Accessing heterogeneous sources of evidence to answer clinical questions. Review uri icon

Overview

MeSH

  • Humans
  • Information Systems
  • Library Services
  • Medical Records Systems, Computerized
  • Online Systems
  • Terminology as Topic

MeSH Major

  • Computational Biology
  • Information Storage and Retrieval

abstract

  • The large and rapidly growing number of information sources relevant to health care, and the increasing amounts of new evidence produced by researchers, are improving the access of professionals and students to valuable information. However, seeking and filtering useful, valid information can be still very difficult. An online information system that conducts searches based on individual patient data can have a beneficial influence on the particular patient's outcome and educate the healthcare worker. In this paper, we describe the underlying model for a system that aims to facilitate the search for evidence based on clinicians' needs. This paper reviews studies of information needs of clinicians, describes principles of information retrieval, and examines the role that standardized terminologies can play in the integration between a clinical system and literature resources, as well as in the information retrieval process. The paper also describes a model for a digital library system that supports the integration of clinical systems with online information sources, making use of information available in the electronic medical record to enhance searches and information retrieval. The model builds on several different, previously developed techniques to identify information themes that are relevant to specific clinical data. Using a framework of evidence-based practice, the system generates well-structured questions with the intent of enhancing information retrieval. We believe that by helping clinicians to pose well-structured clinical queries and including in them relevant information from individual patients' medical records, we can enhance information retrieval and thus can improve patient-care.

publication date

  • April 2001

has subject area

  • Computational Biology
  • Humans
  • Information Storage and Retrieval
  • Information Systems
  • Library Services
  • Medical Records Systems, Computerized
  • Online Systems
  • Terminology as Topic

Research

keywords

  • Journal Article
  • Review

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1006/jbin.2001.1012

PubMed ID

  • 11515415

Additional Document Info

start page

  • 85

end page

  • 98

volume

  • 34

number

  • 2