Goal of the analysis:
Investigate and quantify the economic and clinical value of a medical device. This includes measuring cost-effectiveness, comparative clinical outcomes, and quality-of-life impacts to inform payers, providers, and regulatory bodies.
Data required:
- Clinical trial data and real-world evidence showing device efficacy and safety
- Healthcare cost data (for example, hospital costs, outpatient care, medication use)
- Quality-of-life metrics (for example, patient-reported outcomes, utility scores)
- Relevant comparator data (standard of care or alternative treatments)
- Epidemiological data on the target patient population
- Payer policies and reimbursement rates
- Existing health economic models or published literature in the therapeutic area
Detailed step-by-step instruction on how to conduct the analysis:
- Define key economic and outcome endpoints. Clarify which measures (for example, cost per QALY, incremental cost-effectiveness ratio (ICER), hospitalization rates) are most relevant to stakeholders.
- Gather clinical and cost data. Collect comprehensive information on direct and indirect healthcare costs, as well as clinical outcomes from published studies or internal trials.
- Select appropriate model framework. Determine whether to use cost-effectiveness, budget impact, or other modeling approaches (for example, Markov models, decision tree analyses) based on the device’s characteristics and available data.
- Build or adapt a health economic model. Input the clinical and cost data, define time horizons, and set up model parameters (for example, discount rates, transition probabilities).
- Validate model assumptions. Conduct sensitivity analyses, scenario testing, and peer reviews to ensure the model’s accuracy and robustness.
- Calculate key results. Estimate outcomes such as cost per QALY gained, total cost savings over a defined period, or improvement in patient quality of life.
- Benchmark against comparators. Compare model outputs to existing treatments, focusing on cost-effectiveness thresholds or value-based pricing benchmarks relevant to target markets.
- Summarize findings for stakeholders. Present clear economic and clinical outcomes to payers, providers, and regulatory agencies, highlighting potential budget impacts and patient benefits.
Format of the output of analysis:
- A written report detailing model methods, results, and conclusions
- A summary table or dashboard presenting cost-effectiveness ratios, budget impact figures, and clinical outcome measures
- Sensitivity analysis charts illustrating how variations in key parameters affect cost-effectiveness
- An executive summary highlighting the device’s economic value and implications for reimbursement or pricing
How to interpret results:
- An incremental cost-effectiveness ratio (ICER) below commonly accepted thresholds (for example, USD 50,000 per QALY) suggests favorable cost-effectiveness.
- Large budget impact savings can indicate strong value for payers and healthcare systems.
- Sensitivity analyses help identify which variables (for example, device price, complication rates) most significantly affect outcomes, guiding risk management and pricing strategies.
Steps a company can take to improve on this measure:
- Gather robust, high-quality clinical and economic data, both in trials and real-world settings, to strengthen model credibility.
- Collaborate with payers and health economics experts early to shape relevant endpoints and study designs.
- Update the model as new data emerges or as market conditions shift (for example, price changes, new competitor entries).
- Provide training and explanatory materials to stakeholders (for example, hospital administrators, insurers) to help them understand and apply model insights.
- Employ continuous feedback loops, refining health economic models in partnership with external research organizations and key opinion leaders.
