Evidence reviews

Evidence reviews

Too much data and not enough clarity? I help you find what really matters. I provide high-quality evidence syntheses that get timely results without breaking the budget

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FAQ

What types of evidence reviews can you help with?

If you’re uncertain about which type of review is most appropriate for your question, I can provide guidance based on your topic, objectives, and available resources.

  • Reviews of clinical evidence:
    • Network meta-analysis of primary studies
    • Diagnostic test accuracy reviews
    • Prognostic reviews
  • Reviews of qualitative evidence:
    • Rapid/scoping reviews
  • Reviews of economic evidence:
    • Quantitative evidence syntheses
    • Rapid/scoping reviews
  • Reviews of mixed-methods evidence:
    • Rapid/scoping reviews

My support for evidence reviews covers the full end-to-end process. Upon agreement, services may include:

Technical and analytical support

  • Developing review protocols, including defining PICO questions and eligibility criteria
  • Designing and executing systematic searches across relevant databases
  • Screening and selecting studies using reproducible tools
  • Extracting and synthesising clinical, qualitative, or economic evidence
  • Applying critical appraisal tools (e.g., GRADE, ROB 2, ROBINS-I, CERQual)
  • Drafting narrative summaries, structured tables, and meta-analytic outputs
  • Preparing consultation responses and technical appendices

Planning and project management

  • Creating a custom roadmap aligned with your project goals
  • Tracking milestones, timelines, and deliverables
  • Leading project meetings and providing regular updates

Communication and delivery

  • Preparing high-quality documentation suitable for publication or review’s submission
  • Addressing queries and offering technical clarification on methods and results
  • Supporting client communication needs (e.g., stakeholder presentations, executive summaries)
  • Sharing live documents via secure cloud platforms (Google Drive, OneDrive)

Each review typically follows a structured seven-step process:

  1. Protocol development – define the research question, objectives, inclusion/exclusion criteria, and methods; a protocol ensures clarity and prevents bias before the review begins
  2. Search strategy – develop and run a comprehensive search across relevant databases to capture all eligible studies; this is documented for transparency
  3. Selection of studies – screen titles, abstracts, and full texts against pre-defined criteria to identify studies that meet the review’s scope
  4. Data collection and analysis – extract relevant data from included studies using standardized forms, followed by data synthesis (narrative or statistical)
  5. Assessment of risk of bias in included studies – use validated tools (for example ROB 2, ROBINS-I, CASP checkists) to assess the methodological quality and risk of bias for each included study
  6. Summary of findings and assessment of the certainty of the evidence – summarise key findings and assess the certainty or confidence in the evidence (for example using GRADE or GRADE-CERQual)
  7. Final synthesis and report – integrate findings into a final structured report, including evidence tables, forest plots or thematic maps (if applicable), and conclusions tailored to the review’s aims
  • Each review is typically structured around key milestones (from ‘Protocol development’ to ‘Assessment of risk of bias in included studies’ or ‘Final synthesis and report’). At every step, you review deliverables and provide feedback
  • Revisions are made iteratively before advancing to the next stage, ensuring quality and alignment throughout.

We agree on a communication plan that suits you:

  • Regular meetings (for example, bi-weekly) via Zoom, Google Meet
  • Shared folder for documents (for example, Google Drive)
  • Progress tracked via a shared online file for full transparency

The process is fully flexible:

  • I can refine and complete your existing work—whether it’s a draft protocol, search strategy, or partial synthesis
  • Or I can start from scratch, designing and delivering each step from question formulation to final reporting

In both cases, I adapt my role based on timelines, available resources, and your specific needs (for example, acting as lead reviewer, co-author, or technical advisor as required)

We apply specialist software and tools at each key stage of the evidence review process, tailored to the nature of the evidence (clinical, qualitative, economic, or mixed-methods):

