scholarly journals A systematic approach to searching: an efficient and complete method to develop literature searches

2018 ◽  
Vol 106 (4) ◽  
Author(s):  
Wichor M. Bramer ◽  
Gerdien B. De Jonge ◽  
Melissa L. Rethlefsen ◽  
Frans Mast ◽  
Jos Kleijnen
Keyword(s):  
Systematic Reviews ◽  
Search Strategy ◽  
Optimization Technique ◽  
Search Strategies ◽  
Biomedical Literature ◽  
Systematic Search ◽  
Free Text ◽  
Text Document ◽  
Search Terms ◽  
Free Text Search

Creating search strategies for systematic reviews, finding the best balance between sensitivity and specificity, and translating search strategies between databases is challenging. Several methods describe standards for systematic search strategies, but a consistent approach for creating an exhaustive search strategy has not yet been fully described in enough detail to be fully replicable. The authors have established a method that describes step by step the process of developing a systematic search strategy as needed in the systematic review. This method describes how single-line search strategies can be prepared in a text document by typing search syntax (such as field codes, parentheses, and Boolean operators) before copying and pasting search terms (keywords and free-text synonyms) that are found in the thesaurus. To help ensure term completeness, we developed a novel optimization technique that is mainly based on comparing the results retrieved by thesaurus terms with those retrieved by the free-text search words to identify potentially relevant candidate search terms. Macros in Microsoft Word have been developed to convert syntaxes between databases and interfaces almost automatically. This method helps information specialists in developing librarian-mediated searches for systematic reviews as well as medical and health care practitioners who are searching for evidence to answer clinical questions. The described method can be used to create complex and comprehensive search strategies for different databases and interfaces, such as those that are needed when searching for relevant references for systematic reviews, and will assist both information specialists and practitioners when they are searching the biomedical literature.

scholarly journals Errors in search strategies used in systematic reviews and their effects on information retrieval

2019 ◽  
Vol 107 (2) ◽  
Author(s):  
José Antonio Salvador-Oliván ◽  
Gonzalo Marco-Cuenca ◽  
Rosario Arquero-Avilés
Keyword(s):  
Systematic Reviews ◽  
Search Strategies ◽  
Primary Objective ◽  
Free Text ◽  
Medical Subject Headings ◽  
Search Terms ◽  
Pubmed Search ◽  
Meta Analyses ◽  
Mesh Database ◽  
Controlled Language

Objectives: Errors in search strategies negatively affect the quality and validity of systematic reviews. The primary objective of this study was to evaluate searches performed in MEDLINE/PubMed to identify errors and determine their effects on information retrieval.Methods: A PubMed search was conducted using the systematic review filter to identify articles that were published in January of 2018. Systematic reviews or meta-analyses were selected from a systematic search for literature containing reproducible and explicit search strategies in MEDLINE/PubMed. Data were extracted from these studies related to ten types of errors and to the terms and phrases search modes.Results: The study included 137 systematic reviews in which the number of search strategies containing some type of error was very high (92.7%). Errors that affected recall were the most frequent (78.1%), and the most common search errors involved missing terms in both natural language and controlled language and those related to Medical Subject Headings (MeSH) search terms and the non-retrieval of their more specific terms.Conclusions: To improve the quality of searches and avoid errors, it is essential to plan the search strategy carefully, which includes consulting the MeSH database to identify the concepts and choose all appropriate terms, both descriptors and synonyms, and combining search techniques in the free-text and controlled-language fields, truncating the terms appropriately to retrieve all their variants.

scholarly journals Development of an efficient search filter to retrieve systematic reviews from PubMed

2021 ◽  
Vol 109 (4) ◽  
Author(s):  
José Antonio Salvador-Oliván ◽  
Gonzalo Marco-Cuenca ◽  
Rosario Arquero-Avilés
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Systematic Reviews ◽  
Search Strategy ◽  
Average Precision ◽  
Search Filter ◽  
Search Terms ◽  
Mesh Terms ◽  
Cochrane Database ◽  
Relevant Publication

