Start with a clear question, scope, and protocol; plan search terms, sources, and screening rules before you read a single paper.
New to evidence work? This guide shows you how to kick off a healthcare literature review the right way—fast, tidy, and reproducible.
You’ll map a sharp question, set boundaries, lay out a protocol, and build a search that finds the right studies without drowning you in noise.
Set The Aim And Scope
Write one precise review question. Use a format that fits your topic so you don’t drift. For treatment and prevention, a PICO or PICOTS frame works well. For diagnostics, use patient, index test, comparator, and target condition. For policy or service design, a population–concept–context frame keeps things broad yet organized.
Define what’s in and what’s out before you touch a database. List populations, settings, study designs, outcomes, languages, years, and any limits on geography. Add a short note on why each rule exists. That note will save arguments later.
Common Question Frames In Healthcare Reviews
| Framework | Best Fit | Example Question |
|---|---|---|
| PICO / PICOTS | Interventions, prevention, prognosis | Adults with type 2 diabetes; metformin vs sulfonylurea; HbA1c change at 6 months |
| Diagnostic Accuracy | Test performance questions | Adults with suspected PE; D-dimer vs Wells-guided imaging; confirmed PE within 3 months |
| Population–Concept–Context (PCC) | Broad or scoping topics | Rural clinics; telehealth follow-up; primary care settings |
Starting A Literature Review In Healthcare: The First Hour
Draft a short protocol. Keep it to one page for now. Capture your question, scope, planned sources, screening rules, data items, risk-of-bias tools, and your synthesis plan. Give the file a version number.
Pick a project name and a clean folder structure. Create subfolders for search strategies, exports, screening, extraction, and drafts. Save everything in plain text or open formats so teammates can read and edit without friction.
One-Page Protocol Checklist
- Title and review question
- Scope and eligibility rules
- Databases and grey sources
- Draft search blocks and strings
- Screening plan and reviewer roles
- Data items and outcomes
- Risk-of-bias approach
- Synthesis plan and subgroup checks
Design The Search Strategy (Databases And Terms)
List where you’ll search. PubMed or MEDLINE for biomedicine, Embase for drugs and European journals, CINAHL for nursing and allied health, and the Cochrane Library for trials and reviews. Add one regional source if your topic needs it.
For methods and examples, the Cochrane Handbook lays out tried-and-tested steps.
Sketch your concept blocks from the question. Convert each block to synonyms, word variants, and subject headings. For PubMed, pair free-text with MeSH. For Embase, use Emtree. Add spelling variants and truncation so you catch phrasing you didn’t expect.
If you’re new to controlled vocabulary, start with Using MeSH and test how headings map to your topic.
Map Keywords And Subject Headings
Scan a handful of on-target articles and copy the indexing terms you see. Add broader and narrower headings where needed. Pair each heading with core synonyms, abbreviations, and spelling variants in free text. This blend lifts recall while keeping precision.
When a core concept lacks a perfect heading, lean on proximity and phrase variants in free text. Track every string you try so you can retrace your steps and defend choices later.
Build A PICO-Driven Query
Start with the population and the main intervention or exposure. Add the comparison only if it’s specific; many searches work better without it. Add the key outcome terms sparingly—too many outcome words can choke recall.
Use AND to combine blocks and OR within each block. Pair free-text with field tags like [tiab] in PubMed. Add proximity where supported by the platform to keep linked phrases tight without quotes.
Choose Filters With Care
Study-design filters can help when your scope is tight. Use peer-reviewed filters from library teams rather than ad-hoc strings. Limit language or year only when it ties to your aim, not for convenience.
Pilot The Search And Refine
Run a quick draft in your main database. Check the first 100 hits. Do you see known sentinel papers? If not, scan subject headings on a few on-target articles and expand your blocks. If results look noisy, tighten proximity, drop vague terms, or add a study-design filter that fits your scope.
Save the exact search string and the run date in a text file. Capture the number of hits. You’ll need those details when you report methods and build your flow diagram.
Grey Literature And Registries
Add trial and guideline sources when your topic demands it. A clinical registry can surface unpublished or ongoing trials; conference books can catch early signals. Document every source and date so readers can repeat your path.
Set Up Screening And Data Management
Export results from each source in a clean, deduplicated set. Use a reference manager or screening tool that can tag records and track decisions. If you’re working in a pair, record who screened what and how conflicts get resolved.
Write simple, testable eligibility rules. One line per rule. Pilot them on a 50-record sample. If two people disagree often, refine the wording until agreement jumps. Then lock the rules.
Eligibility Rules That Work
State the population, condition, setting, and minimum design requirements plainly. Note any mandatory outcomes or follow-up windows. Flag typical edge cases—mixed populations, subgroup reports, early phase trials—so reviewers handle them the same way every time.
Reference Management Tips
Keep a single master library and a dated export per source. Use consistent tags for decisions: included, excluded-title, excluded-abstract, excluded-full text with a reason code. Back up the library to a shared drive.
Deduplication Basics
Combine exports into one library, then remove exact matches on identifiers such as DOI, PubMed ID, or trial registration. Next, sweep for near-duplicates using title, first author, and year. Keep the fullest record and tag the rest as duplicates rather than deleting, so you can restore a record if a later step needs a missing field.
