Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2025
Face Validation of an Artificial Intelligence Driven Tool for Clinical Triaging in Australian Public Oral Healthcare: A Pilot Study.
СтатьяВалидационное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
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.
Nguyen Tan Minh, Caponio Vito Carlo Alberto, Rajappa Ravikumar, Lawrence Daniel, Tawadros Youstina, Jones Bree, Crow Keegan, Cirillo Nicola
Аннотация
OBJECTIVES: The adoption of artificial intelligence (AI) technology holds significant potential to drive innovation for value-based healthcare for Victorian public oral healthcare, Australia. This pilot study compared the clinical triage decision outcome of experienced dentists in prioritizing consumers with urgent dental care at Your Community Health, a community health service in Victoria, Australia, with those generated by the CoTreat AI-driven tool (CoTreat Pty Ltd, Australia).
METHODS: Consecutive sampling of consumers were recruited for the 6-month pilot. Five clinical criteria were established to determine consumers with urgent care: (1) requires urgent extraction causing loss of upper or lower anterior teeth, (2) multiple teeth (≥15% of remaining dentition) with moderate/extensive dental caries, (3) abscessed tooth/teeth, (4) root caries, and (5) missing upper and lower anterior teeth. Face validation was undertaken to compare the agreement between the triage output returned by CoTreat (index test) and 2 experienced dentists (reference standard) in determining urgent care.
RESULTS: A total of 173 consumers were triaged in this pilot study (mean age 61.9 years [SD 18.]). One-third (n = 57) were identified needing urgent care. CoTreat achieved 98.3% agreement with dentist clinical triage outcome (Cohen's k = 0.96), 100% sensitivity, and 97.5% specificity, with positive predictive value of 94.7% and negative predictive value of 100%. The most common triage criteria were missing anterior teeth (60.3%) and abscesses (20.7%).
CONCLUSIONS: CoTreat demonstrated excellent agreement with dentists' clinical triage decisions. AI-driven tools, such as CoTreat, can advance value-based healthcare implementation by identifying consumers with urgent care needs for Victorian public oral healthcare.
METHODS: Consecutive sampling of consumers were recruited for the 6-month pilot. Five clinical criteria were established to determine consumers with urgent care: (1) requires urgent extraction causing loss of upper or lower anterior teeth, (2) multiple teeth (≥15% of remaining dentition) with moderate/extensive dental caries, (3) abscessed tooth/teeth, (4) root caries, and (5) missing upper and lower anterior teeth. Face validation was undertaken to compare the agreement between the triage output returned by CoTreat (index test) and 2 experienced dentists (reference standard) in determining urgent care.
RESULTS: A total of 173 consumers were triaged in this pilot study (mean age 61.9 years [SD 18.]). One-third (n = 57) were identified needing urgent care. CoTreat achieved 98.3% agreement with dentist clinical triage outcome (Cohen's k = 0.96), 100% sensitivity, and 97.5% specificity, with positive predictive value of 94.7% and negative predictive value of 100%. The most common triage criteria were missing anterior teeth (60.3%) and abscesses (20.7%).
CONCLUSIONS: CoTreat demonstrated excellent agreement with dentists' clinical triage decisions. AI-driven tools, such as CoTreat, can advance value-based healthcare implementation by identifying consumers with urgent care needs for Victorian public oral healthcare.