No abstract available.
Medical Records

OBJECTIVES: Clinical documents (CDs) have evolved from traditional paper documents containing narrative text information into the electronic record sheets composed of itemized records, where each record is expressed as an item with a specific value. We defined medical record (MR) items to be information entities with a specific value. These entities were then used to compile form-based clinical documents as part of an electronic health record system (EHR-s). METHODS: We took a reusable bottom-up developmental approach for the MR items, which provided three things: efficient incorporation of the local needs and requirements of the medical professionals from various departments in the hospital, comprehensive inclusion of the essential concepts of the basic elements required in clinical documents, and the provision of a structured means for meaningful data entry and retrieval. This paper delineates our experiences in developing and managing medical records at a large tertiary university hospital in Korea. RESULTS: We collected 63,232 MR items from paper records scanned into 962 CDs. The MR item database was constructed using 13,287 MR items after removing redundant items. During the first year of service users requested changes to be made to 235 (1.8%) attributes of the MR items and also requested the additional 9,572 new MR items. In the second year, the attributes of 70 (0.5%) of the existing MR items were changed and 3,704 new items were added. The number of registered MR items increased by 72.0% in the first year and 27.9% in the second year. CONCLUSIONS: The MR item concept provides an easier and more structured means of data entry within an EHR-s. By using these MR items, various kinds of clinical documents can be easily constructed and allows for medical information to be reused and retrieved as data. The success of the use of MR items in a large tertiary university hospital system provides evidence that verifies our approach as being an efficient means of user-oriented and structured data entry, enabling the easy reuse of medical records.
Electronic Health Records ; Electronics ; Electrons ; Medical Records

Electronic Health Records ; Humans ; Medical Records ; Odontodysplasia

To realize the benefits of electronic health records, electronic health record information needs to be shared seamlessly and meaningfully. Clinical terminology systems, one of the current semantic interoperability solutions, were reviewed in this article. Definition, types, brief history, and examples of clinical terminologieswere introduced along with phases of clinical terminology use and issues on clinical terminology use in electronic health records. Other attempts to standardize the capture, representation and communication of clinical data were also discussed briefly with future needs.
Electronic Health Records ; Semantics*

No abstract available.
Humans ; Medical Records

No abstract available.
Electronic Health Records* ; Jurisprudence*

No abstract available.
Electronic Health Records*

Whitnall's ligament plays an important role as a check ligament of the levator muscle and indicates a definite landmark during the procedure of external levator resection. Whitnall's ligament was variable in the level of the ligament. the tightness and appearance etc. The medical records of 193 patients(263 eyes) with ptosis who had undergone levator resection were reviewed from July, 1987 through October, 1994 at Yeungnam University Hospital. The structure of Whitnall's ligament was studied by measurement of the level, gross appearance of the ligament and the tightness. The level of the ligament was the length from the insertion of the levator aponeurosis to Whitnall's ligament. The most common level(88.6%) of the ligament was between 18 mm and 26 mm(range, from 9 mm to 33 mm). Whitnall's ligament levels in mild ptosis with good levator function were higher than in those of severe ptosis with poor levator function. Whitnall's ligament showed gradually higher in level as patients became older. Weak Whitnall's ligament was observed in 21 eyes and more common in mild ptosis.
Humans ; Ligaments* ; Medical Records

No abstract available.
Health Records, Personal ; Humans

Speech recognition as an input tool for electronic medical record enables efficient data entry at the point of care. We evaluated the speech recognition accuracy of IBM ViaVoiceTM for doctor-patient dialogues and for pronounced medical vocabularies. The recognition accuracy for doctor-patient dialogues was 95.4%, while that for pronounced medical vocabularies was 55.1%. In order to put speech-based electronic medical record to practical use, mis-recognized vocabulary must be significantly corrected. This paper describes a correction system for mis-recognized medical vocabulary for speech recognition-enabled electronic medical record. The correction system is composed of an extraction and a correction steps. In the extraction step, hamming distance between a parsed substring and the nearest medical vocabulary in the vocabulary database greater than 50% of the length of the substring was used to determine if the substring is a possible mis-recognized medical vocabulary. In the correction step, possible mis-recognized medical vocabularies are scored such that when both the code and location of a syllable is the same with those of a medical vocabulary found in our database, +5 is given and when the code is the same but the location is not, +1 is given. The medical vocabulary with the highest score in the database is used as the correction for the mis-recognized one. When 33 patient-doctor dialogues with 33 medical vocabularies were tested for three times by six testees (i.e., 33 x 6 x 3 = 594 sentences), 94% of the mis-recognized words were correctly detected and repaired. Poor recognition performance for hard medical vocabularies can be markedly improved by the mis-recognized medical vocabulary correction system.
Electronic Health Records* ; Vocabulary*