How Is A Medical Review Written? | Clear, Practical Steps

A medical review is written by setting a clear question, running a structured search, screening studies, extracting data, then synthesizing and reporting.

A well-built medical review helps readers make a call fast. This guide shows the full path from idea to manuscript, with plain steps, clean structure, and checks you can copy. You’ll see what to plan, what to write, and how to prove your work meets common standards.

How A Medical Review Gets Written Step By Step

Start with a tight plan, move through a transparent search, then report what you found with enough detail to repeat the work. The flow below fits academic journals and practical roundups alike.

1) Define The Question And Scope

Pin down the clinical or policy question first. State the population, the intervention or exposure, the comparison, and the outcomes you care about. Add time frame and setting if they matter. Write one paragraph that lists inclusions and exclusions in plain words. This short block becomes the anchor for your Methods section.

2) Choose The Review Type

Pick a format that matches your aim and resources. Use the table below to match goals to formats so readers know what to expect from your synthesis.

Review Types And Uses

Type Goal When It Fits
Narrative Review Broad overview with expert context Topic mapping, background for a field
Scoping Review Map concepts, sources, and gaps Heterogeneous evidence, early-stage areas
Systematic Review Answer a focused question with a protocol Clear PICO, need for reproducible methods
Rapid Review Time-boxed summary with streamlined steps Policy deadlines, urgent guidance
Meta-analysis Quantitative pooled effect estimate Comparable studies with extractable data
Umbrella Review Synthesizes existing reviews High-level summary across topics

3) Draft A Protocol

Write a short protocol before you search. Include objectives, eligibility rules, databases, search strings, screening steps, data fields, bias tools, and the plan for synthesis. Register it if the format calls for it (many teams use PROSPERO). A locked protocol raises trust and keeps scope creep out.

4) Build The Search Strategy

List your databases and time limits. Combine subject headings with text words and set language rules only if needed. Save each full search string. Many editors expect clarity here, and readers may try to rerun your search. For detailed guidance, the Cochrane Handbook chapter on searching shows tested patterns for filters and documentation.

5) Screen Records In Two Passes

Run a title/abstract pass, then a full-text pass. Two independent reviewers reduce mistakes. Track counts with a flow diagram: records found, deduplicated, excluded at each step, and final studies included. Keep a log of reasons for exclusion at full text.

6) Extract Data Consistently

Design a form before you start. Capture study design, setting, sample size, key eligibility notes, intervention details, comparators, outcomes, time points, and funding. Test the form on two studies and refine once.

7) Appraise Risk Of Bias

Pick a tool that fits the study design. Common choices include RoB 2 for randomized trials and tools for observational studies. Rate each domain and the overall risk. Explain judgments with one or two lines, not just icons.

8) Synthesize The Evidence

Pick narrative or quantitative synthesis. When pooling, state the model, the metric, and how you handled heterogeneity. When not pooling, group by population, exposure, or outcome and point out trends and tensions. Keep claims tied to data you extracted.

9) Report With A Transparent Checklist

Reporting checklists help readers find what they need fast. The PRISMA 2020 checklist is the common standard for systematic reviews and meta-analyses. It prompts items across title, abstract, methods, results, and other notes such as registration and funding.

10) Edit For Clarity And Flow

Prune jargon where plain words work. Replace vague claims with numbers. Keep paragraphs short. Add tables and figures where they compress detail better than text. Check every table against the data file, then set alt text for each figure.

Core Sections Of The Manuscript

This section shows what to write in each part so readers can skim to the part they need and still get a full picture.

Title And Abstract

Use a direct title that names the topic, the review type, and the main outcome or target group. The abstract should reflect the study question, data sources, eligibility rules, number of included studies, core findings with numbers, and a clear takeaway. Keep the abstract structured and mirror the order of sections below.

Introduction

Set the clinical context in two or three short paragraphs. State the gap your review fills. End with a one-sentence objective that mirrors your PICO.

Methods

Write this so someone else could repeat your steps. Include protocol details, registration number if used, databases and dates searched, full search strings, screening workflow, data fields, bias tools, and synthesis plan. If you changed the protocol, say what changed and why. Readers reward candor.

Results

Start with the flow of studies. Give counts for each gate and cite the figure that shows the flow. Next, describe included studies: designs, settings, sample sizes, and outcome measures. Use a characteristics table if the set is large. Then present the main findings with numbers, ranges, and confidence intervals when available. When you use a meta-analysis, present pooled effects, heterogeneity stats, and any sensitivity checks.

Discussion

Tell readers what the findings mean in practice. Weigh strengths and limits without hedging. Compare your results with major reviews that came before yours, and explain any differences in methods or data that could drive the gap. Add short notes on how results might shift care pathways or research plans.

