McBride Simon J, Lawley Michael J, Leroux Hugo, Gibson Simon
The Australia E-Health Research Centre, Brisbane, CSIRO ICT Centre, Australia.
Stud Health Technol Inform. 2012;178:144-9.
A large scale, long term clinical study faced significant quality issues with its medications use data which had been collected from participants using paper forms and manually entered into a data capture system. A method was developed that automatically mapped 72.2% of the unique medication names collected for the study to the AMT and SNOMED CT-AU using Ontoserver, a terminology server for clinical ontologies. These initial results are promising and, with further improvements to the algorithms and evaluation, are expected to greatly improve the analysis of medication data gathered from the study.
一项大规模、长期的临床研究在其用药数据方面面临重大质量问题，这些数据是通过纸质表格从参与者那里收集并手动录入数据采集系统的。开发了一种方法，该方法使用临床本体术语服务器Ontoserver，将研究收集的72.2%的独特药物名称自动映射到AMT和SNOMED CT-AU。这些初步结果很有前景，随着算法和评估的进一步改进，有望极大地改善从该研究中收集的用药数据分析。
