Real world evidence

Real world evidence (RWE) is evidence that is generated from real world data (RWD), which is obtained from observational data from outside of the clinical research settings, including electronic medical records (EMRs), claims and billing data, product and disease registries, and increasingly, data gathered by personal devices and health applications. RWD and RWE generation may be used to support clinical trial designs and observational studies for innovative interventions and to support post-market regulation. Such research includes an assessment of factors which may impact uptake, adherence and compliance in clinical practice.    

Patient-level data analysis

Patient-level data is disaggregated individual data which may be used to evaluate the safety or efficacy of an intervention and also identify modifiers of treatment effect. Multivariable prediction models may be developed using cross-sectional or longitudinal patient-level data to evaluate the association of prognostic markers.

Burden of illness studies

Burden of illness (BoI) studies analyse the impact of illness or disease upon populations through combination of mortality and morbidity measures into summary statistics of population health by subgroup. Further, the economic and quality of life impact on the patient, caregiver and society may be analysed.

Cost-effectiveness analyses

  • Early planning models
  • Survival modelling and extrapolation
  • Cohort models and individual patient-level simulations
  • Core (global) economic models or HTA agency specific models
  • Model adaptations

Cost-effectiveness analyses are conducted to evaluate the effectiveness of two or more treatments relative to their cost. HCD Economics has expertise in undertaking HTA and economic evaluations on a range of healthcare interventions spanning pharmaceuticals, medical devices, diagnostic technologies, surgical procedures and public health interventions.

Budget impact modelling

Budget impact analyses are used to estimate the predicted change in expenditure to a specific budget holder resulting from a decision to reimburse a new intervention at an aggregated level. The budget (or financial) impact is usually calculated using a budget impact model, over a period of 1 to 5 years, at a national level or for local healthcare payers and providers.

Network meta-analyses and indirect treatment comparisons

Evidence-based decision making requires comparisons of all relevant competing treatments. In the absence of randomized controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analyses provide useful evidence for carefully selecting the optimal treatment strategy. Mixed treatment comparisons are a special case of network meta-analysis which combine direct and indirect evidence for particular pairwise comparisons, thereby synthesizing more evidence than traditional meta-analyses.

Structured and targeted literature reviews

A structured and targeted literature review uses explicit methods to rapidly identify, select, critically appraise, qualitatively analyse and interpret key relevant research.

Systematic literature reviews

A systematic literature review uses systematic methods to identify, select, critically appraise, qualitatively analyse and interpret exhaustive relevant to the research question; the studies are identified, selected and critically appraised by two or more independent reviewers. Where appropriate and feasible, a quantitative analysis and a statistical summary, such as a meta-analysis, is performed.

Preference elicitation studies

Preference elicitation studies apply economic methods to reveal preferences of patients and health professionals to inform decision making. In the absence of revealed preference data, Discrete Choice Experiments (DCE) are a quantitative technique for eliciting preferences that involves asking individuals to state their preference over hypothetical scenarios, goods or services. Each alternative is described by several attributes and their responses are used to determine whether preferences are significantly influenced by the attributes and also their relative importance.

Health-related quality of life/utility studies

Quantifying the health impact on patients through the generation of utility data greatly strengthens HTA evidence submissions. Time trade-off (TTO) interviews are conducted to assess the utility value of specified health states to calculate quality-adjusted life-years (QALYs) and this data can be input into a cost-effectiveness model.   

Patient-Reported Outcome (PRO) measure research

Robust evidence-based approaches to ensure the selection of the most appropriate PRO and patient-centred outcome (PCO) measures used with trial design. HCD Economics can design qualitative, quantitative, and mixed methods research studies to generate evidence for the validity or support the full development and validation of PROs. HCD Economics conduct PRO measure validation, including cognitive debriefing interviews, psychometric validation and translation.

Mapping studies

Quality-adjusted life years (QALYs) are the preferred metric for the economic evaluation of health interventions. However, preference-based measures used to obtain utility values are often not included in clinical studies. Therefore, other measures of health outcomes may be used to ‘map’ or ‘crosswalk’ from other measures of health outcomes. Mapping studies can provide a route for linking outcomes data collected in a trial or observational study to the specific preferred instrument for obtaining utility values to calculate QALYs.