Baker J D, Wallace C T, Cooke J E, Alpert C C, Ackerly J A
South Med J. 1987 Aug;80(8):1031-5. doi: 10.1097/00007611-198708000-00020.
The large numbers of medical graduates seeking residency training in anesthesiology have created a logistical problem for many programs. This difficulty and the recurrent phenomenon of the misplaced physician have prompted a search for better selection criteria and more efficient evaluation systems. The literature does not provide a concise description of the ideal resident candidate, but it does contain several approaches taken by a few individual teaching centers to improve applicant review procedures. Computer-assisted resident candidate selection (CARCS) is a three-phase system of preinterview screening, interview evaluation, and final ranking. Based on faculty criteria, the entire process uses data management technology that provides automatic calculation of selection parameters, sorting on any data field or combination thereof, and maintenance of a concise information profile for each candidate. CARCS allows equitable consideration of all who apply, with significant cost savings to both program and applicants. This paper reviews traditional methods of selecting anesthesiology residents, describes the CARCS system, and previews the future of resident candidate selection.
大量寻求麻醉学住院医师培训的医学毕业生给许多项目带来了后勤保障方面的问题。这一困难以及医生定位不当的反复出现促使人们寻求更好的选拔标准和更高效的评估体系。文献中并未对理想的住院医师候选人给出简洁的描述，但确实包含了一些个别教学中心为改进申请人审核程序所采取的方法。计算机辅助住院医师候选人选拔（CARCS）是一个包括面试前筛选、面试评估和最终排名三个阶段的系统。基于教员标准，整个过程使用数据管理技术，该技术可自动计算选拔参数，按任何数据字段或其组合进行排序，并为每位候选人维护一份简洁的信息档案。CARCS允许公平地考虑所有申请者，同时为项目和申请人节省大量成本。本文回顾了选拔麻醉学住院医师的传统方法，描述了CARCS系统，并展望了住院医师候选人选拔的未来。
