血液病理学
医学
皮肤病理学
课程
医学教育
住院医师培训
中国
临床病理学
病理
心理学
继续教育
教育学
生物化学
化学
细胞遗传学
政治学
法学
染色体
基因
作者
Li Niu,Fulong Yu,Bei Qi,Sushma Hossur,Sufang Tian
出处
期刊:Archives of Pathology & Laboratory Medicine
[Archives of Pathology and Laboratory Medicine]
日期:2022-05-01
卷期号:147 (5): 604-610
标识
DOI:10.5858/arpa.2021-0122-ep
摘要
The pathology residency program began in China in 2014. There has been no competency assessment on training programs in the Hubei province of China.To evaluate the current residency training curriculum and resident performance in Hubei Province.A 37-question online questionnaire was designed to cover general demographic information, diagnostic competency, expectations of ideal caseload for gross and preview, teaching patterns, examinations, research activities, weak points, and other topics in pathology practice.A total of 166 participants, including 62 postgraduate year (PGY) 2, 49 PGY3, and 55 new practicing pathologists, responded to the survey. PGY3 residents were found to be more competent than PGY2 in diagnostic competency. Forty-five of 55 new practicing pathologists (81.8%) reported that they could sign out cases independently, whereas 10 of 55 (18.2%) were found to still need transitional time for learning before working independently. Some residents could sign out cytopathology cases and gained knowledge in immunohistochemistry and histochemical staining, while some residents did not receive adequate training in molecular pathology. The ideal caseloads for gross and preview during residency were greater than 5000 and 7000, respectively. Nonneoplastic diseases, neuropathology, dermatopathology, hematopathology, and soft tissue pathology were considered difficult subspecialties in pathology practice.While residents trained in Hubei Province have met the basic requirements for qualified pathologists, more efforts need to be made in many areas, such as a well-structured training curriculum and better-designed proficiency examinations. The findings of this study are of great importance to prioritizing training in the future.
科研通智能强力驱动
Strongly Powered by AbleSci AI