title: Populating decision-analytic models: the feasibility and efficiency of database searching for individual parameters.
abstract: OBJECTIVE
  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.
authors.affiliation: University of York, York YO10 5DD, UK. spg3@york.ac.uk
authors.forename: Su
authors.initials: S
authors.lastname: Golder
authors.forename: Julie
authors.initials: J
authors.lastname: Glanville
authors.forename: Laura
authors.initials: L
authors.lastname: Ginnelly
mesh_terms: D000900:Anti-Bacterial Agents / Q000191:economics / Q000627:therapeutic use; D002648:Child; D003362:Cost-Benefit Analysis; D016208:Databases, Factual; D003661:Decision Support Techniques; D024881:Drug Resistance, Bacterial; D006801:Humans; D007223:Infant; D016247:Information Storage and Retrieval / Q000379:methods*; D019057:Quality-Adjusted Life Years; D014552:Urinary Tract Infections / Q000191:economics / Q000517:prevention & control
chemical_list: D000900:Anti-Bacterial Agents