Drug Information Retrieval Flashcards
Dr. Amaeze
Define drug information retrieval.
Drug information retrieval refers to the process of locating, accessing, and obtaining relevant drug-related data and information to address specific queries or clinical needs.
It involves using various resources, tools, and techniques to gather evidence-based, accurate, and current information.
What is the first step in DI retrieval?
The first step in DI retrieval is the definition of the DI query.
This involves clearly articulating the question or clinical problem to be addressed e.g., identify whether the query is related to drug indications, dosing, adverse effects, interactions, or another topic
Highlight, in order, the steps involved in DI retrieval.
- Definition of the DI query
- Identify relevant resources (primary, secondary or tertiary)
- Conduct the search using the appropriate tools and search terms
Biomedical researchers commonly rely on databases such as ________, and search engines such as ________ to source reliable information.
- PubMed
- Google Scholar
What are the two types of search options on a database?
- Indexed search
- Free text search
What are the advantages of free text search?
- It is useful when index terms fail to yield results or when dealing with emerging terms lacking official index entries
- It can capture in-process citations and non-standard terminology
A well-rounded search strategy includes ____________.
Various terms to ensure completeness.
Successful DI retrieval from a database depends on ________.
Adapting the search strategy to the system-specific features of the database.
A good example of the standardised term for DI retrieval is _______.
Medical Subject Headings (MeSH)
_______ further refine searches by defining relationships between terms, thus enabling users to obtain more targeted and relevant results.
Boolean operators
Discuss MeSH terms.
MEDLINE’s MeSH terms effectively provide a standardised vocabulary for indexing and searching articles.
These terms are organized into a hierarchical tree structure, enabling both broad and narrow searches.
For instance, users can explore broad topics like cardiovascular diseases or focus on specific facets such as cardiac tamponade.
Each MeSH term may have associated subheadings (e.g., drug therapy or complications), which can also be subdivided further, offering precision in targeting specific aspects of a topic.
When searching, users can choose between narrow subheadings (e.g., congenital heart defects: drug therapy) or broader categories (e.g., congenital heart defects), depending on their informational needs.
What are other search methods provided by MEDLINE?
- Keyword
- Journal name
- Author
- Article title
Differentiate between Keywords and MeSH terms.
Keywords, unlike MeSH terms, are derived from an article’s title, abstract, or indexed terms.
While keyword searches can be useful when specific MeSH terms are unavailable, they often yield broader, less focused results.
For example, a keyword search may identify irrelevant articles, whereas a MeSH term ensures precise matching.
In some cases, such as for newly
released drugs that lack assigned MeSH terms, keyword searches become the optimal strategy
Though this mapping may not always succeed, search engines like ______ or _____ often attempt to automatically map keywords to MeSH terms.
Ovid or EBSCO
Discuss Boolean operators.
Boolean operators are essential tools for conducting efficient and focused searches, especially when retrieving drug information or research data from databases like PubMed, Google Scholar, or library catalogues.
They allow you to combine search terms to refine and structure your query for optimal results.
The three main Boolean operators are: AND, OR and NOT.
The operator AND will combine two terms, returning only citations containing both of those concepts or terms. Most databases will automatically combine terms using AND if a term is not specified in the search.
Combining two terms with the operator OR will result in an equal or greater number of returns since it will include any citation where either term is used.
NOT will always decrease the number of returns since it eliminates any references with that term. It may eliminate relevant articles simply because the term appears somewhere in the article.
