QUT ePrints

Assessment of preferences for classification detail in medical information: is uniformity better?

Lorence, Daniel P. & Spink, Amanda H. (2003) Assessment of preferences for classification detail in medical information: is uniformity better? Information Processing and Management, 39(3), pp. 465-477.

View at publisher

Abstract

The growing acceptance of evidence-based decision making in healthcare organizations has resulted in recognition of information classification and retrieval as a key area of both strategic and operational management. In the emerging information-intensive healthcare environment, healthcare managers are beginning to understand the increased need for formal, continuous information classification and coding in health services, creating a need for enhanced information retrieval, delivery of services and quality management. Variation in classification preferences across practice settings poses healthcare quality management problems for evidence-based medicine in such an environment. This paper reports results from a major national study into the perceived variation reported by health information managers related to the relevance-efficiency trade-offs of information classification across regions and practice settings. This study provides: (1) a benchmark of the degree of such variation, examining how classification preferences vary across organization types, regions, and management indicators, and (2) the extent to which managers prefer more descriptive classification systems, despite nationwide mandates to adopt greater non-descriptive categorization of information. Findings suggest that due to major regional variation, stringent national information standards may be counterproductive for some healthcare practice settings and geographic locations. Implications for healthcare information classification and retrieval are further examined and discussed.

Impact and interest:

0 citations in Scopus
Search Google Scholar™
0 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

307 since deposited on 14 Sep 2006
63 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 5002
Item Type: Journal Article
Keywords: health, classification, retrieval, coding, evidence, based, medical
DOI: 10.1016/S0306-4573(02)00095-X
ISSN: 0306-4573
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2003 Elsevier
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 14 Sep 2006
Last Modified: 29 Feb 2012 23:19

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page