Objective: Locating systematic reviews is essential for clinicians and researchers when creating or updating reviews and for decision-making in health care. This study aimed to develop a search filter for retrieving systematic reviews that improves upon the performance of the PubMed systematic review search filter.Methods: Search terms were identified from abstracts of reviews published in Cochrane Database of Systematic Reviews and the titles of articles indexed as systematic reviews in PubMed. Both the precision of the candidate terms and the number of systematic reviews retrieved from PubMed were evaluated after excluding the subset of articles retrieved by the PubMed systematic review filter. Terms that achieved a precision greater than 70% and relevant publication types indexed with MeSH terms were included in the filter search strategy.Results: The search strategy used in our filter added specific terms not included in PubMed’s systematic review filter and achieved a 61.3% increase in the number of retrieved articles that are potential systematic reviews. Moreover, it achieved an average precision that is likely greater than 80%.Conclusions: The developed search filter will enable users to identify more systematic reviews from PubMed than the PubMed systematic review filter with high precision.

scholarly journals On the Way to Close the Loop in Information Logistics: Data from the Patient — Value for the Patient

2018 ◽  
Vol 27 (01) ◽  
pp. 091-097 ◽  
Author(s):  
Werner Hackl ◽  
Alexander Hoerbst ◽  
Keyword(s):  
Information Systems ◽  
Medical Informatics ◽  
Clinical Information ◽  
Data Reuse ◽  
Clinical Information Systems ◽  
Free Text ◽  
Search Terms ◽  
Information Logistics ◽  
Free Text Search ◽  
Selection Of

Objective: To summarize recent research and to propose a selection of best papers published in 2017 in the field of Clinical Information Systems (CIS). Method: Each year a systematic process is carried out to retrieve articles and to select a set of best papers for the CIS section of the International Medical Informatics Association (IMIA) Yearbook of Medical Informatics. The query aiming at identifying relevant publications in the field of CIS was refined by the section editors during the last years. For three years now, the query is stable. It comprises search terms from the Medical Subject Headings (MeSH) thesaurus as well as additional free text search terms from PubMed and Web of Science®. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results, the best papers were then selected by the IMIA Yearbook editorial board. Text mining, and term co-occurrence mapping techniques were used to get an overview on the content of the retrieved articles. Results: The query was carried out in mid-January 2018, yielding a consolidated result set of 2,255 articles which had been published in 939 different journals. Out of them, 15 papers were nominated as candidate best papers and four of them were finally selected as best papers in the CIS section. Again, the content analysis of the articles revealed the broad spectrum of topics which is covered by CIS research. Conclusions: Modern clinical information systems serve as backbone for a very complex, trans-institutional information logistics process. Data that is produced by, documented in, shared via, organized in, presented by, and stored within clinical information systems is more and more reused for multiple purposes. We found a lot of examples showing the benefits of such data reuse with various novel approaches implemented to tackle the challenges of this process. We also found that the patient moves in the focus of interest of CIS research. So the loop of information logistics begins to close: data from the patients is used to produce value for the patients.

scholarly journals Naming Specific Adverse Effects Improves Relative Recall for Search Filters Identifying Literature on Surgical Interventions in MEDLINE and Embase

2019 ◽  
Vol 14 (1) ◽  
pp. 65-67
Author(s):  
Ann Glusker
Keyword(s):  
Adverse Effects ◽  
Systematic Reviews ◽  
Mesh Term ◽  
Search Strategies ◽  
User Engagement ◽  
Discussion Section ◽  
Surgical Interventions ◽  
Search Terms ◽  
Search Filters ◽  
Specific Search

