Claude in Systematic Reviews and Evidence Synthesis

Use Claude before the protocol to find ambiguity

Before registration or protocol freeze, Claude can help find ambiguous terms, overlapping constructs, hidden comparators, and databases that might be needed. This is brainstorming, not evidence. Save the exchange as protocol-development context and then write the formal method in human language.

Once the protocol is set, Claude should operate inside it. If Claude discovers a new term or criterion later, log the proposed amendment rather than silently changing the search.

Treat AI screening as assisted screening

For title and abstract screening, Claude can produce a ranked queue and suggested reasons. The review team should still decide whether the classification is accepted, overridden, or escalated. A useful output includes record ID, classification, confidence note, and the phrase in the abstract that triggered the classification.

If a review requires independent dual screening, do not treat the model as an independent human reviewer. It may be useful as a third assistant for conflict explanation, but governance should be declared in the methods.

Extraction should be fielded and source-tied

Evidence extraction is where Claude becomes genuinely useful. Ask for structured fields: study design, setting, sample, intervention or exposure, comparator, outcomes, effect estimates, limitations, funding, conflicts, and notes. Require a supporting passage or table marker for each field.

Do not let Claude fill missing cells from background knowledge. Missing is a valid value. In a systematic review, an empty cell that accurately reflects the paper is better than a fluent invented value.

Report AI use plainly

If Claude materially assisted search design, screening, extraction, translation, coding, or drafting, describe the task, date, model or product surface when available, human verification process, and whether outputs were retained. That makes the review more reproducible and easier to evaluate.

Cochrane and other evidence-synthesis organizations have emphasized responsible AI standards because automation can help but also disrupt integrity. The practical response is not avoidance; it is transparent method design.

Workflow checklist

1. Use Claude to stress-test the review question before protocol freeze.
2. Run searches in declared databases and save full search records.
3. Use Claude to assist screening with passage-tied reasons.
4. Human reviewers accept, reject, or escalate classifications.
5. Extract evidence into a locked structured table.
6. Use Claude to draft synthesis only from the table.
7. Report AI assistance and verification in the methods.

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