Moore G W, Berman J J
Department of Pathology, Baltimore Veterans Administration Medical Center, MD 21201.
Am J Clin Pathol. 1994 Mar;101(3):253-6. doi: 10.1093/ajcp/101.3.253.
Many pathology departments rely on the accuracy of computer-generated diagnostic coding for surgical specimens. At present, there are no published guidelines to assure the quality of coding devices. To assess the performance of systemized nomenclature of medicine (SNOMED) coding software, manual coding was compared with automated coding in 9353 consecutive surgical pathology reports at the Baltimore Veterans Affairs Medical Center. Manual SNOMED coding produced 13,454 morphologic codes comprising 519 distinct codes; 209 were unique codes (assigned to only one report apiece). Automated coding obtained 23,744 morphologic codes comprising 498 distinct codes, of which 129 were unique codes. Only 44 (.5%) instances were found in which automated coding missed key diagnoses on surgical case reports. Thus, automated coding compared favorably with manual coding. To achieve the maximum performance, departments should monitor the output from automatic coders. Modifications in reporting style, code dictionaries, and coding algorithms can lead to improved coding performance.
许多病理科依赖计算机生成的手术标本诊断编码的准确性。目前，尚无已发表的指南来确保编码设备的质量。为评估医学系统命名法（SNOMED）编码软件的性能，在巴尔的摩退伍军人事务医疗中心对9353份连续的手术病理报告中的手动编码与自动编码进行了比较。手动SNOMED编码产生了13454个形态学编码，包括519个不同的编码；其中209个是唯一编码（每份报告仅分配一个）。自动编码获得了23744个形态学编码，包括498个不同的编码，其中129个是唯一编码。在手术病例报告中，仅发现44例（0.5%）自动编码遗漏关键诊断的情况。因此，自动编码与手动编码相比表现良好。为实现最佳性能，各科室应监测自动编码的输出。报告风格、编码词典和编码算法的修改可提高编码性能。
