ArticleJournal of the Medical Library Association : JMLA2020
Influence of library relocation and marketing: examining zip codes and health disparities to serve consumers in East Tennessee.
Article in Journal of the Medical Library Association : JMLA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Systematic librarian-led zip code analysis to target underserved communities.Journal of the Medical Library Association : JMLA · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 2014, the Preston Medical Library underwent a radical change, moving from an academic office building to the main floor of a regional medical center. While the library had previously served the public, health information requests have substantially increased in volume due to the new location. Researchers analyzed request data to see if the service's reach has expanded to counties that previously had not used the service, to see which counties have requested the most health information, and to ascertain whether more requests are from counties with higher poverty rates. CASE PRESENTATION: Each health information request is logged with the subject nature and patron contact information. Consumer health request data were downloaded from the library database. Names and other identifying data were removed. Request forms were sorted and reviewed by zip code and county, comparing number of requests as well as poverty levels. Tableau was utilized to create maps, visually showing patron concentrations and poverty levels.
conclusionsThere were 3,141 health information requests from September 21, 2014, to May 31, 2019. The majority of requests were from local counties. Requests were also received from counties that had not been previously reached and counties with elevated poverty levels. Collecting data on patron interactions is not only critical for institutional reporting, but also for community outreach. Understanding that data require taking additional steps to filter the information, assess local demographics, and customize library services. Researchers anticipate being able to better tailor services to the community based on the results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.