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Populating decision-analytic models: The feasibility and efficiency of database searching for individual parameters

Published online by Cambridge University Press:  04 August 2005

Su Golder ,
Julie Glanville  and
Laura Ginnelly
Su Golder
Affiliation:
University of York
Julie Glanville
Affiliation:
University of York
Laura Ginnelly
Affiliation:
University of York
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Abstract

Objectives: The aim of the study was to investigate the feasibility and effectiveness of searching selected databases to identify information required to populate a decision-analytic model.

Methods: Methods of searching for information to populate a decision-analytic model were piloted using a case study of prophylactic antibiotics to prevent recurrent urinary tract infections in children. This study explored how the information requirements for a decision-analytic model could be developed into searchable questions and how search strategies could be derived to answer these questions. The study also assessed the usefulness of three published search filters and explored which resources might produce relevant information for the various model parameters.

Results: Based on the data requirements for this case study, 42 questions were developed for searching. These questions related to baseline event rates, health-related quality of life and outcomes, relative treatment effects, resource use and unit costs, and antibiotic resistance. A total of 1,237 records were assessed by the modeler, and of these, 48 were found to be relevant to the model. Search precision ranged from 0 percent to 38 percent, and no single database proved the most useful for all the questions.

Conclusions: The process of conducting specific searches to address each of the model questions provided information that was useful in populating the case study model. The most appropriate resources to search were dependent on the question, and multiple database searching using focused search strategies may prove more effective in finding relevant data than thorough searches of a single database.

Keywords

Information storage and retrievalDecision support techniquesDatabases
Type
GENERAL ESSAYS
Information
International Journal of Technology Assessment in Health Care , Volume 21 , Issue 3 , July 2005 , pp. 305 - 311
Copyright
© 2005 Cambridge University Press

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