Automated Misspelling Detection and Correction in Clinical Free-Text Records

Correct record is important in all fields especially in the medical field. For correct medication, safety of patient and correct documentation accurate medical records are important. There is possibility that medical record can contain some misspelled words that can lead towards the wrong interpretation and wrong treatment of patients. So, it is necessary that the medical record must be correct for proper treatment and care of patients. Part of speech tagging is a mechanism that reads the text in documents and separates the different part of speech. Regular expression is a mechanism that is used to match the specific pattern of words in documents. A Methodology/spellchecker is proposed for automated misspelling detection and correction in medical free-text records for correction of misspelled terms. Proposed methodology is based on part of speech tagging and regular expression and is applied on all types of medical documents such as allergy entries, free-text medication order and clinical notes. Dictionary lookup is used for detection of misspelled words. Suffix and prefix based suggestion list is used for misspelled correction. Incorrect spellings from different medical documents are detected and corrected. A significant percentage of misspelling detection and correction is achieved.