Utilization of the PICO framework to improve searching PubMed for clinical questions
Open accessAbstract
Background: Supporting 21 st century health care and the practice of evidence-based medicine (EBM) requires ubiquitous access to clinical information and to knowledge-based resources to answer clinical questions. Many questions go unanswered, however, due to lack of skills in formulating questions, crafting effective search strategies, and accessing databases to identify best levels of evidence. Methods: This randomized trial was designed as a pilot study to measure the relevancy of search results using three different interfaces for the PubMed search system. Two of the search interfaces utilized a specific framework called PICO, which was designed to focus clinical questions and to prompt for publication type or type of question asked. The third interface was the standard PubMed interface readily available on the Web. Study subjects were recruited from interns and residents on an inpatient general medicine rotation at an academic medical center in the US. Thirty-one subjects were randomized to one of the three interfaces, given 3 clinical questions, and asked to search PubMed for a set of relevant articles that would provide an answer for each question. The success of the search results was determined by a precision score, which compared the number of relevant or gold standard articles retrieved in a result set to the total number of articles retrieved in that set. Results: Participants using the PICO templates (Protocol A or Protocol B) had higher precision scores for each question than the participants who used Protocol C, the standard PubMed Web interface. (Question 1: A = 35%, B = 28%, C = 20%; Question 2: A = 5%, B = 6%, C = 4%; Question 3: A = 1%, B = 0%, C = 0%) 95% confidence intervals were calculated for the precision for each question using a lower boundary of zero. However, the 95% confidence limits were overlapping, suggesting no statistical difference between the groups. Conclusion: Due to the small number of searches for each arm, this pilot study could not demonstrate a statistically significant difference between the search protocols. However there was a trend towards higher precision that needs to be investigated in a larger study to determine if PICO can improve the relevancy of search results.
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The PICOS framework was followed a priori to identify key study concepts and facilitate the search process.
“The population, interventions, comparisons, outcomes, and study design (PICOS) framework [27] was followed to identify key study concepts in the research question a priori, and to facilitate the search process.”
The search strategy was implemented following the PRISMA-P checklist.
“The population, intervention, comparison, and outcome framework [25] was used to develop the search strategy, which was implemented following the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analyses Protocols) checklist [26].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [25]
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- Authors
- Schardt, C., Adams, M. B., Owens, T., Keitz, S., & Fontelo, P.
- Affiliations
- Duke University (US)
- Miami VA Healthcare System (US)
- United States National Library of Medicine (US)
- Corresponding author
- Schardt, Connie
- Adams, Martha B
- Owens, Thomas
- Keitz, Sheri
- Fontelo, Paul
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2007-06-15
- Volume
- 7
- Issue
- 1
- Pages
- 16-16
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC1904193
- OpenAlex
- W2111722073
- Cited by
- 3,053
- References
- 14
- Citations by year
- 2026: 346 · 2025: 460 · 2024: 364 · 2023: 345 · 2022: 380 · 2021: 302 · 2020: 310 · 2019: 134 · 2018: 93 · 2017: 79 · 2016: 57 · 2015: 46 · 2014: 35 · 2013: 18 · 2012: 24
- FWCI
- 24.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- PICO framework, PubMed search, clinical question formulation, evidence-based medicine, search result relevance, search interface design, medical information retrieval
- MeSH terms
- Humans, Internship and Residency, Medical Informatics, Probability, Surveys and Questionnaires, Sensitivity and Specificity, MEDLINE, Information Storage and Retrieval, Evidence-Based Medicine, PubMed, Medical Subject Headings
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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