A Review of: Golder, S., Wright, K., & Loke, Y.K. (2018). The development of search filters for adverse effects of surgical interventions in MEDLINE and Embase. Health Information and Libraries Journal, 35(2), 121-129. https://doi.org/10.1111/hir.12213 Abstract Objective – “To develop and validate search filters for MEDLINE and Embase for the adverse effects of surgical interventions” (p.121). Design – From a universe of systematic reviews, the authors created “an unselected cohort…where relevant articles are not chosen because of the presence of adverse effects terms” (p.123). The studies referenced in the cohort reviews were extracted to create an overall citation set. From this, three equal-sized sets of studies were created by random selection, and used for: development of a filter (identifying search terms); evaluation of the filter (testing how well it worked); and validation of the filter (assessing how well it retrieved relevant studies). Setting – Systematic reviews of adverse effects from the Database of Abstracts of Reviews of Effects (DARE), published in 2014. Subjects – 358 studies derived from the references of 19 systematic reviews (352 available in MEDLINE, 348 available in Embase). Methods – Word and phrase frequency analysis was performed on the development set of articles to identify a list of terms, starting with the term creating the highest recall from titles and abstracts of articles, and continuing until adding new search terms produced no more new records recalled. The search strategy thus developed was then tested on the evaluation set of articles. In this case, using the strategy recalled all of the articles which could be obtained using generic search terms; however, adding specific search terms (such as the MeSH term “surgical site infection”) improved recall. Finally, the strategy incorporating both generic and specific search terms for adverse effects was used on the validation set of articles. Search strategies used are included in the article, as is a list in the discussion section of MeSH and Embase indexing terms specific to or suggesting adverse effects. Main Results – “In each case the addition of specific adverse effects terms could have improved the recall of the searches” (p. 127). This was true for all six cases (development, evaluation and validation study sets, for each of MEDLINE and Embase) in which specific terms were added to searches using generic terms, and recall percentages compared. Conclusion – While no filter can deliver 100% of items in a given standard set of studies on adverse effects (since title and abstract fields may not contain any indication of relevance to the topic), adding specific adverse effects terms to generic ones while developing filters is shown to improve recall for surgery-related adverse effects (similarly to drug-related adverse effects). The use of filters requires user engagement and critical analysis; at the same time, deploying well-constructed filters can have many benefits, including: helping users, especially clinicians, get a search started; managing a large and unwieldy set of citations retrieved; and to suggest new search strategies.

scholarly journals Clinical Information Systems as the Backbone of a Complex Information Logistics Process: Findings from the Clinical Information Systems Perspective for 2016

2017 ◽  
Vol 26 (01) ◽  
pp. 103-109 ◽  
Author(s):  
W. O. Hackl ◽  
T. Ganslandt
Keyword(s):  
Information Systems ◽  
Clinical Information ◽  
Clinical Information Systems ◽  
Free Text ◽  
Medical Subject Headings ◽  
Search Terms ◽  
Information Logistics ◽  
Free Text Search ◽  
Logistics Process ◽  
Selection Of

Summary Objective: To summarize recent research and to propose a selection of best papers published in 2016 in the field of Clinical Information Systems (CIS). Method: The query used to retrieve the articles for the CIS section of the 2016 edition of the IMIA Yearbook of Medical Informatics was reused. It again aimed at identifying relevant publications in the field of CIS from PubMed and Web of Science and comprised search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results, the best papers were then chosen at the selection meeting with the IMIA Yearbook editorial board. Text mining, term co-occurrence mapping, and topic modelling techniques were used to get an overview on the content of the retrieved articles. Results: The query was carried out in mid-January 2017, yielding a consolidated result set of 2,190 articles published in 921 different journals. Out of them, 14 papers were nominated as candidate best papers and three of them were finally selected as the best papers of the CIS field. The content analysis of the articles revealed the broad spectrum of topics covered by CIS research. Conclusions: The CIS field is multi-dimensional and complex. It is hard to draw a well-defined outline between CIS and other domains or other sections of the IMIA Yearbook. The trends observed in the previous years are progressing. Clinical information systems are more than just sociotechnical systems for data collection, processing, exchange, presentation, and archiving. They are the backbone of a complex, trans-institutional information logistics process.

scholarly journals Updating search strategies for systematic reviews using EndNote

2017 ◽  
Vol 105 (3) ◽  
Author(s):  
Wichor Bramer ◽  
Paul Bain
Keyword(s):  
Systematic Reviews ◽  
Search Strategy ◽  
Search Strategies ◽  
New Method

A new method is described to update search strategies in multiple databases without the use of date limits. By deduplication of the most recent EndNote library with the EndNote library created at the time of the earlier search only recently added references or older references now retrieved by a changed search strategy remain.

scholarly journals Efficiency and contribution of strategies for finding randomized controlled trials: a case study from a systematic review on therapeutic interventions of chronic depression

2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Annika Westphal ◽  
Levente Kriston ◽  
Lars P. Hölzel ◽  
Martin Härter ◽  
Alessa Von Wolff
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Search Strategy ◽  
Reference Lists ◽  
Search Strategies ◽  
Database Search ◽  
Controlled Trials ◽  
Electronic Database ◽  
Randomized Controlled ◽  
Electronic Database Search

