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Journal List > AMIA Annu Symp Proc > v.2005; 2005

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AMIA Annu Symp Proc. 2005; 2005: 1035.
PMCID: PMC1560598
Copyright This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
Generating PubMed Chemical Queries for Consumer Health Literature
Jeffery Loo, MLIS, Associate Fellow
National Library of Medicine
Hua Florence Chang, MS, Colette Hochstein, DMD, MLS, and Ying Sun, MS
Specialized Information Services, National Library of Medicine, Bethesda, Maryland
Abstract
Two popular NLM resources that provide information for consumers about chemicals and their safety are the Household Products Database and Haz-Map. Search queries to PubMed via web links were generated from these databases. The query retrieves consumer health-oriented literature about adverse effects of chemicals. The retrieval was limited to a manageable set of 20 to 60 citations, achieved by successively applying increasing limits to the search until the desired number of references was reached.
Purpose
After learning about potential exposure to chemicals they use at home or at work, the general public may want to learn more by reviewing the appropriate biomedical literature. Web links with pre-constructed queries make it easy for them to obtain this information. However, chemical information retrieved from a simple PubMed search can be overwhelming or irrelevant for the general public. An algorithm was devised to establish PubMed queries that would retrieve a set of relevant, easy to understand, and easily browsable citations about chemicals.
Method
PubMed search links were implemented in the chemical records of the Household Products Database (HPD). HPD is the National Library of Medicine’s database on the health, safety, and chemical information for approximately 5,000 brand name household products.
After preliminary testing and experimentation, an algorithm for creating the queries was developed. The algorithm included: (1) a basic PubMed search query for the chemical, and (2) a set of limits added to the search. These limits were added successively, until the PubMed retrieval met the desired criteria of 20–60 consumer-oriented citations.
For chemicals with corresponding MeSH descriptors, the basic search query was (MeSH Term /adverse effects [MH:noexp] OR MeSH Term /poisoning [MH:noexp]). For chemicals which have corresponding Supplemental Concept Records in MeSH, the basic query was (SCR Term [NM] ). In both cases, the search was limited to English language and human studies. In order to limit the search to the specific chemical and not related or similar chemicals, MeSH terms were not exploded.
The following limits and changes to the search strategy were used in succession; each subsequent limit is more restrictive. Limits were applied stepwise until a retrieval of 20–60 citations was achieved.
  • Toxicology subset
  • For SCR terms, change the basic query to a related MeSH term search (if possible)
  • Journal subsets: nursing, consumer health, and core clinical journals subsets
  • For MeSH terms, change the basic query to a major topic search for the chemical term.
  • Review and case report publication types.
A Java program was written for processing the query and subsequent retrieval from PubMed via the Entrez Utility Esearch. The program sent queries to the PubMed database, and received a count of the number of citations retrieved. The count of the citations retrieved determined whether additional search parameters or limits would need to be appended to the query. The outputs of the program were web links with embedded search queries. These web links were then stored in the chemical records in the database.
Results
Household Products Database chemical records now contain web links that search PubMed for consumer health literature on chemicals. After the success of this implementation, PubMed search links, created with the same algorithm, were also placed in Haz-Map chemical records. Haz-Map is an NLM database on occupational diseases caused by work-related exposure to hazardous chemicals.
Conclusion
Linking chemical records to consumer health literature in PubMed was successfully implemented in two NLM databases. Similar algorithms could be applied to other domains by substituting the basic search query with domain-specific MeSH headings and subheadings, and changing the initial subject subset limit.
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