Limitations

List the main limits you faced: gaps in the literature, small samples, inconsistent measures, or high risk of bias in core studies. State how each limit could tilt the findings and what you did to reduce that tilt.

Practical Takeaways

End with short bullets that a busy reader can act on. Keep each line data-anchored. Avoid hype words and vague calls to action.

Search Strings That Hold Up Under Review

Good search strings pair controlled vocabulary with text words. Plan synonyms for each PICO element. Combine with Boolean logic, add study filters only when they are validated, and avoid skipping trial registries and preprints if your topic needs them. Log the date you ran each search and export the exact string. Save screenshots of database settings and save management notes for deduplication.

Documenting The Flow

Editors like visual clarity. Use a flow diagram that starts with total records, shows deduplication, and tracks exclusion steps with reasons. Keep the diagram readable on a phone; labels should be short and clean.

Data Extraction, Bias Ratings, And Synthesis Choices

Consistency beats speed. Two reviewers spot errors that creep in during long sessions. When you hit conflicts, use a third reviewer or a predefined rule. Tell readers how you handled missing data, unit conversions, and multi-arm trials. When results vary, prespecify subgroup or sensitivity checks. Report them even when they don’t move the needle, since null checks still raise confidence.

When To Pool And When Not To

Pool results only when the question, designs, and outcomes line up. If heterogeneity is high and you can’t explain it, stick with a narrative grouping. Readers prefer a clean story over a forced average.

Tables And Figures That Do Real Work

Tables can carry heavy detail without slowing the read. Use them for study characteristics, bias ratings, and key outcomes. Keep columns lean, avoid tiny fonts, and cap each with a clear caption. Every number should match the source file.

Quality Checklist For Medical Reviews

Item What To Show Proof/Evidence
Question & Scope PICO and inclusion/exclusion rules Protocol paragraph and registry ID
Search Databases, dates, full strings Saved queries and timestamps
Screening Two-stage, dual reviewers Flow diagram and reasons log
Data Extraction Preset fields and piloted form Template and pilot notes
Bias Appraisal Tool matched to study design Domain ratings with justifications
Synthesis Model choice and heterogeneity plan Stats, subgroup rules, sensitivity checks
Reporting Checklist item mapping PRISMA table or appendix
Transparency Funding, conflicts, data access Statements and links

Style, Tone, And Readability

Write for clinicians and learners who skim first. Lead with the answer, then add detail in tidy blocks. Sentences should be short and active. Keep verbs close to subjects. Prefer plain words over layers of modifiers. Where a number helps, show it.

Ethics, Registration, And Data Sharing

Disclose funding and any ties to product makers. State whether you preregistered the protocol, where data and code live, and how readers can request materials that can’t be shared publicly. If your work includes patient data, describe consent and approvals where relevant.

Visuals That Carry Evidence

Figures should earn their place. Forest plots, bias summaries, and simple bar charts add value when they present more than the text can carry. Use vector formats when you can, label axes in full words, and keep color choices accessible. Set descriptive alt text so screen readers convey the same message.

Common Pitfalls And Fast Fixes

Scope Creep

When new angles pop up midstream, note them for a later project. Stick to the named PICO to protect rigor.

Opaque Methods

Missing search strings or screening rules undercut trust. Add them in an appendix if space is tight.

Selective Reporting

Do not bury outcomes that showed little or no effect. Balance keeps readers with you.

Overstating Certainty

Match your language to the strength of the evidence. If most studies are small or at high risk of bias, say so plainly.

Submitting Your Manuscript

Before you send, run a final PRISMA pass, check figure callouts, and match every table to the Results text. Confirm reference formatting and data availability notes. Ensure your title and abstract align with the claims in the body. Many rejections stem from mismatches here, not from the findings themselves.

Tooling That Speeds The Work

Use a reference manager to store records and deduplicate. Screening platforms help with dual screening and logs. Spreadsheets or forms keep extraction tidy. Scripted workflows for meta-analysis make updates easier when new trials appear.

Plain-Language Takeaways For Busy Readers

  • State the question in one line and keep to it.
  • Log every search with full strings and dates.
  • Screen in pairs and explain every exclusion at full text.
  • Pick bias tools that match the design and justify each call.
  • Use tables and figures to compress detail without losing meaning.
  • Map your report to a checklist and show where each item sits.

Why This Process Earns Trust

Readers want clear questions, transparent methods, and claims tied to data. When you follow a registered plan, document your search, and report with a checklist, your review becomes easier to read, reuse, and update. Editors see the work, and decision-makers can act with confidence in what you wrote.