Number of found records: 18
|
PITKIN, Roy M.; BRANAGAN, Mary Ann |
|
Can the accuracy of abstracts be improved by providing specific instructions? A randomized controlled trial |
|
JAMA, jul 15 1998, vol.280, n.3, pp. 267. |
|
On line (11/2005) |
|
Pitkin and Branagan tested the hypothesis that providing authors with specific instructions about abstract accuracy will result in improved accuracy of abstracts for medical journals |
|
abstract accuracy; medical journal |
Assessment |
|
|
|
|
RAU, Lisa F.; BRANDOW, Ronald; MITZE, Karl |
|
Domain-Independent Summarization of News |
|
On line (12/05/2005) |
|
Implementation and testing of a prototype system for improving summarization of independent domain |
|
Summarization; evaluation. |
Assessment |
|
|
|
|
TULLY, Lorraine; RULON, Vera |
|
Evolution of the uses of ICD-9-CM coding: Medicare risk adjustment methodology for managed care plans |
|
Topics in Health Information Management, 2000,vol.21, n.2, pp.62-67. |
|
On line ( 15/06/2004)(Only UGR) |
|
The health information management (HIM) profession is expanding to new sites and perspectives. The implementation of Medicare managed care has brought changes not only by emphasis on management of the individual's medical care and the cost of that care, but also by creating new uses for coded data. This article examines the evolution of risk adjustment methods in Medicare Managed Care. The current choice for risk adjustment is the Principal Inpatient Diagnostic Cost Groups (PIP-- DCG). This article explains the health plan's submission of encounter data and how HIM can play a valuable role in data capture and improvement in data quality and reimbursement (AU) |
|
classification systems; data capture; risk adjustment methodology; Medicare+ Choice; |
Assessment |
|
|
|
|
VLEDUTS STOKOLOV, Natasha |
|
Concept recognition in an automatic text-processing system for the life sciences. |
|
Journal of the American Society for Information Science, 1987, vol. 38, n. 4, pp.269-287. |
|
On line (12/05/2005) |
|
Describes a natural-language text-processing system designed as an automatic aid to subject indexing at BIOSIS. The intellectual procedure the system should model is deep indexing with a controlled vocabulary of biological concepts-Concept Headings (CHs). On the average, 10 CHs are assigned to each articles by BIOSIS indexers. The automatic procedure consists of 2 stages: translation of natural-language biological titles into title-semantic representations which are in the constructed formalised language of Concept Primitives, and translation of the latter representations into the language of CHs. The first stage is performed by matching the titles against the system's Semantic Vocabulary (SV). The SV currently contains approximately 15,000 biological natural-language terms and their translations in the language of Concept Primitives. For the ambiguous terms, the SV contains the algorithmical rules of term disambiguation, rules based on semantic analysis of the contexts. The second stage of the automatic procedure is performed by matching the title representations against the CH definitions, formulated as Boolean search strategies in the language of Concept Primitives. (AU) |
|
Natural language; Technical services; Information storage and retrieval; Information work; Subject indexing ; Automatic subject indexing; BIOSIS |
Assessment |
|
|
|
|
