedural burden across 2 cleft teams.DesignRetrospective cohort study of operative data using novel data visualization methods.SettingTwo cleft teams in the United States.Patients and ParticipantsPatients with cleft lip and/or palate with operative clinical encounters between 2018 and 2023. Team A had 228 patients and team B had 355.InterventionsVisualization of primary cleft-related surgical procedures which were cleft lip and palate repair, fistula repair, alveolar bone grafting, correction of velopharyngeal insufficiency, orthognathic surgery, and rhinoplasty.Main Outcome Measure(s)Visual interpretation of surgical timing, frequency, volume, and distribution using novel timelines, stacked-bar charts, and ridgeplots.ResultsTimeline visualizations clarified procedural sequencing and highlighted variation in treatment timing by team and phenotype but were too dense for interpretation for a large volume of patients. Stacked-bar charts illustrated procedural volume but lacked temporal insight. Ridgeplots demonstrated both timing of procedures and aggregate team volume.ConclusionsIndividual patient timelines can effectively depict deviation from "ideal" care protocols, but aggregate data may be best depicted by a ridgeplot. These tools may support quality improvement initiatives by transforming raw data into actionable insights and enhancing multidisciplinary team reflection.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты