Background: Factor VIII (FVIII) inhibitor diagnosis and surveillance in Indonesia are challenging owing to geographic conditions and the lack of laboratory facilities nationwide for inhibitor assays. This study aimed to determine the prevalence of FVIII inhibitors in children diagnosed with hemophilia A (HA) in Indonesia. Methods: A cross-sectional study was conducted in 12 hospitals in eight provinces of Indonesia between 2020 and 2021. Factor VIII inhibitor screening was performed in a central hemostasis laboratory for all children with HA (≤18 yr) who had received a minimum of 10 exposure days to clotting factor concentrates. The FVIII inhibitor titer was determined using the Bethesda assay. Results: Children (388) were enrolled in this study, including 219 (56.4%), 131 (33.8%), and 38 (9.4%) with severe, moderate, and mild HA, respectively. The prevalence of children who developed FVIII inhibitors was 37 out of 388 (9.6%). Factor VIII inhibitors were found in 25/219 (11.4%) severe, 11/131 (8.3%) moderate, and 1/38 (2.6%) children with mild HA. Thirteen children had low-titer inhibitors and 24 had high-titer inhibitors, with a median of 9.44 (1.48‒412.0) Bethesda Units. Among 13 children with low-titer inhibitors, eight underwent a confirmation test, of which five tested negative and were classified as transient. A significant difference in annual joint bleeding rate was found between patients with low and high inhibitor titers and those without inhibitors (P ＜0.001). Conclusion Factor VIII inhibitor prevalence in Indonesia was relatively low. However, the risk factors that may contribute to FVIII inhibitor development among Indonesian patients require further study.

Objectives: The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods: An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results: A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.

Objectives: The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods: An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results: A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.

Objectives: The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods: An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results: A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.

Objectives: The use of technology has rapidly increased in the past century. Artificial intelligence (AI) and information technology (IT) are now applied in healthcare and medical education. The purpose of this study was to assess the readiness of Indonesian teaching staff and pediatric residents for AI integration into the curriculum. Methods: An anonymous online survey was distributed among teaching staff and pediatric residents from 15 national universities. The questionnaire consisted of two sections: demographic information and questions regarding the use of IT and AI in child health education. Responses were collected using a 5-point Likert scale: strongly disagree, disagree, neutral, agree, and highly agree. Results: A total of 728 pediatric residents and 196 teaching staff from 15 national universities participated in the survey. Over half of the respondents were familiar with the terms IT and AI. The majority agreed that IT and AI have simplified the process of learning theories and skills. All participants were in favor of sharing data to facilitate the development of AI and expressed readiness to incorporate IT and AI into their teaching tools. Conclusions The findings of our study indicate that pediatric residents and teaching staff are ready to implement AI in medical education.