Factors influencing choice of medical vs. surgical treatment of pediatric appendicitis

PurposeTo examine what proportion of caregivers, if given a choice, would choose medical versus surgical treatment of appendicitis and what factors would be important in their decision.MethodsA survey was devised and given to the caregivers of children presenting to the pediatrician for a routine visit in community and academic pediatric clinics. The survey presented a summary of outcomes after medical (non-operative) and surgical treatment of uncomplicated appendicitis. Participants were then asked to choose medical versus surgical treatment if their child were to develop appendicitis. They were also asked to rate the importance of certain factors in their decision ? 1 being “not important” and 5 being “very important”.ResultsFour hundred surveys were distributed with an 86.2% (345/400) response rate. Six percent (21/342) of respondents reported a history of appendicitis and 49.4% (168/340) reported having known someone who had appendicitis. The majority of respondents, 85.3% (284/333), were mothers. A minority of respondents, 41.7% (95% CI: 36.7, 47.0), chose medical treatment over surgery for appendicitis. There was no statistical difference in the proportion of mothers (41.6%) versus fathers who chose medical treatment (41.3%). Caregivers who chose medical treatment were more likely to rate time in hospital (p = .008) and time out of school (p = 05) as important in decision making when compared with those who chose surgery. Those who chose surgical treatment were more likely to rate risk of recurrent appendicitis (p < .001) as important to decision making. In the multivariate analysis, those who rated time in hospital as very important had more than twice the odds of choosing medical therapy (OR 2.20, p = 0.02) when compared with those who rated it as less important. Not knowing someone who has had appendicitis was significantly associated with choosing medical therapy when compared with those who do know someone who has had appendicitis, OR 2.3, p = .002. Rating pain as very important was also significantly associated with choosing medical therapy, when compared to those rating pain 1–3, OR 3.38, p = .03.ConclusionsIn this survey of caregivers of children presenting for routine care, 41.7% would choose medical, or non-operative, therapy for their children with acute appendicitis. The risk of recurrence, time in hospital, and time out of school, pain, and knowing someone who has had appendicitis were all important factors that families may consider when making a decision. These data may be useful for surgeons counseling patients on which treatment to pursue.     

Registries,Databases and Repositories for Developing Artificial Intelligence in Cancer Care

Modern artificial intelligence techniques have solved some previously intractable problems and produced impressive results in selected medical domains. One of their drawbacks is that they often need very large amounts of data. Pre-existing datasets in the form of national cancer registries, image/genetic depositories and clinical datasets already exist and have been used for research. In theory, the combination of healthcare Big Data with modern, data-hungry artificial intelligence techniques should offer significant opportunities for artificial intelligence development, but this has not yet happened. Here we discuss some of the structural reasons for this, barriers preventing artificial intelligence from making full use of existing datasets, and make suggestions as to enable progress. To do this, we use the framework of the 6Vs of Big Data and the FAIR criteria for data sharing and availability (Findability, Accessibility, Interoperability, and Reuse). We share our experience in navigating these barriers through The Brain Tumour Data Accelerator, a Brain Tumour Charity-supported initiative to integrate fragmented patient data into an enriched dataset. We conclude with some comments as to the limits of such approaches.     

“人工智能+X”背景下医学信息管理专业研究生培养模式

阐述当前“人工智能+X”背景下市场对医学信息管理专业人才能力的需求，分析医学信息管理专业人才培养现状，提出从重塑学科人才培养目标、优化课程内容与课程设置、建设“双师型”导师队伍、搭建多方协同共建共享在线平台及设立“政用产学研”联合培养基地等方面探索医学信息管理专业研究生培养模式，以期培养适应人工智能时代发展，具备学科优势特色的高层次、高水平、高质量的复合型、应用型、创新型人才。