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pico-search-strategy

translate research questions into PubMed search strategies

Covers Research PubMed Life Sciences Bioinformatics

Description

Translate a clinical or research question into a PICO/PECO-structured PubMed + Europe PMC search strategy with MeSH terms, field tags, and search hedges. Use whenever the user asks a comparative-effectiveness, etiology, prognosis, diagnosis, or HEOR question, OR when they explicitly ask for a "search strategy".

SKILL.md

PICO Search Strategy

You are constructing a transparent, reproducible literature-search strategy for a pharmaceutical researcher. The goal is to produce a query that another analyst could re-run six months from now and get the same hits.

Workflow

1. Decompose the question into PICO (or PECO for etiology)

ElementClinical questionEtiology / safety question
PPopulationPopulation
IInterventionExposure
CComparatorComparator (often unexposed)
OOutcomeOutcome

Restate the user's question as a single PICO sentence and confirm with them before running searches if anything is ambiguous (especially the population — adults vs. pediatric, treatment-naive vs. refractory).

2. Build the concept blocks

For each PICO element, build a concept block that combines:

  • Controlled vocabulary: MeSH (PubMed) and EMTREE-equivalent terms. Use the [MeSH] field tag and explode by default.
  • Free-text synonyms: include brand + generic drug names, gene symbols
    • protein names, and the major spelling variants (US/UK).
  • Field tags to control precision: [Title/Abstract] for high-precision blocks, no tag for high-recall blocks.

Combine within a block with OR, between blocks with AND.

3. Apply methodologic filters as a separate block

Use validated search hedges rather than ad-hoc filters:

  • Systematic reviews: (systematic review[PT] OR meta-analysis[PT])
  • RCTs: append the Cochrane Highly Sensitive Search Strategy for RCTs.
  • Observational studies: (cohort studies[MeSH] OR case-control studies[MeSH] OR observational study[PT])
  • Real-world evidence: combine ("real world"[TIAB] OR "real-world"[TIAB] OR registry[TIAB]) with the population block.

4. Add date / language / human filters last

  • Date: ("YYYY/MM/DD"[PDAT] : "YYYY/MM/DD"[PDAT]). Default to the last 5 years for active areas, 10 years for chronic-disease background.
  • Humans: humans[MeSH] only when the user wants to exclude in-vitro / animal work.
  • Language: avoid filtering by language unless explicitly requested; doing so introduces selection bias.

5. Run + report

Always report:

  • The full PubMed query string verbatim (the user must be able to paste it into PubMed).
  • The hit count.
  • For Europe PMC, the equivalent query in Europe PMC field-tag syntax (TITLE:, ABS:, MESH:, KW:, PUB_YEAR:YYYY TO YYYY).
  • A one-paragraph rationale for the trade-offs (why MeSH explosion was/was not used, why a particular synonym was included).

If hits exceed ~500, propose narrowing concept-by-concept; if hits are under ~10, propose loosening the highest-precision block first (typically the outcome).

Tools to call

  • search_pubmed for free-text + field-tag queries.
  • advanced_search when the request specifies dates, MeSH, journal, or publication type as discrete filters.
  • search_europe_pmc for the parallel Europe PMC run (broader coverage).

What good output looks like

A pharma evidence-generation analyst should be able to take your output, paste the query into PubMed and Europe PMC, and confirm the hit count matches yours within a small drift (NCBI updates daily). Include the PRISMA-style "search executed on YYYY-MM-DD" line.

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