Use of a hospital practice management system to provide initial data for a pediatric immunization registry.
(65/3027)
An ongoing challenge in the creation of clinical information systems is the capture of structured clinical information from health care providers while avoiding duplicate data recording. Because immunizations are reimbursable medical procedures, practice management systems that already capture such procedures may be used as a source of clinical data for information systems. We instituted a method for capturing such data on one campus of a multi-institution pediatric immunization registry. We measured the effectiveness of this capture by comparing it to manual audits of selected paper charts over 26 months. Of the immunizations documented by chart audit, 39.69% were captured by the practice management system. Of those not captured, we estimate that a substantial portion were immunizations administered elsewhere and as a result not submitted as a claim through the practice management system. In turn, this was affected by a rate of patient disengagement from primary care of 49%. We discuss the issues associated with using claims data to capture clinical information in the setting of an immunization registry and review possible explanations for this data capture rate. (+info)
Identifying patient subgroups with simple Bayes'.
(66/3027)
Medical records can form the basis of retrospective studies, be used to evaluate hospital practices and guidelines, and provide examples for teaching medicine. Each of these tasks presumes the ability to accurately identify patient subgroups. We describe a method for selecting patient subgroups based on the text of their medical records and demonstrate its effectiveness. We also describe a modification of the basic system that does not assume the existence of a preclassified training set, and illustrate its effectiveness in one retrieval task. (+info)
A technique for semantic classification of unknown words using UMLS resources.
(67/3027)
Natural Language Processing (NLP) is a tool for transforming natural text into codable form. Success of NLP systems is contingent on a well constructed semantic lexicon. However, creation and maintenance of these lexicons is difficult, costly and time consuming. The UMLS contains semantic and syntactic information of medical terms, which may be used to automate some of this task. Using UMLS resources we have observed that it is possible to define one semantic type by its syntactic combinations with other types in a corpus of discharge summaries. These patterns of combination can then be used to classify words which are not in the lexicon. The technique was applied to a corpus for a single semantic type and generated a list of 875 words which matched the classification criteria for that type. The words were ranked by number of patterns matched and the top 95 words were correctly typed with 80% accuracy. (+info)
Creating and indexing teaching files from free-text patient reports.
(68/3027)
Teaching files based on real patient data can enhance the education of students, staff and other colleagues. Although information retrieval system can index free-text documents using keywords, these systems do not work well where content bearing terms (e.g., anatomy descriptions) frequently appears. This paper describes a system that uses multi-word indexing terms to provide access to free-text patient reports. The utilization of multi-word indexing allows better modeling of the content of medical reports, thus improving retrieval performance. The method used to select indexing terms as well as early evaluation of retrieval performance is discussed. (+info)
Streamlining semantic interpretation for medical narratives.
(69/3027)
We introduce two abstraction mechanisms by which the process of semantic interpretation of medical narratives can be simplified and further optimized. One relates to generalized triggering conditions, the other to inheritance-based specifications of semantic rules. The proposed methodology leads to a parsimonious inventory of abstract, simple and domain-independent semantic interpretation schemata whose effectiveness has been evaluated on a medical text corpus. (+info)
A statistical natural language processor for medical reports.
(70/3027)
Statistical natural language processors have been the focus of much research during the past decade. The main advantage of such an approach over grammatical rule-based approaches is its scalability to new domains. We present a statistical NLP for the domain of radiology and report on methods of knowledge acquisition, parsing, semantic interpretation, and evaluation. Preliminary performance data are given. A discussion of the perceived benefit, limitations and future work is presented. (+info)
A feasibility study of two methods for end-user configuration of a clinical event monitor.
(71/3027)
We developed and evaluated a feature that allows users to control what types of clinical information are delivered to them. Using a paper or web-based configuration form, users turn individual alerts and sets of results on or off, and set how they are delivered. We used usage rates to evaluate this feature. Of 16 residents who had received clinical information from our clinical event monitor, 4 (25%) made at least one change (range 10-25). Of 41 interns, 5 (12.2%) made at least one change (range 5-91). The difference was borderline significant (p < 0.1). 5/7 web users changed preferences through a dial-up connection from home. More users used the web-based preference form than the paper form. This difference may be due to the better accessibility of the web-based form. A survey established that this feature was not as highly utilized as anticipated partly because the initial (default) preference setting was acceptable and partly because the users were too busy to customize their alert settings. We conclude that user configuration of a system that delivers information using a web-based preference form is feasible and may become important as the volume of information and number of available communication channels increase. (+info)
A programme for collaborative influenza surveillance. A report of a working group of the Public Health Laboratory Service.
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A surveillance programme is described which is intended to assess the effects of influenza virus infections on communities at large by collating influenza virus isolations and consultations for respiratory infections from general practices with new claims for sickness benefit and deaths from all causes. Particular importance is attached to relating virus isolations to symptomatic respiratory disease seen in practices of known age and sex structure. (+info)