If two records look similar but not identical, open the PDFs or abstracts side by side. Check journal, volume, sample size, and follow-up windows. Conference abstracts that later became full articles should stay as one unit; keep the most complete version and note the link in your library.
Document Names And Versioning Tips
Name files with a prefix for the step, a short label, and an ISO date, such as 01_protocol_v1_2025-09-16 or 03_search_pubmed_2025-09-16. That pattern sorts cleanly in a folder and helps teammates spot the latest file at a glance.
When you revise a search or a rule, bump the version number and add a one-line change note at the top of the file. Small habits like this keep the team aligned and make your methods section almost write itself.
Track Records With A Flow
Keep a tally at each step: found, deduplicated, screened, assessed in full, excluded with reasons, and included. A standard flow diagram makes this simple; the PRISMA 2020 checklist links to templates.
Appraise Study Quality
Pick a risk-of-bias tool that matches your designs. Randomized trials use a domain-based tool; observational designs use checklists tuned to confounding and selection issues; diagnostic accuracy has tools for patient flow, reference standards, and blinding.
Calibrate on two or three studies as a team. Write short notes behind each judgment so readers can see how you called it. If you downgrade, explain what you saw and why it matters for the outcome in question.
Synthesize And Map The Evidence
Decide whether a narrative summary or meta-analysis fits your data. If effect measures, populations, and follow-up line up, a pooled estimate may help. If designs, measures, or settings clash, a structured narrative with tables and plots can answer the question cleanly.
Shape your plan now, even if you’re still early. List the outcomes you’ll summarize, the subgroups you’ll check, and any sensitivity checks you’ll run if enough data appear.
Scoping Versus Systematic: Pick The Right Path
If you’re mapping concepts, a scoping review suits early-stage topics, broad questions, and method mixes. If you’re answering a tight effect question, a systematic review with prespecified outcomes and appraisal fits better. Pick the path now so your method steps match your aim.
Either path needs a protocol, a transparent search, clear eligibility, and an audit trail. The difference lies in depth of appraisal, synthesis plans, and how tightly outcomes are defined.
Team Roles And Calibration
Name who writes strings, who screens, who extracts, and who appraises. Set response times so work doesn’t stall. Do a calibration round on titles, abstracts, and full texts. Measure agreement informally and fix rules before you scale.
Keep short debrief notes after each round. Note tricky patterns—cluster trials labelled as cohort, subgroup papers with overlapping samples, or split publications. Add quick rules so the whole team reacts the same way when those pop up again.
Write While You Read
Draft methods sections as you go. Drop in your question, scope, databases, dates, full search strings, and screening workflow. Paste a blank flow diagram and fill it as counts settle. Future-you will thank you.
Build a short extraction template. Include study ID, setting, sample, exposure or intervention details, comparators, outcomes, time points, and analysis notes. Keep units consistent so pooled work later doesn’t stall.
Data Extraction Fields That Pay Off
- Study identifiers: author, year, registry ID
- Setting and sample: country, care level, inclusion notes
- Intervention or exposure: dose, schedule, delivery
- Comparator: usual care, placebo, active control
- Outcomes: definitions, windows, measurement tools
- Effect data: counts, means, confidence intervals
- Follow-up and attrition: time points, losses
- Notes: deviations, author queries, funding
Common Pitfalls And Quick Fixes
Scope creep: If your hit list balloons, trim outcomes or settings, not the core population.
Vague eligibility: Rewrite rules in plain language and retest on a sample until agreement rises.
One-database bias: Add a second core database and a trial registry if interventions are central.
Search drift: Freeze strings once they perform; log tweaks with dates and reasons.
Lost audit trail: Save every string, export, and decision list in dated folders.
Minimum Files To Finalize Before Screening
| Item | What It Covers | Format |
|---|---|---|
| Protocol (v1.0+) | Question, scope, methods | PDF + editable source |
| Search Log | Exact strings, dates, hit counts | Plain-text file per source |
| Eligibility Rules | One-line, testable items | Locked after pilot |
| Screening Plan | Who does what; conflict path | Single page |
| Data Template | Outcomes, time points, units | Spreadsheet |
| Risk-Of-Bias Form | Domains and notes | Checklist or web form |
Ethics, Transparency And Registration
Declare funding and potential conflicts in your protocol and manuscript. If you plan a systematic review with public impact, register the protocol so readers can track changes. Share your search strings and screening rules in an appendix or a repository. For reporting, the PRISMA 2020 checklist keeps your write-up clean.
How To Start Your Healthcare Literature Review Plan
Block two focused sessions for setup. Ninety minutes for the protocol and folders. Ninety minutes for the first search and a 100-record pilot. That small sprint creates momentum and flushes gaps early—before you scale.
If your topic is fast-moving, schedule an update run before writing results. Lock your rerun date in the protocol so readers can see the cut-off.
Begin Your Healthcare Literature Review Workflow
You’re ready to start. With a tight question, a short protocol, reliable searches, and a clear audit trail, you’ll save weeks later and cut rework. Start small, write as you go, and keep every step reproducible.
Trusted Standards To Keep You On Track
When you need a yardstick, lean on the Cochrane Handbook for method detail and the PRISMA 2020 checklist for reporting. For PubMed indexing terms, Using MeSH is the fastest primer.
Bookmark these pages, store your strings, and keep versioned notes; those small steps protect rigor, speed writing, and make updates later feel like routine maintenance, not rebuilds.