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*

Shunt infection remains one of the most frequent and disabling neurosurgical complications. We reviewed the medical records of 40 patients who between 1989 and 1997 underwent CSF shunt surgery involving a total of 48 procedures. Infection occured in six of the 40 patients and secondary postoperative infection in two; i.e. in eight of 48 procedures(16.7%); the microorganisms involved were not always isolated, though in all cases, clinical symptoms were detected. Most episodes occured within 6 months of the last shunt operation and patients under one year old are greater risk of infection than those who are older. To prevent such infection careful preoperative surgical planning is mandatory.
Humans ; Hydrocephalus* ; Medical Records

PURPOSE: The purpose of this study was to examine the effects on knowledge and performance in clinical nurses who participated in education on nursing recording focusing on the legal aspects. METHOD: The participants were working in medical departments in one hospital. There were 32 nurses in the experimental group and 25 in the control group. Pre-test was conducted on the two groups before education, and, in order to examine the effects of education, a post-test was conducted after three weeks. For the experimental group, the education on nursing recording focusing on legal aspects was provided as a lecture-led one-to-one training. RESULTS: Significant differences were found between the experimental and control groups in knowledge (F=15.728, p<.001), and performance (F=42.454, p<.001). CONCLUSIONS: The results of this study indicate that education on nurse recording enhances the knowledge and performance of the nurses. Thus education on nurse recording focusing on legal aspects should be required in the area of nursing science.
Jurisprudence ; Nursing 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*

No abstract available.
Electronic Health Records* ; Jurisprudence*

No abstract available.
Electronic Health Records*