  • Protocol development and project management
    • MS Excel – for workflow planning
    • Rayyan – for scoping and initial screening strategy planning
    • Google meet and Google drive – Collaboration tools
  • Search strategy
  • Screening and study selection
    • Rayyan  – for title/abstract and full-text screening
    • MS Excel  – for tracking decisions 
  • Data extraction
    • MS Excel – for structured and customizable extraction forms
    • MS Excel and Word – for qualitative data extraction
    • MS Excel, REVMAN – for quantitative and clinical data extraction
    • MS Excel, R, SPSS – for economic data extraction
  • Quality appraisal / Risk of Bias (RoB) assessment
  • Evidence synthesis and analysis
    • REVMAN – for clinical meta-analyses
    • R, Stata – for advanced statistical synthesis, including meta-regression
    • MS Excel – for qualitative synthesis (e.g., thematic synthesis, framework synthesis)
    • MS Excel, Stata, R – for economic evaluations
    • MS Excel – supports mixed-methods synthesis
  • Final synthesis and report
    • GRADEpro GDT – for Summary of Findings tables
    • MS Word, Excel, PowerPoint, Canva – for creating reports and visualisations

Timelines are agreed during the initial consultation and adjusted as needed. Timelines depend on scope and urgency:

  • Full systematic reviews (regardless type of evidence: clinical, qualitative and economics): 7–15 weeks
  • Mixed-methods evidence reviews: 8–17 weeks
  • Overview of reviews:7–12 weeks
  • Narrative reviews: 6–10 weeks
  • Rapid reviews: 4–6 weeks

Your final package may include:

  • Protocol (draft or PROSPERO-registered version)
  • ‘PRISMA flow diagram’
  • Search strategy appendices
  • Study selection log and data extraction tables
  • Risk-of-bias assessments
  • Final narrative/tabulated synthesis (with visuals and forest plots)
  • Summary of findings and key research gaps
  • Related publications: scientific articles or conference abstracts

Pricing depends on complexity, steps required, and timeline. Options include:

  • ‘Per-stage’ fee (ideal for clients needing support with specific phases of the review process (for example, protocol development or data synthesis):
    • Step 1 (protocol development): €500–€700
    • Steps 2–7 (Search strategy and results-final synthesis and report): €1,200–€1,800
  • ‘All-inclusive’ package (best for full-service projects where I manage the end-to-end review process):
    • Full systematic reviews (regardless type of evidence: clinical, qualitative and economics): €1,400–€2,000
    • Mixed-methods evidence reviews: €2,000
    • Overview of reviews: €1,800
    • Narrative reviews: €1,600
    • Rapid reviews: €1,400
  • Hourly rate (recommended for updates, revisions, or targeted support during or after project completion):
    • €25.00/hour

My contributions may include:

Protocol development
  • Defining the review scope and objectives by refining the clinical question using frameworks such as PICO
  • Designing a clear and reproducible methodology, including eligibility criteria, search strategy, and planned synthesis approach
  • Drafting the protocol in line with PRISMA-P and relevant methodological or editorial requirements
  • Supporting registration of the protocol on platforms like PROSPERO
  • Time planning to ensure alignment with priorities, requirements, or decision-maker expectations
  • Drafting initial keyword lists and controlled vocabulary terms (e.g., MeSH terms, text words), linked using Boolean logic to ensure consistency with the review’s objectives and PICO elements
  • Developing and refining reproducible search strings in freely accessible databases such as PubMed, Cochrane Library, and Google Scholar
  • Piloting and adjusting search strategies to ensure sensitivity and relevance of results, documenting iterations clearly
  • Conducting a structured review of search results to identify potentially relevant studies, based on predefined inclusion/exclusion criteria – using a piloted and automated checklists
  • Locating and accessing relevant full-text articles
  • Reviewing each article against eligibility criteria, documenting decisions clearly and flagging uncertainties for team discussion or consensus – using a piloted and automated checklists
  • Handsearching and reference screening, by reviewing reference lists and citations of key studies to identify any additional relevant evidence
  • Keeping a detailed log of screening decisions (for example, PRISMA flowchart data) and reasons for exclusions

Extracting key information using standardized templates from each included clinical studies, ensuring consistency across studies—including:

