Article type
Year
Abstract
Background: Diagnostic test methods usually have been applied in studies with search strategies development purpose to evaluate the search terms and search strategies. These methods compile a set of relevant studies as the “gold standard” and determine the sensitivity, specificity,precision and accuracy of searches. If the gold standard has been produced by following the sensitive search in bibliographic databases, the sensitivity and precision of search queries and strategies have been evaluated and compared.
Objectives: This study aimed to build and develop a computational program for combining search queries to design a highly sensitive search strategy, aswell as an optimal sensitive and precise one.
Methods: An algorithm has been introduced to measure the sensitivity and precision of search terms and their combinations with purpose of finding the most sensitive combination of search terms. Then, a C++ code is developed to capture user-defined search terms and their dependencies and constraints to derive optimized combinations. In order to test and improve the program, our former data on developing search strategies have been assessed continuously to identify reports of off- label drug use in MEDLINE and EMBASE via OvidSP.
Results: Two versions of the software, SenPrecOptim, have been developed. They automatically perform calculations regarding the sensitivity and precision of search queries and all their possible combinations. The software outputs the optimized ranked list of search queries combinations based on the sensitivity in a .csv file. The best balance of sensitivity and precision strategy of optimized outputs can be obtained by finding the best-fit line on the scatter plot of sensitivity versus precision.
Conclusions: The evaluation of search queries combinations can be enhancedby utilization of this software. The output of this yields the best-balanced sensitive and precisesearch strategies.
Objectives: This study aimed to build and develop a computational program for combining search queries to design a highly sensitive search strategy, aswell as an optimal sensitive and precise one.
Methods: An algorithm has been introduced to measure the sensitivity and precision of search terms and their combinations with purpose of finding the most sensitive combination of search terms. Then, a C++ code is developed to capture user-defined search terms and their dependencies and constraints to derive optimized combinations. In order to test and improve the program, our former data on developing search strategies have been assessed continuously to identify reports of off- label drug use in MEDLINE and EMBASE via OvidSP.
Results: Two versions of the software, SenPrecOptim, have been developed. They automatically perform calculations regarding the sensitivity and precision of search queries and all their possible combinations. The software outputs the optimized ranked list of search queries combinations based on the sensitivity in a .csv file. The best balance of sensitivity and precision strategy of optimized outputs can be obtained by finding the best-fit line on the scatter plot of sensitivity versus precision.
Conclusions: The evaluation of search queries combinations can be enhancedby utilization of this software. The output of this yields the best-balanced sensitive and precisesearch strategies.