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

Su Golder; Julie Glanville; Laura Ginnelly

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

Su Golder, Julie Glanville, Laura Ginnelly

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	305-11
Number of pages	7
Journal	International Journal of Technology Assessment in Health Care
Volume	21
Issue number	3
Publication status	Published - 2005

Keywords

Anti-Bacterial Agents
Child
Cost-Benefit Analysis
Databases, Factual
Decision Support Techniques
Drug Resistance, Bacterial
Humans
Infant
Information Storage and Retrieval
Quality-Adjusted Life Years
Urinary Tract Infections

Access to Document

http://www.ncbi.nlm.nih.gov/pubmed/16110709

Cite this

@article{323fe9679d6c4b2bbcb5f3cc49f278f6,

title = "Populating decision-analytic models: the feasibility and efficiency of database searching for individual parameters",

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 = "Anti-Bacterial Agents, Child, Cost-Benefit Analysis, Databases, Factual, Decision Support Techniques, Drug Resistance, Bacterial, Humans, Infant, Information Storage and Retrieval, Quality-Adjusted Life Years, Urinary Tract Infections",

author = "Su Golder and Julie Glanville and Laura Ginnelly",

year = "2005",

language = "English",

volume = "21",

pages = "305--11",

journal = "International Journal of Technology Assessment in Health Care",

issn = "0266-4623",

publisher = "Cambridge University Press",

number = "3",

}

TY - JOUR

T1 - Populating decision-analytic models

T2 - the feasibility and efficiency of database searching for individual parameters

AU - Golder, Su

AU - Glanville, Julie

AU - Ginnelly, Laura

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

KW - Anti-Bacterial Agents

KW - Child

KW - Cost-Benefit Analysis

KW - Databases, Factual

KW - Decision Support Techniques

KW - Drug Resistance, Bacterial

KW - Humans

KW - Infant

KW - Information Storage and Retrieval

KW - Quality-Adjusted Life Years

KW - Urinary Tract Infections

M3 - Article

C2 - 16110709

SN - 0266-4623

VL - 21

SP - 305

EP - 311

JO - International Journal of Technology Assessment in Health Care

JF - International Journal of Technology Assessment in Health Care

IS - 3

ER -