  • Participant and intervention details: data on study populations (e.g., age, sex, sample size) and interventions (e.g., provider, timing, delivery mode)
  • Outcome and follow-up reporting: data on primary and secondary outcome measures, follow-up periods, and assessment tools
  • Reporting of funding/conflicts: data on funding sources and authors’ conflicts of interest to support risk-of-bias assessment

Quality assurance (QA): ensuring extracted data is complete, internally consistent, and systematic

 

  • Selecting and using the correct appraisal tool based on each study’s design (e.g., RoB 2 for RCTs, ROBINS-I etc.), ensuring a methodologically sound assessment process
  • Reviewing included studies independently to identify potential sources of bias across key domains of risk-of-bias (RoB)
  • Facilitating resolution in case of disagreements among RoB assessments
  • Highlighting studies with unclear or high RoB that may require additional judgement
  • Contributing to the preparation of visual risk of bias summaries (e.g., RoB tables or graphs) for inclusion in the final report and to inform GRADE certainty assessments
  • Assessing the certainty of evidence for each key outcome using the five GRADE domains—risk of bias, inconsistency, imprecision, indirectness, and publication bias—as outlined in the Cochrane Handbook
  • Preparing structured ‘Summary of Findings’ (SoF) tables and ‘Evidence Profile’ Tables using GRADEpro GDT to ensure standardized and transparent presentation of results
  • Incorporating the overall risk of bias judgments from earlier stages into GRADE ratings, ensuring that study limitations are appropriately considered in the certainty grading
  • Documenting and justifying all decisions to downgrade or upgrade the certainty of evidence
  • Drafting an interpretive executive summary of the main outcomes, highlighting the quality of the evidence and key implications for practice and policy
  • Following the most accreditated methodological guidance to ensure consistency with international standards in evidence synthesis
  • Synthesising findings into a clear, evidence-based narrative, highlighting key patterns, limitations, and implications for practice and research
  • Preparing a structured, publication-ready report in line with PRISMA guidelines, including visuals such as summary tables, flow diagrams, and GRADE profiles
  • Finalising the document through iterative revisions

Reviews of qualitative evidence

My contributions may include:

Protocol development
  • Defining the review scope and objectives by refining the qualitative question using frameworks such as PICOS, PerSPecTIF or SPIDER
  • Designing a clear and reproducible methodology, including eligibility criteria, search strategy, and planned synthesis approach
  • Drafting the protocol in line with and ENTREQ guidelines and relevant methodological or editorial requirements
  • Supporting registration of the protocol on platforms like PROSPERO
  • Time planning to ensure alignment with priorities, requirements, or decision-maker expectations
  • Drafting initial keyword lists and controlled vocabulary terms (e.g., MeSH terms, text words), linked using Boolean logic to ensure consistency with the review’s objectives and PICOS (PerSPecTIF or SPIDER) elements
  • Developing and refining reproducible search strings in freely accessible databases such as PubMed, Cochrane Library, and Google Scholar
  • Piloting and adjusting search strategies to ensure sensitivity and relevance of results, documenting iterations clearly
  • Conducting a structured review of search results to identify potentially relevant studies, based on predefined inclusion/exclusion criteria – using a piloted and automated checklists
  • Locating and accessing relevant full-text articles
  • Reviewing each article against eligibility criteria, documenting decisions clearly and flagging uncertainties for team discussion or consensus – using a piloted and automated checklists
  • Handsearching and reference screening, by reviewing reference lists and citations of key studies to identify any additional relevant evidence
  • Keeping a detailed log of screening decisions (for example, PRISMA flowchart data) and reasons for exclusions

Extracting in-depth, descriptive information from each included qualitative study using prestructured templates, while ensuringanalytical consistency. This information may include:

