Health economics

Health economics

Efficient healthcare isn’t just about spending less—it’s about making better spending. I offer guidance and practical support in building and using models that inform better decisions.

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FAQ

What projects are included in health economics?

I offer two main types of health economics services:

  1. Modelling for health economic evaluation
    • Defining tailored cost-effectiveness questions and economic analysis plans
    • Developing decision-analytic models (e.g., Markov, decision trees, hybrid decision models) to inform resource allocation
    • Writing methods and results sections for reports and publications
  2. Systematic reviews of health economic evidence
    • Identifying, appraising, and synthesising published economic evaluations
    • Summarising economic findings
    • Critically evaluating cost-effectiveness evidence against established standards
    • Supporting scoping and question development to focus reviews on economic outcomes
    • Presenting review findings clearly for reports and publications
  • Budget impact analysis (BIA) or financial forecasting
  • Pricing or market access strategy development for commercial products
  • Primary data collection (e.g., patient surveys, clinical trials) for economic inputs
  • Health technology assessment (HTA) submissions for industry clients
  • Legal, regulatory, or reimbursement consultancy services outside academic and policy-focused contexts
  • Network meta-analyses (NMA) are not conducted as part of my health economics services, though I can integrate NMA results into economic models when available
  • Discrete event simulation (DES) models are not offered; I focus on cohort-based models like Markov and decision trees for economic evaluation.
  • Microsimulation models, including individual-level simulations, are not provided
  • Draft outputs (models, reports, summaries) are shared for structured feedback
  • Revisions are completed in iterative rounds, incorporating client comments for accuracy and clarity
  • Version control and scheduled check-ins ensure transparent, efficient progress toward final deliverables
  • Following established frameworks like NICE, ISPOR , CDR, Cochrane and PRISMA  for conducting and reporting systematic reviews of economic evidence
  • Documenting all methods, assumptions, and data sources to ensure transparency and reproducibility
  • Seeking peer-review checks from technical experts and academic collaborators throughout the process
  • Using validated tools and software (e.g. Excel, R, GRADEpro, etc.)
  • Updating methodologies regularly by incorporating new evidence, standards, and best practices

I use a range of tools depending on the project needs. These typically include:

  • For economic modelling:
    • MS Excel – for flexible and transparent model development (e.g. Markov models, decision trees, for statistical analysis, probabilistic sensitivity analysis (PSA), and parametric simulations
    • R or RStudio – for more complex modelling scenarios
  • For reviews of economic evidence:
    • Rayyan  – for screening and managing systematic reviews, for reference management and deduplication
    • MS Excel – for data extraction and evidence synthesis, and for tracking decisions
    • MS Word, Excel, PowerPoint, and Canva – for creating reports and visualisations

Upon agreement, you will receive tailored deliverables depending on the service provided. These may include:

  1. Modelling for health economic evaluation:
    • Model files with full documentation of structure, assumptions, and parameters
    •  Sensitivity analysis outputs and scenario testing results robustness
    • Written methods and results sections ready for inclusion in reports, publications, or policy submissions
    • Interpretation summaries, highlighting key findings and policy implications
  2. Reviews of economic evidence:
    • Structured review report, including search strategy, inclusion criteria, and economic evidence tables
    • Summary of economic findings for each comparison/intervention, including economic evidence statements
    • Critical appraisal assessments using standardised tools (e.g., CHEERS, Drummond checklist, CHEC/Evers 2005, etc.)
    • Supporting files, such as PRISMA flow diagrams and data extraction tables
    • Written methods and results sections ready for inclusion in reports, publications, or policy submissions
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Project timelines depend on the complexity and scope of work, but typically:

  • Modelling for health economic evaluation: 6–12 weeks for standard models (e.g., Markov, decision trees); longer for complex or iterative projects
  • Reviews of economic evidence: 8–16 weeks for full systematic reviews, depending on search scope, study volume, and reporting needs
  • Shorter scoping reviews or rapid reviews: typically 4–6 weeks

Interim deliverables (e.g., preliminary findings, draft reports) are provided during the project for early feedback

Timelines are agreed upfront, with adjustments possible based on project needs or client input

  • Rates depend on the project type, complexity, and timeline—whether for modelling, evidence reviews, or combined services
  • Fixed-fee options are available for clearly defined projects (e.g. a standard economic model or systematic review)
  • Hourly or daily rates apply for ad-hoc support, consultancy, or iterative work
  • Transparent quotes are provided upfront after initial scoping discussions
  • Discounts for academic collaborations or non-profit projects can be discussed
    1. ‘All-inclusive’ package (best for full-service projects where I manage the end-to-end project process process):
      • Standard economic models: €2,000–€3,000
      • Full systematic reviews of economic evidence: €1,500–€2,000
      • Rapid/scoping reviews of economic evidence: €1,000–€1,500
    2. Hourly rate (recommended for updates, revisions, or targeted support during or after project completion):
      • €25.00/hour for updates or ad hoc support
    3. ‘Per-stage’ fee (only for reviews of economic evidence):
      • Step 1 (protocol development): €500–€700
      • Steps 2–7 (Search strategy, -final synthesis and report): €1,200–€1,800

My contributions may include:

Defining the objective of economic modelling
  • Framing the model to address specific economic evaluation questions
  • Aligning objectives with decision-maker needs and policy context
  • Specifying eligible population, subgroups, and comparators
  • Detailing intervention pathways based on clinical evidence
  • Selecting appropriate modelling approach (e.g., Markov, decision tree, hybrid decision model)
  • Structuring health states and transitions based on clinical pathways
  • Defining time horizon and analytic perspective
  • Applying and justifying discount rates following methodological standards
  • Testing discounting impact in sensitivity analyses
  • Identifying relevant cost categories (e.g. intervention, healthcare use, adverse events)
  • Sourcing and adjusting cost data (e.g. currency, inflation)
  • Ensuring full transparency of input derivation
  • Extracting efficacy/effectiveness data and utility data (where necessary) from robust sources
  • Including outcomes such as QALYs, LYs, clinical events
  • Documenting and justifying all clinical inputs
  • Sourcing mortality, adherence rates, adverse event risks
  • Incorporating epidemiological and demographic parameters
  • Conducting deterministic and probabilistic sensitivity analyses
  • Presenting uncertainty via CEACs, ICER ranges, and scenario analyses
  • Presenting results (narratively or in a tabulated manner) consistenly and clearly to support evidence-informed reporting
  • Constructing iterative, reproducible models using MS Excel VBA Macros
  • Building a logic framework presenting the structure of the economic model to be validated with the client’s needs
  • Performing internal and face-validity checks
  • Documenting model development and validation processes systematically

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)