<em>Background</em>. Identifying all existing evidence is a crucial aspect in conducting systematic reviews. Since the retrieval of electronic database searches alone is limited, guidelines recommend the use of addi- tional search strategies. The aim of this investigation was to assess the efficiency and contribution of additional search strategies for identifying randomized controlled trials in conducting a systematic review on interventions after performing a sensitive electronic database search. <br /><em>Design and Methods</em>. Seven electronic databases, 3 journals and 11 systematic reviews were searched. All first authors of the included studies were contacted; citation tracking and a search in clinical trial registers were performed. <em>A priori</em> defined evaluation criteria were calculated for each search strategy. <br /><em>Results</em>. A total of 358 full-text articles were identified; 50 studies were included in the systematic review, wherefrom 84.0% (42) were acquired by the sensitive electronic database search and 16.0% (8) through additional search strategies. Screening reference lists of related systematic reviews was the most beneficial additional search strategy, with an efficiency of 31.3% (5) and a contribution of 10.0% (5/50), whereas hand-searching and author contacts contributed two and one additional studies, respectively. Citation tracking and searching clinical trial registers did not lead to any further inclusion of primary studies. <br /><em>Conclusions</em>. Based on our findings, hand-searching contents of relevant journals and screening reference lists of related systematic reviews may be helpful additional strategies to identify an extensive body of evidence. In case of limited resources, a sensitive electronic database search may constitute an appropriate alternative for identifying relevant trials.

scholarly journals New Problems - New Solutions: A Never Ending Story

2016 ◽  
Vol 25 (01) ◽  
pp. 146-151 ◽  
Author(s):  
T. Ganslandt ◽  
W.O. Hackl ◽  
Keyword(s):  
Clinical Information ◽  
Free Text ◽  
Medical Subject Headings ◽  
Search Terms ◽  
Research Activities ◽  
Free Text Search ◽  
Problems And Solutions ◽  
Mapping Techniques ◽  
Selection Of

Summary Objective: To summarize recent research and to propose a selection of best papers published in 2015 in the field of Clinical Information Systems (CIS). Method: The query which had been used last year to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics 2015 was refined. It again aimed at identifying relevant publications in the field of CIS and comprised search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms from PubMed and Web of Science. The retrieved articles were categorized in a multi-pass review carried out separately by the two section editors. The final selection of 15 candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results the four best papers were then selected at the best papers selection meeting with the IMIA Yearbook editorial board. To get an overview on the content of the retrieved articles we applied text mining and term co-occurrence mapping techniques. Results: The query was carried out in mid-January 2016, yielding a combined result set of 1851 articles which were published in 790 different journals. The most relevant terms from abstracts and titles of these articles were assigned to six different clusters. A majority of articles dealt with two thematic blocks, problems and solutions in the CIS field. The majority of the 2016 CIS candidate papers and all four best papers could be assigned to these two thematic blocks. Conclusions: We identified two main tracks among the CIS candidate and best papers as well as in CIS research activities in general: problems and solutions. A never ending cycle of continuous improvement.

scholarly journals P.002 Improving the quality of systematic reviews of neurological conditions with more accurate search strategies: a series of validation studies

2017 ◽  
Vol 44 (S2) ◽  
pp. S14-S15
Author(s):  
KA Bui ◽  
J Abdaem ◽  
GC Gore ◽  
MR Keezer
Keyword(s):  
Systematic Reviews ◽  
English Language ◽  
Search Strategy ◽  
Search Strategies ◽  
Electronic Database ◽  
Mesh Terms ◽  
Pubmed Search ◽  
Neurological Conditions ◽  
Sensitivity Specificity

Background: A well-constructed search strategy is an important feature of any systematic review. We aimed to design and validate electronic database (e.g. Pubmed) search strategies (i.e. a hedge or series of words used to identify articles of interest) for six neurological conditions. Methods: We enumerated 10311 consecutive articles in the 21 highest impact factor English-language general neurology journals. We constructed a simple hedge, limited to one keyword, for each condition. We also constructed a complex hedge using a series of MeSH terms and keywords. Two reviewers independently reviewed (confirmed by a third reviewer) all articles and established which condition(s) were the article’s subject. We calculated sensitivity/specificity estimates for the simple and complex hedges, and compared these using McNemar’s test. Results: The results are summarized in the Table. Conclusions: Our complex hedges for most conditions dramatically improve sensitivity without compromising specificity. This study will help improve the accuracy of search strategies in future systematic reviews.

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