  • Capturing details such as study setting, population type, sampling strategy, and methodological approach (e.g., phenomenology, grounded theory), to understand the transferability of findings
  • First-order constructs: extracting direct participant quotations and raw narrative data that reflect the original voices and experiences reported in the studies
  • Second-order constructs: documenting the original authors’ interpretations or themes, as stated in the included studies
  • Third-order interpretations (synthesis level): comparing and interpreting across studies to identify patterns, contradictions, and overarching themes, supporting theory generation and analytical depth
  • Thematic analysis and saturation tracking, by organizing data thematically, noting when new studies stop contributing new insights—indicating conceptual saturation has been reached (where appropriate)

Quality assurance (QA): ensuring extracted data is complete, internally consistent, and systematic

  • Applying the 10-item Critical Appraisal Skills Programme (CASP) tool to assess methodological quality across domains such as study aims, design, sampling, data collection, reflexivity, ethics, and rigour of analysis
  • Identifying patterns in methodological quality across studies (e.g., limited reflexivity or weak sampling strategies) to inform synthesis and interpretation
  • Using CASP results to guide sensitivity analyses and to inform the GRADE-CERQual assessment of confidence in the review’s findings
  • Summarising appraisal outcomes in visual formats (e.g., summary tables or appraisal matrices) for inclusion in the final report or appendices
  • Applying the GRADE-CERQual approach to assess confidence in each key finding based on four domains: methodological limitations, coherence of the data, adequacy of data, and relevance to the review question
  • Integrating prior quality assessments (e.g. CASP results) to evaluate methodological limitations and support transparent confidence ratings for each synthesised theme
  • Developing thematic maps or conceptual frameworks to visually represent relationships between emerging themes
  • Documenting and justifying all confidence judgments, explaining any downgrading decisions
  • Preparing ‘Summary of Qualitative Findings’ tables using standardized formats that outline each key finding, the level of confidence (high, moderate, low, or very low), and supporting rationale
  • Drafting a narrative summary that highlights key findings, their implications, and the overall strength of the qualitative evidence base, in a format accessible to decision-makers
  • Following established methodological guidance (e.g. Cochrane, JBI, and the GRADE-CERQual approach)
  • Synthesising qualitative findings into a clear, thematic narrative, identifying overarching patterns, conceptual linkages, and key insights into experiences, perspectives, or views
  • Preparing a structured, publication-ready report in line with PRISMA and ENTREQ  guidelines, including visuals such as thematic maps
  • Finalising the synthesis through iterative revisions, incorporating team or client feedback to ensure the report is transparent, coherent, and tailored

Reviews of economic evidence

My contributions may include:

