Validation for Accuracy of Cancer Diagnosis in Electronic Medical Records Using a Text Mining Method.
To validate the accuracy of data in electronic medical record, we compared cancer diagnosis and key words in pathologic reports of cancer patients in a tertiary hospital, using text mining method. We investigated in fourteen kinds of cancers that had highest incidence rates in Korea. Approximately two-third (71.0%) of total patients had right match in cancer diagnosis with pathologic report. The ratio of concurrence was the highest (86.3%) in thyroid cancer patients, however, the ratio was the lowest (49.9%) in liver cancer patients. To prevent the errors in data input, a systematic alarm and feedback to clinicians should be required.
Department of Biomedical Informatics, Asan Medical Center.
Yura
Y
Lee
Department of Biomedical Informatics, Asan Medical Center.
Soo-Yong
SY
Shin
Department of Biomedical Informatics, Asan Medical Center.
Sung-Min
SM
Ahn
Department of Biomedical Informatics, Asan Medical Center.
Jae-Ho
JH
Lee
Department of Biomedical Informatics, Asan Medical Center.
Woo-Sung
WS
Kim
D000068598:Data Accuracy; D057225:Data Mining / Q000379:methods*; D003951:Diagnostic Errors / Q000517:prevention & control / Q000706:statistics & numerical data*; D004282:Documentation / Q000379:methods; D057286:Electronic Health Records / Q000145:classification* / Q000706:statistics & numerical data*; D006801:Humans; D009323:Natural Language Processing; D009369:Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D015995:Prevalence; D015203:Reproducibility of Results; D056910:Republic of Korea / Q000453:epidemiology; D012680:Sensitivity and Specificity