Protocol development
  • Refining the review question and scope using frameworks like  to ensure relevance for economic decision-making
  • Designing a transparent and replicable methodology, including clear inclusion/exclusion criteria (e.g. types of economic evaluations: cost-effectiveness, cost-utility, cost-benefit, etc.), planned data extraction elements (e.g. ICERs, currency year, perspective, etc.), and synthesis methods (i.e. narrative, tabular, model-based)
  • Drafting the protocol in line with PRISMA-P and economic evaluation-specific guidance
  • Supporting protocol registration on appropriate platforms such as PROSPERO
  • Drafting keyword lists and economic-specific controlled vocabulary (e.g. MeSH terms, text words, etc.) aligned with the PRISMA-EconEval framework and review objectives
  • Developing and refining reproducible search strategies in free-access databases (i.e. PubMed, Cochrane Library, NHS EED,  and Google Scholar)
  • Piloting and iteratively improving search strings to balance sensitivity and specificity, ensuring key economic studies and modelling papers are captured, with transparent documentation of adjustments
  • Conducting a systematic screening of search results using predefined inclusion/exclusion criteria specific to economic evaluations (e.g. full vs. partial evaluations, study perspective, costing methods, etc.), supported by piloted checklists or automated tools
  • Retrieving and accessing full-texts of potentially relevant economic studies, including grey literature such as HTA reports, governmental publications, and theses 
  • Screening each study against eligibility criteria, carefully assessing features like type of economic evaluation (e.g. cost-effectiveness, cost-utility, cost-benefit), time horizon, and perspective; documenting decisions and flagging any uncertainties for discussion
  • Handsearching key journals and screening reference lists of included studies and relevant reviews to identify additional economic evaluations
  • Maintaining a detailed record of screening decisions, including reasons for exclusion at each stage
  • Extracting key information using standardized templates, tailored to economic evaluations, to ensure consistency and comparability across studies—including:
    • Study characteristics: country, setting, year, population, and intervention/comparator descriptions
    • Type of economic evaluation: for example full economic analyses (e.g. cost-effectiveness analysis [CEA), etc.) versus partial economic analyses (e.g. cost analysis  [CA], etc.); etc.
    • Perspective and time horizon: e.g. healthcare system, societal, payer; short-term vs. lifetime horizon, etc.
    • Cost data: including types of costs considered (direct, indirect), currency year, sources of cost data, discount rates, and inflation adjustments, etc.
    • Outcome measures: e.g. cost per QALY gained, cost per DALY averted, net monetary benefitm, etc.
  • Preparing structured summaries of results, such as cost-effectiveness planes, incremental cost-effectiveness ratios (ICERs), and league tables, where applicable
  • Transparently noting assumptions and modelling approaches (e.g. Markov models, decision trees, hybrid economic models), to aid comparability and inform subsequent interpretation
  • Selecting and applying the appropriate critical appraisal checklist (e.g., CHEC/Evers 2005 for trial-based evaluations, Philips 2004/2006 for model-based studies, CHEERS 2013 for reporting standards, JBI Checklist for EEs or QHES 2003 depending on project resource availability), based on the design and objectives of each included economic evaluations
  • Evaluating methodological quality across key domains, such as study perspective, cost measurement and valuation, modelling structure and transparency, sensitivity analysis, time horizon, discounting, data sources, and generalisability
  • Integrating quality assessments into downstream analyses, such as subgroup or sensitivity analyses, and using these insights to inform assessments of relevance and credibility within the synthesis
  • Presenting the appraisal results clearly, using structured summary tables, heat maps, or checklist matrices, for inclusion in the final report and to support transparency in the review process
  • Assessing the certainty of the economic evidence for each key economic comparison using adapted GRADE principles (using the NICE methodological framework), considering domains such as methodological limitations, applicability to the decision context, consistency of cost-effectiveness estimates, precision of incremental cost-effectiveness ratios (ICERs), and methodological limitations
  • Preparing structured economic summary tables (e.g. adapted GRADE Evidence Profiles or Economic Evidence Statements) to transparently present key findings for each comparison—summarising costs, effects, ICERs, certainty judgments, and contextual factors influencing transferability
  • Drafting interpretive economic evidence statements for each priority comparison, highlighting the cost-effectiveness conclusions, certainty of evidence, and potential implications for healthcare policy, practice, and resource allocation
  • Following recognised guidance for economic evidence grading, such as those proposed by Cochrane Economic Methods, WHO-CHOICE, and EUnetHTA, and NICE
  • Synthesising economic findings into a clear, comparative narrative, highlighting cost-effectiveness trends, key assumptions, and contextual drivers
  • Reporting in line with PRISMA and CHEERS guidelines, using structured visuals such as cost-effectiveness tables, ICER plots, and economic evidence statements
  • Finalising the report through iterative revisions, ensuring transparency, stakeholder relevance, and alignment with methodological standards (e.g. GRADE for economic evidence)

Reviews of mixed-methods evidence

My contributions may include:

Protocol development
  • Framing the review question using appropriate frameworks such as PICO, SPIDER, or PerSPecTIF 
  • Designing an integrated and reproducible methodology, clearly defining eligibility criteria, search strategy, and planned approach to synthesising both quantitative and qualitative evidence
  • Drafting the protocol in line with PRISMA-P, ENTREQ (for qualitative components), based on JBI or Cochrane methodological guidance
  • Registering the protocol on platforms such as PROSPERO
  • Planning timelines and resource allocation 
  • Developing initial search terms and controlled vocabulary (e.g., MeSH, free-text) aligned with the mixed-methods review question and key elements across both qualitative and quantitative domains
  • Designing and refining reproducible search strategies that effectively identify both qualitative and quantitative evidence, using freely accessible databases such as PubMed, Cochrane Library, and Google Scholar and tailored filters for study type
  • Piloting and optimising search strings to ensure sensitivity and breadth—capturing studies using diverse methodologies relevant to the review’s synthesis approach
  • Screening and mapping pilot search results to understand the volume and characteristics of available evidence from both methodological domains
  • Systematically screening search results using piloted checklists and predefined inclusion/exclusion criteria tailored to both qualitative and quantitative study types
  • Handsearching references and citation tracking of key studies to detect additional relevant evidence
  • Monitoring for thematic and data saturation in qualitative strands while ensuring quantitative data are comprehensively captured
  • Maintaining a detailed screening log (e.g., PRISMA diagram), recording screening decisions, exclusion reasons, and saturation notes
  • Using structured templates to extract key data consistently across both qualitative and quantitative components
  • Capturing contextual and design details (e.g., study setting, population characteristics, sampling strategy, and methodology—such as RCTs or ethnography) to support meaningful comparison and integration
  • Extracting first-order constructs (participant quotes and direct experiences) and second-order constructs (authors’ interpretations) from qualitative studies
  • Extracting key quantitative outcomes (e.g., effect sizes, confidence intervals, p-values) alongside relevant descriptive study information to enable accurate synthesis and comparison across studies
  • Linking all extracted data to original sources with built-in quality checks to maintain traceability, completeness, and consistency across the dataset
  • Selecting and using the correct appraisal tool based on each study’s design (e.g., RoB 2 for RCTs, ROBINS-I etc.)
  • Reviewing included studies independently to identify potential sources of bias across key domains of risk-of-bias (RoB)
  • Contributing to the preparation of visual risk of bias summaries (e.g., RoB tables or graphs) for inclusion in the final report and to inform GRADE certainty assessments
  • Applying the 10-item Critical Appraisal Skills Programme (CASP) tool to assess methodological quality across domains such as study aims, design, sampling, data collection, reflexivity, ethics, and rigour of analysis
  • Identifying patterns in methodological quality across studies (e.g., limited reflexivity or weak sampling strategies) to inform synthesis and interpretation
  • Using CASP results to guide sensitivity analyses and to inform the GRADE-CERQual assessment of confidence in the review’s findings
  • Summarising appraisal outcomes in visual formats (e.g., summary tables or appraisal matrices) for inclusion in the final report or appendices
  • Applying the MMAT (Mixed Methods Appraisal Tool) to assess qualitative, quantitative, and mixed-methods components consistently, supporting coherent integration and interpretation
  • Using integrated synthesis frameworks (e.g. convergent segregated, sequential, etc.) to combine data domains either independently or in merged form, depending on methodological fit
  • Implementing integrated designs that allow for side-by-side comparison, joint displays, or narrative weaving—enabling a deeper understanding of not just what works, but how and why
  • Assessing confidence in review findings using the most appropriate tools: applying GRADE for quantitative outcomes and GRADE-CERQual for qualitative syntheses—covering domains such as risk of bias, inconsistency, adequacy, and relevance
  • Preparing integrated Summary of Findings (SoF) tables that transparently present both statistical outcomes and thematic findings, using tools such as GRADEpro GDT and tailored CERQual summary templates
  • Drafting interpretive summaries that bring together statistical certainty and thematic richness—highlighting what works, how it works, and how confident we can be in each type of evidence
  • Following internationally endorsed guidance from Cochrane, JBI, and the GRADE Working Group
  • Integrating qualitative and quantitative findings into a cohesive, evidence-informed narrative
  • Preparing a structured, publication-ready report following best practice guidelines (e.g. PRISMA, JBI, ENTREQ), with clear visuals such as flowcharts, and thematic or meta-analytic diagrams
  • Finalising the report through iterative peer and stakeholder feedback, ensuring the synthesis is coherent, balanced, and clearly communicates the confidence in both qualitative and quantitative finding